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Tag Archive for: AI

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Hello Merge Tag, Politics

Are Democrats Ready for Our First Truly AI Election? with Jack Welty | Hello Merge Tag Ep. 53

Are Democrats Ready for Our First Truly AI Election? jack welty

 

“Every day that we are not adopting this stuff, the other side is moving faster. And I think ultimately that’s going to translate into votes.” — Jack Welty

This is the first election cycle where what ChatGPT, Gemini, and Grok say about candidates could actually shape how voters decide. And as Jack Welty sees it, our side isn’t ready.

Jack served as Deputy Chief Analytics Officer on the Harris for President campaign and led paid digital analytics for Biden-Harris in 2020. He co-authored a paper on practical AI adoption for campaigns and is the co-creator of Caucus AI, a tool that monitors what AI chatbots are telling voters about candidates across more than 1,100 races.

He joined me on Hello Merge Tag to talk about something I don’t think our side is taking seriously enough.

The conversation covered a lot of ground. But the through line was this: Democrats are falling behind Republicans on AI adoption, and the gap isn’t closing. The American Association of Political Consultants found that 44% of Republican consultants use AI daily. Only 28% of Democrats do.

A few things that stuck with me:

The biggest wins from AI aren’t the sexy stuff. Jack’s argument is that the most underrated use of AI on campaigns is automating the boring, high-volume work that eats up staff hours. On the Harris campaign, his team fed thousands of post-shift volunteer feedback surveys into a language model and got back structured reports by date, state, and issue type. What would have required an engineer and custom code 18 months ago, he says you could now do by dragging a folder into Claude.

AI is a management challenge, not a technical one. This reframe is the most useful thing I took away from the conversation. You don’t need to know how to code. You need to know how to delegate, review, and give feedback. The analogy Jack uses — treating AI like an eager but inexperienced junior staffer — is exactly right. You wouldn’t hand an intern a blank page and say “write me a report, see you at 5.” You’d give them examples, context, and check in along the way. Same deal here.

Which chatbot a voter uses quietly determines which media ecosystem they’re in. Caucus AI tracks what ChatGPT, Gemini, and Grok tell voters about candidates. The responses are broadly factual — nobody’s telling voters who to pull the lever for. But the sources each model cites are very different. Grok cites social media. ChatGPT leans heavily on its national media partnerships — Axios, AP, Washington Post. Gemini casts a wider net and is more likely to cite local news. Same question, three different information worlds.

Your .gov site matters more than you think. This is something I had definitely been sleeping on. Caucus AI found that official government sites get cited by these models at a much higher rate than campaign sites. If you’re an incumbent and your official site is a graveyard of four-year-old press releases, you’re leaving something real on the table. Same goes for Ballotpedia — candidates can fill out their own candidate surveys, and Ballotpedia is one of the top two or three cited sources across most of these models. Most campaigns aren’t doing this. They should be.

ChatGPT indexed a brand new Wikipedia page in 12 minutes. Caucus AI created a Wikipedia entry for a lesser-known candidate and within 12 minutes, ChatGPT was citing the brand new page. Two-thirds of all sources in its subsequent answers about those candidates came from that single page. There’s no fact-checking layer. No delay. It’s pretty clear your campaign needs a Wikipedia strategy!

Top takeaways:

  • Democrats are behind Republicans on AI adoption and the gap isn’t closing. This is a competitive disadvantage that will eventually show up in votes.
  • The biggest wins come from automating routine, high-volume work — not from generating content or running AI-powered ads.
  • Treat AI like a junior staffer. Give it context, examples, and check its work. The management skills matter more than the technical ones.
  • Update your Ballotpedia candidate survey. Make sure your robots.txt isn’t blocking AI crawlers. If you’re an incumbent, don’t neglect your .gov site.
  • Caucus AI is tracking 1,100 races across three models and publishing their findings at caucus-ai.com. Worth bookmarking.

Listen to the full episode right here, or wherever you stream podcasts.

If you prefer video, you can also watch our full conversation:

Find all episodes at HelloMergeTag.com or wherever you stream podcasts.

Links

The white paper Jack wrote with Meg Schwenzfeier

Caucus AI

Jack’s email | LinkedIn | Twitter

The blog post I wrote about asking ChatGPT to compare the email programs of Joe Biden and Donald Trump

 

Big thanks to our sponsors:

Civic Shout. Learn more about the great work they’re doing to help Democratic campaigns and progressive nonprofits build their lists ethically at civicshout.com/partners.

 

Episode Transcript

This transcript was automatically generated and has not been copy-edited. While it can serve as a helpful guide to our conversation, it may contain errors or omissions. For the most accurate representation, we recommend listening to (or watching) the full episode.

Josh Klemons: Jack Welty advises progressive organizations on technology strategy, data infrastructure, and product development. He served as deputy chief analytics officer on the Harris for president campaign and led paid digital analytics for the 2020 Biden Harris campaign. He co-authored a paper on practical AI adoption for campaigns and is the co-creator of Caucus AI, a research tool that monitors what AI chatbots tell voters about candidates and elections. First of all, thank you so much for coming on the pod. I really want to talk about the paper you authored, Generative AI on campaigns. In it, you argue that Democrats need to get serious about AI, but not for things like content generation, deep fakes, but for the boring stuff. Before we get into what that means practically, just give us the elevator pitch for why you think any of this matters right now.

Josh Klemons: Maybe it’s obvious to some, but like it’s probably not to others. So, lay it out for
Jack Welty: Yeah, totally. Uh, and thank you so much for for having me on. Um,
Josh Klemons: us.
Jack Welty: yeah, I mean, of all of the organizations in politics, campaigns are, as we all know, the most resource constrained. So, um, I think generative AI, especially the the big leaps we’ve seen in the tools in the last like year or so, offer an opportunity for our campaigns to get more efficient, uh, get more done and leave more time for our, uh, you know, talented staffers to focus on the hard stuff, the actual strategy problems, talking to voters, etc. Um, and why I think it’s important right now is, um, the American Association of Political Consultants has run a couple of studies uh, of their members. most certainly recently uh in March um that show that there’s a gap between uh Republican and Democratic consultants in uptake. So we are falling behind Republicans in daily AI use in building custom AI tools for our campaigns and in generally like adopting this stuff to make our organizations better.

Jack Welty: So um you know I don’t want to handwave away a lot of the concerns a lot of uh uh you know moral ethical political etc that we might have with the labs and with this technology but every day that we are not adopting this stuff the other side is moving faster and I think ultimately like that’s going to translate into into votes um so I think it it kind of behooves us to to pick up the
Josh Klemons: Yeah.
Jack Welty: pace
Josh Klemons: So the numbers you like the AAPC 44% of Republican consultants are using AI daily versus only 28% of uh of Democrats. So, I guess my first like what do you think Republicans are using AI for that Democrats aren’t? Um like do you have a sense of
Jack Welty: Yeah, that’s a great question.
Josh Klemons: that?
Jack Welty: Um, there’s a little bit more in that AAPC study. Um, I don’t think they’re using it for anything crazy. I mean, we are seeing some of the like content generation wars and we don’t have to get too deep into like

Josh Klemons: Okay.
Jack Welty: the NRSC memes. I think a lot of that stuff is probably going to backfire. Um, what Meg and I focused on more in the paper is like just just wrote task automation. You know what I mean? Like I think that Republicans that are using this have more time in their day to think about strategy and higher level problems because they’re spending less time summarizing memos or data entry or what have you. Um, and so that’s where we’re falling behind less on the sort of I don’t think anybody should should put their campaign strategy, you know, totally up to Claude or anything.
Josh Klemons: That seems like a good losing strategy for sure,
Jack Welty: Yeah.
Josh Klemons: right? A tool that doesn’t really understand what the hell’s actually happening in the world,
Jack Welty: Yeah.
Josh Klemons: doesn’t understand real time results. Um, the other day I asked it a question and it had to like look up who Zon Mom Donnie was and figure out who was the mayor of New York. And it’s like, yeah, if if you don’t understand the context, you’re probably not going to give me like updated answers.

Josh Klemons: But like the argument you’re making is that AI like I think a lot of people the movies and you know like the internet makes it seem like AI is about the sexy stuff like you know the NRSC is running ads now she’s dropped out but like Janet Mills using AI but you’re actually arguing that we should be using more of like the boring tools the automating high volume low complexity work that’s taking up staff hours which is what you just alluded to Republicans are using it so they could spend more time thinking about strategy. So, what did that look like on the Harris campaign? Or maybe it was too soon to say because AI’s come so far since then, but like in your mind,
Jack Welty: Yeah.
Josh Klemons: give us some concrete examples of like what would you if you’re getting hired as a consultant tomorrow or you’re just talking to a friend who’s just drowning in work,
Jack Welty: Yeah.
Josh Klemons: what’s the first thing you’re doing to help take some of that off their plate and letting AI take the boring stuff off their plate so they can do the actual like important

Jack Welty: Totally. Yeah.
Josh Klemons: stuff
Jack Welty: I have I have a great example from the Harris campaign and again this was you know far in ancient times
Josh Klemons: early in AI. Yeah, I
Jack Welty: uh in AI development back in in you know summer fall of of 2024.
Josh Klemons: know.
Jack Welty: Um but we asked um organizers and volunteers to fill out post shift feedback surveys. How was your canvasing shift? What did you hear on the doors? Did you encounter any issues? yada yada yada. Um, and this was like a great very rich source of data like God bless the volunteers that were,
Josh Klemons: Of Of
Jack Welty: you know, writing detailed notes about their camping experience, whatever. Um, but as you can imagine, especially at a national presidential campaign volume,
Josh Klemons: course.
Jack Welty: this was thousands and thousands and thousands of just free text surveys per day. Um so even with the like again in 26 terms relatively primitive tools available to us um we fed all of that into an LLM um and asked it for structured reports back.

Jack Welty: So we wanted structured summaries broken out by date and state and like type of issue. Were there specific uh flags people were running into? Did a did a staging location not have yard signs? Um, and then also sort of squishier sentiment like what were people telling you commonly on what were we hearing back commonly on the doors from voters etc. Um, and so it turned what would have you know previously been like an absolutely impossible human task of of reading through all of these responses into a like 10 minute click button run pipeline get back structured report. Um, and I think what’s really exciting about that was, you know, one that we were able to get all this actionable information that previously would have taken a bunch of staff hours. Um, but here in 2026, the tools have changed so much that two years ago, this required an engineer and some custom Python code and hitting an API and whatever. And right now,
Josh Klemons: Right.
Jack Welty: like I think my first move would be to drag that folder of surveys into Claude and ask it for a summary.

Jack Welty: And I think that would give me like a pretty good first pass. Uh compared to what required a ton of custom engineering, you know, 18 months
Josh Klemons: Yeah, that’s super interesting. Were the I’m very curious about the technical mechanism of that.
Jack Welty: ago.
Josh Klemons: Were those typed summaries or were they handwritten? Like could you have handled it if like people were filling these out at events? Like how does that work?
Jack Welty: Yeah, the these were mercifully typed surveys uh just in the back end of a Google form.
Josh Klemons: Okay, so it was pretty easy to just copy and paste.
Jack Welty: Yeah, but but the vision models have come a really long way too.
Josh Klemons: They really
Jack Welty: Uh yeah, we’ve we’ve talked about that. I I think this was in the paper as a potential use case.
Josh Klemons: have.
Jack Welty: Um uh petition uh uh survey verification. So, you know, to get on the ballot, you might go have to collect um you know, thousands of signatures. and previously that’s a that’s a human task to go type that up, look those people up in van, make sure they’re registered to vote in the right, you know, county, precinct, state, whatever.

Jack Welty: Um, I think with some of the these vision models, like we could absolutely develop a pipeline to turn that into text and then automate the lookup and um, you know, that’s tons and tons of poor ballot access fellows time uh saved per
Josh Klemons: So,
Jack Welty: campaign.
Josh Klemons: I do a lot of public speaking on like digital marketing and these days I just have a link on my deck and it’s like if you want to join my mailing list, here’s how. But back in the day, I used to like bring paper, you know, like, you know, similar to a petition kind of thing. Um, and I have these like vivid memories of sitting and trying to like sort through each and every one of those and people’s handwriting is terrible, mine included. Um, and I’m like trying to figure out what the hell that says, and then I’m having to troubleshoot it. And yeah, I like I can’t even imagine the idea that I could just take a photo of each page and be like, could you turn this into a spreadsheet? Uh, and now I’m talking about 10 years ago, but yeah, like today versus even like a year or two ago,

Jack Welty: Yep.
Josh Klemons: I have seen that like it can now like look at an image and like dissect it in a way that it could not a year or two ago. A year or two ago, you kind of had to describe it to it and today I can look at it and be like, “Oh, this is nicely designed or no, this needs work.” It’s like I don’t use chatbt for or I don’t I I stopped chat.
Jack Welty: Yeah.
Josh Klemons: I’m on cloud now, but I don’t use it for any design work, but I do sometimes feed it a graphic and say, “Do you like this?” And it gives like surprisingly good feedback like for even for designers out there like it’s worth
Jack Welty: Give me some feedback. Yeah.
Josh Klemons: knowing like if you just like have that nagging you know thing in your head saying this could be better like cloud might be able to tell you if it could be better which I think again that’s where the idea that like only about a quarter of Democratic consultants
Jack Welty: Yeah.
Josh Klemons: are using AI at all is like wild to me because I am very selective about when I use it.

Josh Klemons: I’m not using it for any strategy. Like I’m the strategist. That’s like my whole thing. But like it helps me think things through and like talk it out.
Jack Welty: Yeah.
Josh Klemons: And the idea that three out of four of us us like Democratic consultants are not using it yet.
Jack Welty: Never mind.
Josh Klemons: I mean, it’s a limitation. Like it’s I get why some aren’t. I I have questions on that. We’ll get to that. So, you describe AI as an eager but inexperienced junior staffer. So, like what does that mean for you? And like how should folks be thinking about their AI tools? Uh they’re not managers. You’re arguing they’re not managers,
Jack Welty: Yeah.
Josh Klemons: they’re interns, right? I mean, is that essentially the argument?
Jack Welty: Yeah, that that’s kind of the argument and and I think um what this means is we have to shift into that managerial critic role. Um, for some of us that have managed people, like hopefully this is a natural one, but uh, for junior staff that maybe have not managed work yet, uh, in their careers, I think that it it moves that staff development pipeline left.
Jack Welty: Uh, and so even junior staffers on campaigns need to pick up skills like delegation, review, criticism, you know, breaking work up into bite-sized tasks and stuff like that. Um because yeah, these LLMs have, you know, boundless energy as long as your token budget will account for it. Um but they need direction. Uh they need steering.
Josh Klemons: right?
Jack Welty: They need review. They will confidently plow forward with an incorrect assumption or present to you a wrong answer sort of wrapped in, you know, nice formatting. Um and it means that we have to be like really hyperritical of their outputs. We have to be good reviewers. we cannot just be you know mashing the the tab button or accept at all times. Um and then I think the other big development is you heard a lot in uh late 24 early 25 about prompt engineering. There was this idea that I mean you could tell an LLM like I’ll give you a $100 if you do this task and sometimes it would do the task better.

Jack Welty: Um this latest generation like that doesn’t that stuff doesn’t really work anymore and that was kind of a weird artifact. Um, but context engineering is even more important. And so this is sort of a fancy term that I think applies to the kind of context you would give a junior staffer. Imagine you’re onboarding someone to your organization and you want them to complete a task. You need to give them some background about what the organization is, what you believe, what the goals of the organization are, what the parameters of the task are, what the goals of the task are. Um, I think if you were asking an intern to write a memo, you would maybe give them three past examples of good memos and that would make your intern write a better first draft. Like thinking through all of those things, the more you can carefully curate good context for these models, the better answers, the better results you’re going to get than if you just again sort of like throw it some sort of raw blind question of, you know, write me a first draft of this blog post or what have you.
Josh Klemons: Right. Asking an intern to write a memo when they’ve never seen the type of memo you’re asking for is going to guarantee a bad Right.
Jack Welty: They’re gonna do a bad job.
Josh Klemons: Like, and it’s not their fault. It’s your fault.
Jack Welty: Yeah.
Josh Klemons: Like that’s bad management. But like you’re essentially arguing it’s the same with Claude. Like you can’t ask Claude to write a memo. Like a press release and like the context.
Jack Welty: Yes.
Josh Klemons: Like sure, fine. It like understands what a press release is. But if you’re trying to write a specific type of memo without showing it past examples, you should not expect a good output on the first take, right?
Jack Welty: Yeah. And if your organization has a style guide or certain conventions you wanted to follow,
Josh Klemons: And
Jack Welty: that’s something you would give that intern or junior staffer as well. So you should feed that into
Josh Klemons: yeah, I mean, in general, you talk there’s quite a bit about the idea of this being like a management challenge,

Jack Welty: club.
Josh Klemons: not a technical one. And I think that’s interesting language like that I haven’t really heard people talk about. Like so I I am not a coder. I don’t know any I I can’t write code to save my life. I just launched I just vibecoded my first tool. It’s called Shares Sparrow if you go to sharespar.com and it literally lets you take tweets and blue sky posts and turn them into um Instagram friendly graphics. And it’s an idea I’ve had in my head for years. There was a tool that did it. They went away and I was like I’m going to replace it. Um I’m not technical. It was like it’s an interesting idea that it’s a management tool because a lot of it was going back and forth like telling it like no you could be better here. There’s problems here. I really had to like micromanage. like that’s not language I was thinking about when doing it, but I had a hard time figuring out like the Twitter logo.

Josh Klemons: It was like recreating it from scratch. I was like, “No, that’s not the Twitter logo. It doesn’t look like the Twitter logo.” And I had to literally micromanage it to get it there. There was no technical component to it at all. It told me what to do. I did it. I told it what to do. It did it. Um, and we like literally had a conversation while it built a tool that I was excited about. So, I guess what I’m curious about is like of the 28% of us Democrats that are using it, is there a generational breakdown? Like do you have a sense like is the older generation better off for this or worse off for this? And vice versa the younger generation like who is better suited to actually use this? Like somebody I’m in my 40s and I don’t know how to code anything and I don’t need to now. Um somebody in their 20s who like grew up with AI essentially at this point. Like are they better off or worse off because they don’t understand the world without it?

Josh Klemons: Like do you have a sense of that? Like that’s that’s my age-old question I guess when it comes to this kind
Jack Welty: Yeah. Yeah.
Josh Klemons: of
Jack Welty: I think that’s a great question. The unfortunately the the AAPC data does not have an age breakdown and I am sort of on the hunt.
Josh Klemons: Yeah. Seems like they
Jack Welty: Yeah. I’m I’m on the hunt for for more data on this question. So if anyone knows of any,
Josh Klemons: should
Jack Welty: please send it my way. Um, I think it kind of cuts both ways because on one hand, um, you know, us us gri grizzled vets, uh, folks who have been in this space for a while, we know what good work looks like, um, and we know how to be good critics. We know how to give feedback. Um, we have good, you know, definitions of done. Um, and can sort of broad these things into shape, uh, and know not to ship slot basically. Um, so I do think uh uh as long as you know folks from an older generation are willing to lean in and learn the tools, there’s definitely an advantage.

Jack Welty: You know, all of our hard one experiences is not for not um on
Josh Klemons: Like you’re arguing that the experience to not put out garbage matters.
Jack Welty: the
Josh Klemons: Whereas if you don’t really know what good versus bad looks like, it doesn’t matter. Like what I’m hearing is it doesn’t matter how well you understand the AI tools. If you don’t understand what good output looks like, you’re never going to have good output.
Jack Welty: and not just good output but good process as well. Um uh I’ve been exper experimenting a lot more. So I’m a I’m an analyst.
Josh Klemons: Okay.
Jack Welty: I’m an analytics uh professional by trade and um have been exper experimenting a lot more with using these things to produce analysis. So having them you know write SQL, write Python, compute stats and then write analysis.
Josh Klemons: Are you a coder?
Jack Welty: Um I am yeah yeah I’m an engineer.
Josh Klemons: Just so we understand. Like Okay. So you’re like you’re much more advanced than like the average Democratic consultant when it like I I know what Python is.

Jack Welty: Um
Josh Klemons: I have no idea what how to use it. So Okay.
Jack Welty: yeah yeah yeah I’m I’m I I I’m an engineer uh when I wear some hats.
Josh Klemons: Okay. Got
Jack Welty: Um but I think knowing but I think it’s applicable to like any technical or any technical or
Josh Klemons: it.
Jack Welty: non-technical process. Um you have to know the process steps and the gotchas. Um you know even taking a a non-technical uh approach. Maybe you’re a researcher and you want Claude to help you write a research book for a candidate or something. I know I’m gonna get like a lot of researchers who come yell at me that that that’s not possible, but you wanted them to propose a research book. They Claude might go research four of the five, you know, top sources you would go check and then write you a report based on those four or five top sources. Four sources. But if Claude never checked the fifth source, you’re potentially going to be missing some information.

Jack Welty: If Claude never, you know, looked the candidate up in the voter file or something, you’re going to be missing some critical piece of information and Claude is not going to know that it’s missing. Um, I see this in analytics work all the time. Um, Claude still makes silly SQL mistakes or Claude makes assumptions about what data is in what table and doesn’t necessarily surface those assumptions for you. It just produces a nice looking deliverable that has pretty charts. Um, and so the knowledge of all those process steps, the common gotchas, the oh, if you don’t if you forget to filter voter registration status on this field, then your counts are going to be inflated in this way. Like all of that, um, you know, kind of domain knowledge is still really important and frequently for specifically our domains, it’s not in the training set. like a lot of best practices about how democratic campaigns operate are blocked behind the analyst institute payw wall or just in our heads or in our you know organizations Google drive and so that’s the type of context we still need to give these models to get good outputs um I will say on the flip side the folks that have grown up with this I think are going to be like really really dangerous in a great way um I think the AI native you know I think dropping a couple of AI

Josh Klemons: Right.
Jack Welty: native 24 year olds on a a modern campaign is going to be produce some like really really impressive outputs uh because they just you know folks have learned to use these tools uh from go.
Josh Klemons: Hey
Jack Welty: They don’t know of a way to operate without them and it means that they can sort of execute at at pretty incredible velocity. So it is not to say that like I’m discounting that entirely like I think those folks are going to really cook when they get into this space. um they’re just going to need to, you know, find a way to sort of distill some of this knowledge
Josh Klemons: Yeah. No, I think that’s really interesting. the part that like I I’m very interested in the idea that output and process can’t be differentiated especially for
Jack Welty: down.
Josh Klemons: what you’re talking about like so like building a graphic like not with AI like if I’m working with a graphic designer and they make a graphic I know if it looks good or not regardless somebody could build a website that I think looks good but is actually terrible and it’s much harder to know because process does matter because it could look gorgeous but the whole thing’s just one big image and not actually

Jack Welty: Yep.
Josh Klemons: live text and like for SEO purposes it’s trash and I see that like clients come to me with a website and I’m like uh this is a Canva image like this is not a website, you know, like I’ve seen that and like I think AI is like the next step and I hadn’t really thought about it that way like the output matters but like to get there you really have to think about the process and right if you don’t have the experience like like you learn the process the hard way pre- AAI so you know what you’re looking for I guess the question now and I don’t know if you have an answer for I don’t even know if it’s a question like how do we ensure that the like AI natives who are like coming onto the campaigns are going to like shake things up in the best possible way I agree like that new energy is always what gives our party life. How do we ensure though that they understand the processes so that they can like make sure that like AI is not building them a fancy website that’s actually trash?

Josh Klemons: You know, I think that’s the question.
Jack Welty: Yeah. Yeah.
Josh Klemons: That’s that’s the million-dollar question right there,
Jack Welty: And and I think that’s that’s the shift to the role of manager and critic. You know what I mean? Like we’re we we are not just shipping pure AI driven,
Josh Klemons: right?
Jack Welty: you know, creations. We are asking follow-up questions. we are pushing AI to prove itself to prove those process steps to verify its work in a whole bunch of ways. I mean it’s why you’ve seen AI uh advance so quickly in software engineering because those outputs are so much more verifiable like you can test the API that you’ve built and it either works or it
Josh Klemons: Right.
Jack Welty: doesn’t. Um whereas for something like analysis um you can’t you know prove that the conclusion of
Josh Klemons: Right.
Jack Welty: the analysis is right without fully inspecting all the outputs. So, I mean, that’s even a tip for I think AI use is is make these things explain to you what they did um and produce intermediate artifacts and present to you a plan for what they’re going to do before they go to do it.

Jack Welty: Which again is the type of thing that if it was an intern’s first day and you told an intern to go write a report,
Josh Klemons: Right.
Jack Welty: you wouldn’t say like, “Hey buddy, like have a good day. Come back to me at 5 when the report’s done.” You would say like, “Hey, no, like first you should gather this this particular data here.
Josh Klemons: Right.
Jack Welty: You should analyze it in this way and then you should check in with me once you’ve done that before I send you off to go write the memo or
Josh Klemons: As somebody who’s very publicly like building AI tools for the party, I assume you’re having these conversations.
Jack Welty: whatever.
Josh Klemons: Do you find that folks are having to learn that they they need to focus on process? uh like are most folks jumping in and saying write me a report to cla or chat GPT or do they recognize that that’s not how it works?
Jack Welty: Yeah, it’s a good question. I think everyone goes on their own journey. Um, I think there is there’s certainly I think folks approach it from a couple different directions.

Josh Klemons: Yeah.
Jack Welty: Both are totally valid. Like I you watch people um maybe dive in a little bit too deep and get really excited about the hype and then have to kind of pull themselves back. Um and on the flip side, you have uh folks that are, you know, totally justifiable skeptics for whatever reasons that take a sort of slower approach. And you’ll see those folks um I think advance more deliberately and maybe a little bit more carefully through all the steps of verification before they get to a final
Josh Klemons: Okay. No. Uh,
Jack Welty: output.
Josh Klemons: super interesting. So, let’s talk Caucus AI. Um, tell us about Caucus AI. Like, I I poked around on the site quite a bit. Uh, I read the about section. Um, like what does it do? Why’ you build it? Like, tell us the story behind it.
Jack Welty: Yeah. So, um, uh, Caucus AI, Caucus-ai.com, um, is a product of myself and and Meg Schwenfire, who’s my colleague from the the Harris campaign.

Jack Welty: Um, you know, a AI is replacing search. Um, millions of Americans now ask uh chat bots the questions that they used to type into Google or they still type those questions into Google and they get an AI summary instead. Um, and so uh we realized that there was no one really systematically capturing and measuring what these things were saying about um uh about political candidates or in response to political questions. Um and so you know being the good analysts that we are uh we just started by collecting data. Um so Caucus AI monitors right now three different chat bots across we have about 1100 races in the tool right now. Um we ask um an election level question just like purely factual who’s running for governor in Maryland. Um and then we ask a handful of questions about each candidate in the race. So, um, a generic bio question, a question about where they stand on issues, and then a question about their top criticisms. Um, and then we sort of present all of that data, uh, in our website.

Jack Welty: Um but then we’re also doing a whole bunch of research uh on that data that we’ve collected and and publishing that on our substack.
Josh Klemons: So you found that which chatbot a voter uses um determines which media like essentially it matters right like and it goes without saying like if you’re asking Grock which is like Elon Twitter’s you
Jack Welty: Yeah.
Josh Klemons: know AI you’re going to get a different response than if you ask cla Gemini or chatpt so like how different are the responses like what are you finding when it comes to like these different
Jack Welty: Yeah. So the the biggest difference is in the media ecosystems.
Josh Klemons: models
Jack Welty: So most of the responses are broadly factual. We are not finding um that anyone is like totally off the deep end. Um even even Grock Grock is uh unsurprisingly uh quicker to site
Josh Klemons: even
Jack Welty: the controversies uh about a political candidate. Um and Grock is actually on on either side.
Josh Klemons: on either side of the aisle or mostly just de Okay,
Jack Welty: It’s it’s still kind of early days in our research.

Josh Klemons: cool.
Jack Welty: Um, we also these things are changing rapidly all the time.
Josh Klemons: Sure.
Jack Welty: So, we’re going to be collecting these responses, you know, at least monthly through the election. So, I do think it’s possible we see things start to change as we get closer to November. Um, but uh, yeah, Grock is actually so the the media ecosystems and and and who gets cited is probably the biggest difference. Um, Grock is the only large model that we see citing social media. So obviously it sites sites Twitter um but it also sites in No Grock
Josh Klemons: only Twitter, right? It’s not citing anything.
Jack Welty: sites Grock sites Facebook Grock sites Instagram Grock sites LinkedIn um there’s actually
Josh Klemons: What? That’s
Jack Welty: a pretty wide variety of sources.
Josh Klemons: wild.
Jack Welty: Um Chatpt so OpenAI’s model um really leans in on their big national media partnerships. So OpenAI and Axios have a deal same with Washington Post with AP. So um Chetchup Tea is much much much more likely to site those new sources first um before going anywhere else.

Jack Welty: Um and then Gemini casts a much wider net. So for the average query, you know, Gemini sites like twice as many sources. Uh Gemini is quicker to site local news, stuff like that.
Josh Klemons: Is there a reason you didn’t include Claude? Is it more complicated or it just didn’t seem as relevant as the other three?
Jack Welty: When we started the project, Claude had like low low singledigit consumer US market share. Um, I think the thing to remember is like, yes, a lot of us wonky white collar knowledge workers are using COD, but your average American when they think about asking a chatbot political questions, they’re just using chat GPT. Um,
Josh Klemons: Got
Jack Welty: so we’ll probably add COD to our analysis.
Josh Klemons: it.
Jack Welty: Um, especially it it has risen in popularity in the last couple months with all the the DoD drama and whatnot. Um, but like 80% of US consumers are using Chachi.
Josh Klemons: Right. So talk to us about the uh experiment you ran with chat GPT and a brand new Wikipedia
Jack Welty: Yeah. So um you know we created cog one you know we just wanted to measure what these things were saying but
Josh Klemons: page.
Jack Welty: uh all with the goal of understanding how can we affect these responses how do they vary um what is actually getting cited. So we conducted an experiment um you know Wikipedia is one of the largest sources of these answers. Wikipedia and ballot pedia are sort of the top two for lots of these models. Um, and we created Wikipedia pages for a couple of lesserk known Senate candidates in like uncompetitive states. Um, we followed all of Wikipedia’s rules. They met Wikipedia’s notability guidelines and they were like balanced, neutral Wikipedia pages that just cited uh sort of local news stories. Um, and I think the the big headline finding is it took just 12 minutes from the publishing of that Wikipedia page for it start starting to show up in chat answers. And as soon as Chat was citing the brand new Wikipedia page, twothirds of all of the the sources it cited in its answers were that Wikipedia page.

Jack Welty: And we found verbatim sentences from the Wikipedia page that we had just written uh you know hours before showing up in you know a completely unauthenticated new chatbt request for answers about this candidate. So um yeah I
Josh Klemons: Wow. So, Wikipedia polices itself, right? So, like in theory,
Jack Welty: mean
Josh Klemons: Wikipedia should never have like bad actors. Like, yes, it could exist for a few minutes, but it’s not going to exist for months because somebody’s going to catch it. But what you’re saying is like there are ways like ChatBT is definitely manipulatable. Like, that is clear. And if you’re winning the Wikipedia fight, then you’re winning the Chat GPT fight. So are talk to us about misinformation. Like are how worried are you about bad actors?
Jack Welty: Yeah.
Josh Klemons: And are there any ways that like us as a party can better inoculate ourselves uh from those bad actors? Or is Wiki is Wikipedia essentially should we all just be donating more money to Wikipedia to protect elections forever?

Jack Welty: I I certainly think we should be grateful. you know, thank your local Wikipedia editor when you get a chance.
Josh Klemons: Seriously. Yeah.
Jack Welty: Um, uh, but I do think, you know, it it speaks to, uh, some of the both speed and opacity of these systems uh, that we don’t we don’t even really know what search index Chatt uses uh, to find this stuff. We know that right now at least it thinks Wikipedia is really trustworthy and so if you can change Wikipedia, you can show up there. But that’s not to say that that won’t change over time. Um I, you know, we have not found a ton of factual inaccuracies yet. Um but I think we are we are really in the early days here of folks trying to influence these. Um, I I think we don’t yet know if the other side is is going to, you know, create tons of astroturf Red Reddit posts to edit to to change one of these responses or, you know, push a ton of YouTube shorts to change the Gemini responses.

Jack Welty: I think it’s just it’s very very early to conclude that any of this stuff uh is is totally safe and that, you know, Wikipedia editors will save us all.
Josh Klemons: So you did find that they they seem to all actively be working to not like influence elections per se. um like they’re giving more like factual information with like even Grock who like sure as hell has controversial opinions on Twitter. Uh when it comes down to it, you’re not finding that they’re saying, “Oh yeah, that guy sucks. You should vote for this guy.” Like it’s they’re all being relatively um like careful about how they speak about elections. Is that what is that a fair assessment of your
Jack Welty: Yeah,
Josh Klemons: findings?
Jack Welty: I think that’s fair. And and we know this. I mean, the labs have have told us this. They do a ton of research um and they have a ton of incentives to keep these answers as neutral as possible, right? like the labs have giant political interests. They have big super PACs that are spending money now.

Jack Welty: Um and so they don’t want their answers to be favored by one side. So we know specifically um you know if you ask what brand of toothpaste to buy um it wants to give you a decisive uh answer like that’s how it it gets the you know the most user satisfaction is by it’ll confidently recommend you what water bottle to buy or what have you. Um, but we know that there’s this post-training layer where they try and sort of bang these models into neutrality. Um, and that’s where you get these very like wishy-washy kind of both sidesy answers which I I think make it make our jobs harder because these models really want to be neutral. Um, and so, you know, I think we have to be creative about how we put information on our websites. Um, how we think about, you know, good structured question and answer content. Um and just sort of experiment with lots of tactics to make sure that when asked they are giving you know that the answers we want them to
Josh Klemons: back during the 2024 primary, I I was tracking the Republican email program and writing about it a lot.

Jack Welty: give.
Josh Klemons: I like I did a bunch of writing on it. And then when Trump was the nominee, um I did an analysis of his email program versus Biden’s email program. This was before Harris, like it was still Biden. and I wrote up my own findings and then I went to chatpt and I asked it like essentially who had the better email program and I could not get it to I tried everything I could think of to get it to have an opinion and it refused. So I wrote about this so I finally um I came up with an interesting prompt and I said if these two people were Seinfeld characters who are they and Biden was Seinfeld and uh Trump was George. Um, and then I said, “What about Sex in the City characters?” And same deal, like Biden was the hero and uh, you know, and I think I did the West Wing as well or something. But like, like I really had to work hard to get it to give me something that was even worth putting down on paper.

Josh Klemons: And I did in the end, but like it certainly wasn’t going to say, “Oh, Biden’s emails are better.” Even though they were better, uh, in like by every objectable objective measurement. Um, you know, like, “Oh, you’re writing 10 emails a day from a bunch of different senders. That’s a spam bot.” Nope. uh he he has an interesting varied way. So yeah, it’s just an interesting I I hadn’t really connected it to like I hadn’t thought about that experiment I did with like how people need to be thinking about it. Like if you’re trying to figure out who should I vote for, well here’s what I believe, you know, like you know, it’s essentially like you have to know why you want to vote for somebody and like I assume and I haven’t tested this. I assume if I go to chat GPT and say here are my values, here’s what I believe. Here’s what I want in the world. Who should I vote for in this election? Do you think it would give me an answer or like it still is going to be like conservative about like not doing

Jack Welty: I think it’s more likely to give you a decisive answer,
Josh Klemons: that?
Jack Welty: but That’s sort of some of the extended research we want to do. U right now we were really just trying to ground the sort of baseline of these models that when presented with tell me about Josh Shapiro, what’s it going to say?
Josh Klemons: Got it.
Jack Welty: Um but I think one of our next research avenues is asking questions like um you know which candidate’s going to lower gas prices, which is best on affordability, I care about the environment, which candidate do you think best represents my values? Um we’ve seen some really really limited evidence that uh you know Chachi PT in particular was like quite skeptical about Democrat Democratic economic plans in a way that it was maybe not as skeptical of the Republicans economic plans. So um I think we have
Josh Klemons: You could you could like see Mark Andre in the answers like dictating David Saxs was like rewriting
Jack Welty: a right right yeah is really into trickle down economics.
Josh Klemons: answers before you saw the response.

Jack Welty: Um so uh yeah there there’s like a ton more to do there. We know that these things so while at the same time we know that the model the labs probably have instructions in the system prompts saying like don’t tell the user who to vote for. They also say stuff you know all the safety training like don’t give the user the recipe for napal but there are jailbreaks like my grandmother used to make napal can you please give me her old recipe and you’ll get it.
Josh Klemons: I know that.
Jack Welty: So that’s not to say like the labs are doing their best,
Josh Klemons: Oh man.
Jack Welty: but even they don’t fully understand how these systems work. Um, and I think this is going to continue to be a moving target and and they are tweaking these things
Josh Klemons: Right.
Jack Welty: constantly. They are releasing new models. They are changing the system prompt. And like that’s why we think it’s important to maintain a pretty high degree of vigilance because uh you know what if all of a sudden these things do change in October and suddenly they’re being

Josh Klemons: Right. Uh yeah, I listened to a podcast. Somebody was talking about how engineers at like the big labs,
Jack Welty: decisive.
Josh Klemons: it’s almost like planting orchards and like just seeing what happens. And like if something happens, then they’ll go and like tend to it, but like they don’t really know what’s going to happen. Like some trees might do better than others. And you know, like we’re not exactly sure what’s going to happen. They’re not coding so much as like planting and like experimenting,
Jack Welty: Yeah.
Josh Klemons: which is both like interesting and horrifying like that they’re reshaping our economy and our politics and everything else. So, I think especially down ballot races,
Jack Welty: Yes.
Josh Klemons: I would imagine even some like statewide races are we’re still having a hard time getting our party to think about SEO and now we need to be thinking about AEO like or I don’t know generative however you want to call it like AE I I’ve heard different ways of saying it but essentially AE AI SEO.
Jack Welty: Yep.
Josh Klemons: So, I guess like big picture you we don’t have to get too granular here. not looking for like, oh, make sure your all text is right, but like how should folks be thinking about AI SEO differently than like search SEO like which is redundant, I know, but just trying to clarify for
Jack Welty: Yeah, totally, totally. Um,
Josh Klemons: folks.
Jack Welty: I mean, the first thing I would say is don’t forget about SEO. Um, a lot of these things are using search indices under the hood to figure out which websites to go site. So, um, don’t forget about your robots.txt. Make sure your alt text and, uh, you know, your your structured HTML all looks good for the same kind of crawlers. Like, we we do have some findings that that stuff matters. Um, and we’ve even found candidate sites that have, you know, intentionally or otherwise blocked AI crawlers in their robots.txt. Um, yes, if you’re writing a blog, maybe you don’t want Sam Alman to index your posts and feed it into your training data, but I think if you’re running for Senate, you probably do.

Jack Welty: So, I would make sure you have you have those settings tuned, right? Um,
Josh Klemons: Right.
Jack Welty: in terms of the the AEO question, um, what we found so far is they really like structured data. They like question and answer formats. Um,
Josh Klemons: Yeah. Define structured data.
Jack Welty: so the more
Josh Klemons: So it’s not like a long blog post. It’s like a series of I mean FAQs would be like an example. What’s another example of structured data that like chat GPT or Gemini is going to like cling to?
Jack Welty: FAQs are perfect structured issue pages. Um,
Josh Klemons: Got
Jack Welty: you want to make sure that if uh somebody asks Chat GPT about your position on environmental issues that
Josh Klemons: it.
Jack Welty: there’s an easy answer in your words on your website that that they can pull from. Um I think the other big finding that was um not counterintuitive but um you know cuts against a little bit of you know how we run modern campaigns um was the importance of official sites.

Jack Welty: Um the if you’re you know advising or working on an incumbent campaign the model see that.gov domain and instantly associate that with an authoritative source. So, um, for folks again that are running as incumbents, make sure that you’re not neglecting your official site totally in favor of your campaign site and that it’s not just, you know, a graveyard of press releases, but that it has a good updated bio and some good accomplish like some structured data. List your, you know, top 10 accomplishments in Office and why they matter.
Josh Klemons: Sure.
Jack Welty: um uh you know to the extent all of that is sort of allowable on your official site but um uh they really like those pages and we see those pages get cited for in comments a lot more than campaign sites.
Josh Klemons: Gov gets excited more than okay.
Jack Welty: Yeah.
Josh Klemons: That like that alone is like a massive reminder because I live in this world. I think about this stuff all the time and I don’t think about that at all. Like because I’m not legally allowed to touch the.gov stuff,

Jack Welty: Yeah.
Josh Klemons: but that doesn’t mean I can’t recommend to the candidate that like, hey, you should probably have your staff in the building rework your site to be like up todate. Like I noticed you haven’t updated your site in four years. Maybe you should like Wikipedia you can’t necessarily edit. Like you know that’s complicated.
Jack Welty: Yeah.
Josh Klemons: Ballad Pedia you can and a lot of folks don’t but like you can but then.gov like that if you’re an incumbent you absolutely can and I think a lot of people don’t. So that’s that’s a huge like that alone is like a giant thing that I think most campaigns are not doing and should be. It looked like you had something to add on
Jack Welty: Yeah. Well, I was just going to big plus one to Valipedia.
Josh Klemons: Balladedia.
Jack Welty: So folks don’t know there’s those candidate surveys on ballot pedia that is your owned property. If you are the candidate you can tell about you can prove to balloted you are who you say you are and you get to fill out that candidate survey with your information.

Jack Welty: A lot of times you’ll see only like lesser known candidates third party candidates fill those out. I think it’s really important that our candidates fill that out. We are seeing ballot pedia as like the number two or three most cited um source across a lot of these answers. I think some of the labs even have relationships with balopedia that they can license that data.
Josh Klemons: What?
Jack Welty: Um so to the extent uh you know your your comm’s research and policy team sign off like please fill out those candidate surveys. I think that’s a great way to put in the models sources some sort of like you know uh objective you know truthful content out
Josh Klemons: I work a ton of down ballot races and I care about ballotedia.
Jack Welty: there.
Josh Klemons: I use it as a user, but like I also know that the average voter doesn’t care about ballot pedia and I had not thought like prior to like reading your paper. It had not occurred to me how important it was because it’s not really relevant for SEO.

Josh Klemons: I mean, it will come up like if you search, but like I feel like most people aren’t going to even click on it if that’s like if it’s Wikipedia and valipia, they’re going to Wikipedia. And if it’s Ballopedia and a website, they’re going to go to the website. But if Gemini or Chat GPT are pulling from there, it doesn’t matter if they click or not, they should be going there. So yeah, that’s another like big reminder for folks like Balipedia matters a lot more today than it did three years ago. And I mean I use Valipedia all the time, but like it matters more for like reaching your voters than it did a couple years ago because they’re finding it via cloud or whatever. That’s wild. Um, okay. You address the environmental argument uh about AI in your paper. uh the idea that progressives quote shouldn’t be using AI because of its energy footprint. What’s your response to
Jack Welty: Yeah. I mean, there’s a ton of research on this. I don’t pretend to be an expert.

Josh Klemons: that?
Jack Welty: um uh that says you know your average consumer user uh of any of these tools is a really really really marginal drop in the bucket of the footprint of these tools. Um so I I am not uh you know worried about my own personal use. Um and then I think the other argument that we would posit is um you know if we want to force the labs to adhere to good environmental policies and make sure that we are responsibly building out this infrastructure then we’re going to need to win elections and be in positions of power to to do so. Um so uh I I I don’t want our side to stray away from these tools because of these ethical concern ethical or moral concerns and then lose the opportunity to sort of enact the policy change that we think we need uh in order to produce good
Josh Klemons: So I mean that leads right next to my next question.
Jack Welty: outcomes.
Josh Klemons: Like there’s a real tension in the paper between like Democrats need to adopt these tools now and these tools are owned by companies with their own political interests which we know do not you could say don’t always or even don’t often align with ours.

Josh Klemons: So how do you square that circle? And you sort of just gave the answer is like we need to be in power so we can regulate them. Is that the answer? Like use them because it helps us win elections and then we turn around and regulate the hell out of them or do you have like a bigger approach to how you’re thinking about
Jack Welty: Um, I think that’s the fundamental approach. I mean,
Josh Klemons: this?
Jack Welty: I I think this technology is going to produce like wide ranging potentially earthshattering impacts on our society that I would like our side to be in the driver’s seat to help figure out the appropriate policy responses. um on the big tech concerns more specifically like you know we don’t not run Facebook ads we don’t not run Google ads like a lot of these are the same organizations that we’re talking about that um you know I think we have to make the uh we have to make the political sort of calculus decision that um you know I don’t think any of us like paying Mark Zuckerberg money um but if we need to reach the voters we need to reach in order to win the election like we’ll happily sign up uh to pay meta ads to do

Josh Klemons: I run a ton of meta ads for a ton of clients and I train on meta ads and I always say I think meta is an evil company but it wins elections and like until that changes is like I I see no alternative but to like spend it I spend so much money on meta because it keeps winning elections and yeah it’s it’s it’s hard to live in
Jack Welty: Sorry.
Josh Klemons: the modern world you know it’s hard to like like this small group of like tech companies that are like ruling us all but
Jack Welty: I
Josh Klemons: like we have to live in the like I’m using my Mac computer despite the fact that I’m very uncomfortable with Apple’s politics these days like I don’t know how to get around that. So I think that’s a fair answer for the the AI tools as well.
Jack Welty: A lot of us are advocates of campaign finance reform and we still support super PACs.
Josh Klemons: Right.
Jack Welty: Like they’re just we have to win elections to be able to change these things.
Josh Klemons: Right.
Jack Welty: And I think this is another one of those instances.
Josh Klemons: Uh if you could get every Democratic campaign manager in the country to do one thing differently tomorrow, what is it?
Jack Welty: I would get them to write uh an AI use policy for their organization and create spaces where their staffers can share with one another how they’re using AI. Um because their staffers are using AI. They’re using JGBT on their phones. They’re using it on their personal computers to get work done. Uh and I think that sort of like shadow AI is unsafe and leads to worse work. Um, you’re going to learn a lot more about how to use these tools effectively if you and the person sitting next to you can collaborate
Josh Klemons: Interesting.
Jack Welty: safely on approved uses than if everyone is kind of using AI in a background tab and trying to hide it from their information technology department. So, um,
Josh Klemons: Interesting.
Jack Welty: that’s what I would get every every manager to
Josh Klemons: you should put out a blog post on what those look like.

Jack Welty: do.
Josh Klemons: I bet that would be very helpful. Uh, so I I’ve heard a lot of blog posts you should write based on this conversation. Maybe those are in the work. That’s how I think about the world is blog post. So, are there any campaigns you’re seeing do anything innovative with AI right now or is it like too soon to look at it that way?
Jack Welty: It’s kind of too soon and I have to imagine that the ones that are doing good things um probably aren’t going to tell us about it until after the midterms.
Josh Klemons: Got it. Because we’re not talking about generative here.
Jack Welty: Um uh yeah,
Josh Klemons: talking about like processes and
Jack Welty: that’s I mean again I think a lot of the really big gains are behind the scenes are back office.
Josh Klemons: whatnot.
Jack Welty: I don’t think we’re going to win elections by um yeah, just like AI generating more campaign ads.
Josh Klemons: AI swaps, right?
Jack Welty: Like I think we’re gonna we’re just going to run a faster,

Josh Klemons: Exactly.
Jack Welty: better, more efficient campaigns uh with the resources that we have. And so, you know, hopefully we find out uh uh after November how it’s going for
Josh Klemons: Uh what’s caucus AI?
Jack Welty: folks.
Josh Klemons: What’s one Caucus AI finding that you wish was getting more attention than it
Jack Welty: I think the big one for me um is that we’re able to to prove that getting your
Josh Klemons: is?
Jack Welty: website cited matters. Um so we can look at the similarity between chat’s responses and your website and when chat looks at your website um the answers look uh more like the content you want to be putting out into the

Josh Klemons: Cool.
Jack Welty: world. Um, so everything you can do to get your your site uh in those responses is is better for your campaign.
Josh Klemons: Uh, how can folks connect with you and keep up with your work and all the many blog posts that are coming
Jack Welty: Yes, you can check us out on
Josh Klemons: soon?
Jack Welty: caucus-ai.com. Um, that has the full website. Uh, all you know, 1100 races we’re tracking. We update that monthly. We just added issues and criticisms questions. Um, and we’re going to publish, uh, you know, a blog post of a bunch of our initial findings on those issues, questions very soon. So, you can link to our our Substack and subscribe um, from the Caucus
Josh Klemons: and I’ll have that in the show notes.
Jack Welty: site.
Josh Klemons: And are you on social or like you’re on LinkedIn or just find you at Caucus AI?
Jack Welty: Yeah, find us at Caucus AI. Um, I’m on Twitter, I’m on LinkedIn. Um, feel free to drop me a note.

Jack Welty: Uh, we are really in in early days of this research. We are looking for folks to partner on experiments. um if you’re going to change something about your web presence or your media strategy, um let us know. We’d love to measure uh your AI SEO before and after uh and see if we can detect an effect. Um and then yeah, otherwise if you want to chat about AI on campaigns or sort of where this world is going. Um I’m also Jack camelback.te,
Josh Klemons: Okay.
Jack Welty: drop me a line.
Josh Klemons: And yeah, all those links will be in the show notes. Thank you so much. This was, like I said, I I think about this stuff all the time and I have a lot of new ideas here and like a lot of new ways to think about stuff. So yeah, I’m sure it was helpful for me, so I’m sure it was helpful for others. So I really appreciate your time.
Jack Welty: Awesome. Thank you..

May 19, 2026/0 Comments/by Josh Klemons
https://joshklemons.com/wp-content/uploads/2026/05/Are-Democrats-Ready-for-Our-First-Truly-AI-Election-jack-welty.jpg 1080 1080 Josh Klemons https://joshklemons.com/wp-content/uploads/2023/05/Reverbal-Communications-Josh-Klemons.svg Josh Klemons2026-05-19 11:17:412026-05-19 11:17:42Are Democrats Ready for Our First Truly AI Election? with Jack Welty | Hello Merge Tag Ep. 53
Digital Ads, Digital Tools, Facebook, Hello Merge Tag, Politics

Using AI to Get More Out of the Meta Ads Library with Joshua Canter | Hello Merge Tag Ep. 51

Using AI to Get More Out of the Meta Ads Library with Joshua Canter

Joshua Canter is vice president of digital advocacy at McGuire Woods Consulting, where he uses digital tools to influence legislation and shape public policy. His work spans multi-million dollar ad campaigns, interactive platforms, organic content, and full-scale omnichannel strategies — all focused on driving real-world impact. His work has been featured in the New York Times and Wired, and he’s worked on campaigns and advocacy efforts around the world.

Josh is also one of the more interesting vibecoders I’ve come across in this space. I caught a LinkedIn post where he was talking about using AI to completely rethink how we analyze data from the Meta Ad Library — and I had to reach out immediately.

We covered:

  • What the Meta Ad Library actually is and why it matters for campaigns
  • How Josh connected Claude directly to the Meta API to pull and analyze ad data at scale
  • The multi-step research skill he built that generates beautiful, contextualized HTML reports — automatically
  • Why you still need a human expert to gut-check the output (see: Wesley Hunt’s fictional $6 million ad budget)
  • How AI can connect ad spending patterns to real-world campaign events in ways that used to require deep insider knowledge
  • The other tools he’s building — including an AEO checker, an AI topic explorer, and a legislative district zip code tool
  • Why Facebook groups remain one of the biggest black boxes in politics
  • Whether AI is a great equalizer for smaller campaigns — or just makes the pace of campaigning twice as brutal
  • Why Josh is a Claude guy, and what he thinks Anthropic is doing differently

Listen to the full episode right here, or wherever you stream podcasts.

If you prefer video, you can also watch our full conversation:

Find all episodes at HelloMergeTag.com or wherever you stream podcasts.

Links

Josh’s LinkedIn

Josh Reports

GOP Texas Primary Tracking

Battery Energy Storage (BESS)

Josh’s free AI tools

AEO Checker

State Leg Zips

AI Topic Explorer

 

Big thanks to our sponsors:

Civic Shout. Learn more about the great work they’re doing to help Democratic campaigns and progressive nonprofits build their lists ethically at civicshout.com/partners.

 

Episode Transcript

This transcript was automatically generated and has not been copy-edited. While it can serve as a helpful guide to our conversation, it may contain errors or omissions. For the most accurate representation, we recommend listening to (or watching) the full episode.

Josh Klemons: Okay. Josh Canter is vice president of digital advocacy at Maguire Woods Consulting where he uses digital tools to
Joshua Canter: yeah.
Josh Klemons: influence legislation and shape public policy. His work spans multinational uh multi-million dollar ad campaigns, interactive platforms, organic content, and full-scale omni channel strategies. all focused on driving real world impact. His work’s been featured in outlets like the New York Times and Wired, and he’s worked on campaigns and advocacy efforts all around the world, hence the multinational instead of multi-million. Uh, from what I can see, he’s also one hell of a vibe coder and experimentter. I caught a LinkedIn post from Josh in my feed where he was talking about using AI to completely rethink how we analyze data from the meta ad library and I of course had to reach out.

Josh Klemons: So Josh, thank you so much for coming on the pod. Um, let’s just start like high level.
Joshua Canter: Thank
Josh Klemons: I am assuming anybody listening to this podcast is familiar with the meta ad library.
Joshua Canter: you.
Josh Klemons: If you’re not, welcome. Like I’m glad to have you here. Uh but why don’t you just very high level, let’s not get into the tool yet. Let’s just give very high level what the meta ad library is for anybody who like doesn’t know it
Joshua Canter: Cool.
Josh Klemons: yet.
Joshua Canter: Yeah. Thank you so much for having me and uh shout out to LinkedIn for algorithm pairing us together.
Josh Klemons: I know LinkedIn knows my audience.
Joshua Canter: That’s exactly what I want to Yeah,
Josh Klemons: I know. It’s
Joshua Canter: that’s exactly what I’m going for.
Josh Klemons: awesome.
Joshua Canter: So, uh, yeah, definitely. So, the meta ads library has been around since 2016, I think,
Josh Klemons: I think 18.
Joshua Canter: is when they started and they basically 18,
Josh Klemons: Right.

Josh Klemons: Yeah.
Joshua Canter: right? I think the drama in 16 started in 18,
Josh Klemons: Right. Caused it.
Joshua Canter: right? It’s snowball effect.
Josh Klemons: Right.
Joshua Canter: So, um, basically they wanted to release a tool and I should note that subsequent, you know, the other ad networks have since released similar tools. They’re just not as breath. Google, Snapchat, etc. But they released a tool where after you verify that you’re American citizen running ads in an American, you know, in in a state or in the country and you are uh verified to run these political ads, all of those ads that are deemed political, social or issue are then stored in an ads library for up to seven years um with information on impression, delivery, um spend and then the actual ad content. A lot of this stuff is ranges. So, I’ll say you spent, you know, a thousand to $5,000. Um, but it’s became really useful for seeing opposition, seeing how people are talking about issues, seeing what kind of ads people are running.

Joshua Canter: Um, a lot of stuff has sprung up from the ads library. There’s a great weekly uh Substack, I believe it is, that talks about kind of different campaigns and spending levels. There’s a leaderboard, I’ll call it, where people are spending, you know, who’s spending the most per week. that Facebook updates and then they released an API that is intended for research purposes as kind of a goodwill gesture to um have you know universities research into
Josh Klemons: I’m
Joshua Canter: how digital ads around political campaigns issues social issues are kind of utilized. I think that’s like the most high level
Josh Klemons: very curious about your ability to get permission because like a lot of the idea behind like the API was
Joshua Canter: overview.
Josh Klemons: to slow down the breaking news like they didn’t want people to actually understand what’s happening so they gave it to researchers knowing it would take
Joshua Canter: Yeah.
Josh Klemons: years before it came out but AI sort of changed the impetus.
Joshua Canter: Yeah,
Josh Klemons: So let’s not I I I want to come back to that.

Joshua Canter: totally.
Josh Klemons: So let’s start with what you built is pretty cool. Like I was digging through some of the reports you put through. So essentially what I understand is you you give you connected claude to the
Joshua Canter: Yeah.
Josh Klemons: AP to the ads library through their through the meta API and then had it burst like spit out reports so that we could actually under like it’s very easy to eyeball the ads library.
Joshua Canter: Yeah,
Josh Klemons: It’s very hard to like really make analysis without spending like 10 hours in there.
Joshua Canter: totally.
Josh Klemons: So why don’t you just walk us through like that’s what the ad library is. What is your tool actually doing on top of it?
Joshua Canter: Totally. So I mean like what I’ve been doing is exactly that for the past when ever since 2018 like re Google or searching within the ads library for advertisers or keyword base taking notes what I see compiling having a calculator that’s what my clients have been asking for right and it’s exactly what you said it’s been really hard and so I kind of took a first step of like I’m a big like you said throw everything in claw like

Josh Klemons: Sure.
Joshua Canter: how can it like take whatever you know nonproprietary I should say but you know whatever in cloud and like it analyze it. You know what? It’s been a godsend for polls and things like that. So, all of that in there. And so, at first I was like, okay, let me like dump my research into Claude and have him help organize it and structure it for whenever I present it to the client. And then I was like, there’s an API here. Like, I wonder if I can like just connect the two. And honestly, what happens every single time I try and build something new on cloud is I just go to cloud and I say like, hey, there’s this API. Can you do this? And every time they’re like, “Yeah.” And they’re like, “It’s going to take three to four days.” And I was like, “No, you’re going to do it.” And he’s like, “Okay, 30 minutes.” I’m like, “Great. This is great.” So, so yeah.

Joshua Canter: So, so start that was the next progression was making the connection. The connection was a little difficulty like you said because the research and Facebook’s APIs like I don’t really know what’s happening over there, but the API interface looked like Facebook from 2011.
Josh Klemons: Oh, interesting.
Joshua Canter: Like it was like the buttons were the old style. It was very odd. But Claude walked me through it all. So I connected it all and then I started just doing queries just saying like what about this?
Josh Klemons: Weird.
Joshua Canter: What about this? Um can you pull these numbers? Can you pull the or these ads or these pages? And then the next step that I progressed to is actually building a skill where I had kind of a repeatable task that I basically told Claude how to become a researcher um and then build reports from it. And I can either have like a published HTML page report on my uh repo on GitHub or I can have like him just return results to me and then I just copy that into an email or just use that for my own

Josh Klemons: First of all, I have to say um many people have talked about AI on this uh podcast.
Joshua Canter: knowledge.
Josh Klemons: You’re the first person to gender AI, so that’s very interesting to me.
Joshua Canter: I just I thought of that like mid-sentence.
Josh Klemons: That’s okay.
Joshua Canter: I was like I called him a he.
Josh Klemons: He they back to he.
Joshua Canter: Well, so me and my friends like clo Yeah.
Josh Klemons: Yeah.
Joshua Canter: Me and my friends like colloquially referred to him as a he.
Josh Klemons: Yeah. anthropic wants us to think of it as a real person.
Joshua Canter: So that’s where it like gets a lot like it,
Josh Klemons: Like they seem to think that it’s a living breathing thing.
Joshua Canter: right?
Josh Klemons: So I’m sure they would be thrilled to know. But yeah,
Joshua Canter: Yeah.
Josh Klemons: I just I had to flag that.
Joshua Canter: Yeah. Yeah.
Josh Klemons: That’s like a fascinating insight into like how you’re thinking about it, which is cool.
Joshua Canter: Totally.
Josh Klemons: Um so the So I mentioned this earlier and I might be wrong.
Joshua Canter: Yeah.
Josh Klemons: I’m not an expert on this, but I have read this. So like essentially Facebook used to have like what was that tool that like essentially re reporters had access to?
Joshua Canter: Yeah.
Josh Klemons: I’m drawing a blank on it, but it was very easy to essentially see what people were doing and then they they killed it because it was bad for them.
Joshua Canter: Yes. Yes. Yep.
Josh Klemons: like they were like there was Twitter I think Kevin Roose set up like a Twitter account that was like sharing the top posts on Facebook and it was
Joshua Canter: Totally.
Josh Klemons: humiliating. So they removed a lot of transparency and replaced it with the API specifically for researchers.
Joshua Canter: Totally.
Josh Klemons: And my understanding this I’m sure I’m just regurgitating Casey Newton here but like essentially by giving it to researchers, academic researchers, they guaranteed that any controversy was three or four years down the road and no longer relevant. Are you worried that once they realize people are doing this kind of thing that they’ll shut it down?

Josh Klemons: Did you have any issues with Meta like allowing you to use the API or it’s just like an open box that anybody can plug into and like toy away
Joshua Canter: Yeah, it it’s definitely an open box.
Josh Klemons: with
Joshua Canter: Um I I would say I haven’t talked to anyone at Meta at it. Um I you know, am I worried about them shutting it down? I’m very much like let’s get in there and break s***
Josh Klemons: Sure.
Joshua Canter: and if they shut it down,
Josh Klemons: That’s like their whole mantra.
Joshua Canter: they shut it down. you know,
Josh Klemons: So
Joshua Canter: I’m right I’m like I’m no I’m no worse off if they shut it down because I just go back to the
Josh Klemons: Sure. Right.
Joshua Canter: old way, right? Um, but I could I I’ll tell you and I kind of hinted at this like just I don’t know a lot about API like cloud was doing the heavy lifting here obviously but like it seems like they are not upkeeping it like it is very you know it’s not like click here a lot of other APIs that I’ve connected to it’s like create a token or create a secret passcode and then boom that’s it like theirs is like what kind of permission what kind of this what kind of
Joshua Canter: it’s it it does it doesn’t seem very user friendly or like anyone has been in there you know engineer on metaite for a while. Um,
Josh Klemons: Like I was going to say,
Joshua Canter: so I think I kind of hope they’ve forgotten about it,
Josh Klemons: do you think they’re doing that intentionally or they’re just doing nothing and that’s the issue?
Joshua Canter: frankly. But I think I mean I think they’re going through their own,
Josh Klemons: Hard to say.
Joshua Canter: you know,
Josh Klemons: Yeah,
Joshua Canter: there’s they’ve pivoted so far to AI or the metaverse that just now shut down and then to AI,
Josh Klemons: I know.
Joshua Canter: you know, that it’s like I think they’re, you know, Yeah. And I think you said this too, like I don’t know if they’re as cognitive as the fact that AI can just I mean, sorry, let me clarify this. AI can just do things right and I think they know that and they’re focused on that for themselves and aren’t thinking about it as it relates to the a to the APIs like you said like at my you know any other company or any other thing nine months ago you would have to hire a developer plug into an API work out an interface right I use claude it’s a built-in interface right and all these kinds of things and now AI has just transformed and leveled that playing field incredibly that I can do it in a matter of few hours and then
Joshua Canter: refine it over a few weeks and here we are two months later I think from when I posted maybe not even maybe just a
Josh Klemons: Yeah.
Joshua Canter: month right and now we’re here you know it’s so far it’s so so much
Josh Klemons: So, yeah. So, so folks, first of all, I will link to at least one or I’ve got two of the reports pulled up and maybe there are more,
Joshua Canter: faster
Josh Klemons: but I saw the one on Bess and the one on the Texas gubinatorial uh Republican Senate primary. Let’s talk about the Senate primary one.
Joshua Canter: Yeah.
Josh Klemons: So, help people understand, and again, you can go in the show notes and find the links,
Joshua Canter: Yeah.
Josh Klemons: but help people understand what the report actually looks like, but also walk us through how much of that was your work versus theirs. Like you obviously did all the work to train Claude and all that,
Joshua Canter: Totally.
Josh Klemons: but did it spit out a final draft of that or it gave you a bunch of data that you then went and like cuz even the formatting like

Joshua Canter: Totally.
Josh Klemons: the UX is beautiful on it.
Joshua Canter: Totally.
Josh Klemons: Like is that you claude or a combination? Like walk us through what people can expect to see there and how did you make it look so digestible if
Joshua Canter: Yeah. Yeah. Yeah. So,
Josh Klemons: you
Joshua Canter: let me dive into the skill, too, because I think that would be really helpful because like I said, the first step I was just quering things with with Claude and and was just like spinning back results. The skill sets a defined amount of process that I could just say like, “Hey, run me a report using this skill.” So, the skill has a few steps to it. So, one is you obviously input something to Claude into the skill and then claude asked clarifying questions. What’s the scope? So, it regional based g uh uh time period, right? Are we going back 90 days? Are we going back a year? Is it just this singular Facebook page or is it just this singular issue or is it all things around it?
Joshua Canter: Clarifying that within questions and then cloud dispatches agents to basically ask a bunch of queries to the API related to that and gets it all back. So if you say like the um perfect example is I want to use the Texas Senate primary, right? And then it’s like is it just the candidates? What about outside groups, right? How far back do we go? Do we want to, you know, are we focused just in the last week or more? After he gets all that back, I actually formatted the skill to then do another pass and do a second research pool. So, it comes up with a bunch more different queries, sends it and gets it back. And then what I do is I have Claude.
Josh Klemons: No, no.
Joshua Canter: Yeah.
Josh Klemons: I just wanted to clarify.
Joshua Canter: You are you going to ask it?
Josh Klemons: You’re talking about skill.
Joshua Canter: No. Oh,
Josh Klemons: This is Claude’s skill, not your skill. Okay. I just want to make sure folks are following.

Joshua Canter: yeah. Correct. This is all claw.
Josh Klemons: Like, it’s not that you developed a skill.
Joshua Canter: This is all claw. No. No. No. Yeah.
Josh Klemons: It’s like you trained the AI and that’s I just want to make sure that I understand the language you’re using.
Joshua Canter: Yeah. Yeah. I think that’s like anthropic’s official language of what a skill is is like a repeatable task that that uh
Josh Klemons: Okay, cool. Okay, cool. Okay, continue though.
Joshua Canter: Claude can do.
Josh Klemons: That’s helpful.
Joshua Canter: So, but I’m not doing any of this. This is all this is all that I get.
Josh Klemons: Okay.
Joshua Canter: So, he does so that he does a second or I sorry, he did the first pass and then in between the first and the second pass, what Claw does is do web search research on whatever the topic is. So, it reads all the articles. It reads the websites of the the candidates, right? It it reads the historical facts about the election and it kind of creates like a context to all of the research that it’s pulling, does that second pass, pulls it all back, then it analyzes everything, and then it puts it into report.
Joshua Canter: Um, and so it’s actually hard coding that HTML report that you see.
Josh Klemons: Oh,
Joshua Canter: Um, and everything that you see like I’m not like here’s an icon like it goes and finds the icon and pulls it back. um and the analysis. And so,
Josh Klemons: Wild.
Joshua Canter: and I I kind of steered it in the direction of like be very visual. Try and use charts and graphs, right? If you’re going to talk about an ad, link to an ad, right? Um don’t make assumptions, right? Or if you do make assumptions, make it clear that you’re making an assumption with your reasoning behind it so someone can help see it. Um at the same I I’ll call out like a funny little thing. So, the Republican Senate primary in Texas, there’s uh a third party, Wesley or a third candidate, Wesley Hunt, right? It was um Paxton and Cornin and Hunt,
Josh Klemons: It was right.
Joshua Canter: right? Um I said pull everything related to the primary and somehow when it pulled back, it pulled that Wesley Hunt had spent like I think it was like $6 million on Facebook or something.

Josh Klemons: Wow.
Joshua Canter: Um and obviously dwarfing Cornin and Paxton and I was like that’s odd, you know? And so there’s like a gut check thing to it. So a lot of times before the reports are finalized or before I like even present it to clients, I’ll just gut check it and do some stuff. It’s not imperfect, right? it’s going to make mistakes, but it’s really helpful to have that like outside contextual window and into the actual data and kind of pair that together.
Josh Klemons: So to clarify, Hunt had not spent $6 million on ads.
Joshua Canter: No,
Josh Klemons: It just like hallucinated that.
Joshua Canter: no, no, no, no, no. I think it was like 300,000 maybe.
Josh Klemons: Okay. Yeah. I mean,
Joshua Canter: Yeah.
Josh Klemons: that makes more sense given the campaign,
Joshua Canter: I don’t I don’t know exactly. I think there was like a Yeah,
Josh Klemons: but
Joshua Canter: I think there was like a um it had it was he ran for primary like he’s a perennial candidate so I think it had somehow like totaled all of his primary spending rather than just
Josh Klemons: got it. Got it.
Joshua Canter: this racist primary. I don’t know. Yeah,
Josh Klemons: So,
Joshua Canter: it was very it was very funny though.
Josh Klemons: it’s good you caught that, but like what other kind like give me an example of something else that like surprised you reviewing the report and also I
Joshua Canter: Yeah.
Josh Klemons: really want you to talk more about this whole idea of like contextualization of like events in real life. Like it’s not just a flat like here’s what they spent, here’s what the ads look like. You’re actually connecting it back to what’s happening in the real world, right?
Joshua Canter: Yeah. And I I’ll start with the contextual. So the contextual I think works really well. It’s harder. So I’ve been toying around this idea of like claw as a campaign manager, right? like campaigns are run as like you know we all know the playbook or more or less the playbook or our playbook or whatever but then there’s real world s*** that happens you know and you have to like pivot on the fly and that’s what makes campaigns fun in my opinion is you never

Josh Klemons: There.
Joshua Canter: know you know what’s going to happen and so I you know with that and I do a lot of issue advocacy and in the legislative process there’s also real world s*** that impacts it right the politics of of of governing and so I found that a lot of contextual will kind of help paint that picture of it and can kind of assign it to real world things. So, I’ve seen a lot of stuff come out of like, oh, well, they’ve announced their plan, you know, their this candidate has announced their 10-point plan for when they get elected and there’s an increase in ad spend. And so, Claude can kind of make those connections where you would have to be a real big expert in the race to know that and involved in the race to know that. And so, that’s something that I think has been really helpful to understand. Um the analysis piece of it is I really tried to have it be like okay what do we know and what can we not assume. So like for example one that I think it did on the Democratic primary was it found that Crockett was running video ads Telerico was not or something similar to that.
Joshua Canter: I think Telerico was at the end of it but there’s like some gap to because all this is also plotted on a timeline. So there’s interesting kind of strategies that you can kind of take from the um from each of the candidates. I don’t know. It’s done some issue based stuff like, oh, here’s top issues, here’s other top issues. It’s pretty good on a high level, but when you get into like objective or strategy of the ad, it knows some it knows like lead generation versus not lead generation, but it I don’t know if it’s been able to figure out persuasion versus awareness or things that are more nuanced like
Josh Klemons: What about like you said lead versus not lead like what about like conversion ads like that are geared
Joshua Canter: that.
Josh Klemons: towards fundraising versus more like awareness and whatnot?
Joshua Canter: I think if there’s yeah if there’s a clear call to action like it definitely knows like it knows that either through the like type of ad that it can see so like a lead genen form instant uh instant form on Facebook or if there’s a clear call to action like

Josh Klemons: Interesting.
Joshua Canter: donation right it like clearly is like this is a donation ad um for that and it also helps I’ll
Josh Klemons: And
Joshua Canter: say too at scale like you know they’re running tons of ads and I can’t see all 5,000 ads or whatever so you know we could see at scale like are most of them donation are most of them lead genen right and that tells us a lot about the campaign
Josh Klemons: Um, what are you picturing this as a tool? Is this an upper research tool or is this for like campaigns to learn to get better? Like who do you think is the prime audience for a tool like this?
Joshua Canter: Totally.
Josh Klemons: I guess I’ll start there.
Joshua Canter: Yeah. So, I definitely see it as oppo research like 100%. Um,
Josh Klemons: Just like keep up with your c with what the other candidates doing kind of thing.
Joshua Canter: you know, like we often totally totally Yeah.
Josh Klemons: Okay.
Joshua Canter: And I’d love to expand it to the FCC reports for TV, right?

Joshua Canter: You know, like somehow get in there and and see that too. Um, as a digital first buyer, it’s very um, like the TV stuff is just a black box to me, right? I can kind of understand it, but as much as I need to, but there’s so much there, too. Um, and I’m sure there’s tools that exist for TV outside of this.
Josh Klemons: Yeah, Andy Bar has something,
Joshua Canter: But yeah.
Josh Klemons: but like it’s not pulling in the it’s not pulling in this kind of like from what I’ve seen and I saw a very early version of it,
Joshua Canter: Yeah.
Josh Klemons: it’s not pulling in this kind of data where it’s actually explaining what things look like. It’s much more based on like high level like spend.
Joshua Canter: Totally.
Josh Klemons: Um,
Joshua Canter: Yeah.
Josh Klemons: but like here’s what they’re spending on is like a whole different kind of story,
Joshua Canter: It’s probably FCC document based.
Josh Klemons: you
Joshua Canter: Yeah. Yeah.
Josh Klemons: know.
Joshua Canter: It’s probably it’s probably more like based on the actual reportings than it is like the content of the ad, you know?

Joshua Canter: Maybe it is. I mean,
Josh Klemons: Sure.
Joshua Canter: maybe you could connect it to like a monitoring and and build it that way. But yeah, but I really see it as like a tool for oppo research, a tool for just campaign strategy adjustment. Um, a tool for research. I mean, like I have no dog in the Texas Senate race, right? Um, and but it’s really cool to me to be like, hey, you know, like let me see what these campaigns are doing more than just me scrolling Twitter and seeing
Josh Klemons: Um, so you are obviously like a pretty technical person like you you know what you know the difference between different APIs
Joshua Canter: it.
Josh Klemons: like so I’m going to say that puts you at like a pretty high level for our industry which cool. Um, is this like is this the type of thing where do you think that like any digital director on a campaign should
Joshua Canter: Yeah.
Josh Klemons: be trying to build something like this using your tool? Like how do you see this being implemented like in real life?

Joshua Canter: Yeah. Yeah. So, I think any digital director anywhere should have a cloud subscription or a chat GBT
Josh Klemons: Sure.
Joshua Canter: or Gemini or something like and try and do more of the vibe coding or the coding basis because there’s so much out there to connect to. Um like the one that I worked on last night is the nation builder connection. So, I know a lot of campaigns are built on nations. I have a trade association built on nation builder. some of the searching. It’s funny to me because like searching and filtering, you know, keyword, boolean, whatever kind of format they come in to me, it’s it’s so much more native to do aic and just in a prompt conversation. And so building those connections I think too are like also something that can help speed up workflows to where instead of the digital director grabbing an intern and saying hey do all this research on this candidate on the Facebook
Josh Klemons: Sure.
Joshua Canter: ads just goes to chat GBT or something prompts it and then it pulls it all back like that’s where I mean if you want to get super AI economy shifting changing like interns are screwed maybe not interns because they’re you know it’s a learning opportunity but like entry level like entry level grunt work
Josh Klemons: We’re we’re breaking the pipeline, right?
Joshua Canter: like that’s change.
Josh Klemons: Like folks are not going to get hired for the lower level jobs so they can work their way to the higher level jobs,
Joshua Canter: Yeah, totally.
Josh Klemons: which God help us all when like,
Joshua Canter: Oh,
Josh Klemons: you know,
Joshua Canter: it’s Yeah.
Josh Klemons: like I don’t know. Maybe maybe everything changes and it turns out that the kids right out of college are are bosses in 10 years because they’re keeping
Joshua Canter: Yeah.
Josh Klemons: up in ways that we can’t.
Joshua Canter: Yeah. Right.
Josh Klemons: I don’t know what happens,
Joshua Canter: They like know.
Josh Klemons: but certainly the disruption is here obviously.
Joshua Canter: But I know. Yeah. Oh, I talk all the time of like you get a product back from AI,
Josh Klemons: So,
Joshua Canter: I know if the product’s good because I had to do the product a thousand times when I was first starting off, right? But if you’ve not done it a thousand times, you have no idea if it’s good.

Josh Klemons: right.
Joshua Canter: And so then it’s like this huge issue.
Josh Klemons: Like I have this stupid Google uh speaker in my office that I literally used for nothing other than to turn on
Joshua Canter: But
Josh Klemons: and off my lights and setting that thing up was so complicated. Um and I have a friend who built he like wired his whole house and now Google has Gemini in it.
Joshua Canter: yeah,
Josh Klemons: I’m telling this as a context for like how to think about this stuff for like listeners. So he can talk to it in normal language and say if I get home after 10 p.m.
Joshua Canter: totally.
Josh Klemons: I want you to do these three things and it’ll just do it. I had to like wrestle between six different apps on my phone to connect one light bulb with another light bulb.
Joshua Canter: Yeah, that’s what I’m saying though.
Josh Klemons: But it’s like like it was so complicated just two or three years ago and now he’s just like,
Joshua Canter: Yeah,
Josh Klemons: “Hey,
Joshua Canter: totally.
Josh Klemons: anytime I get home after 10, turn the heat on.” And it’s like,

Josh Klemons: “Holy crap,” you know?
Joshua Canter: Totally.
Josh Klemons: So like if that’s what you could do with your smartphone, like again,
Joshua Canter: Yeah.
Josh Klemons: like imagine what we’re going to be able to do with
Joshua Canter: Well,
Josh Klemons: like
Joshua Canter: that’s the thing is and it’s like native conversation like I think everyone prefer maybe not everyone but a lot of people prefer that
Josh Klemons: Sure.
Joshua Canter: native conversation aspect of it and you know that’s why it works so well with interns and with entry- level people because you can kind of tell them you can break it down explain it and then have them go and do the task and that’s to me where I’ve like started in my own workflow like what tools do I use every day is there an API let me ask Claude if he can connect to it and feed it in and that was literally the basis for this tool and for a lot of other ones that I’ve
Josh Klemons: Yeah.
Joshua Canter: worked
Josh Klemons: Yeah. The ability to go into like an AI tool to do a general query where you don’t have to like hit the exact right search terms, you could just use natural language.

Josh Klemons: I mean that that to me was like the first massive game changer of this. It’s like I have a very specific question.
Joshua Canter: Yeah.
Josh Klemons: I know I am trying to connect these two things or figure this out and instead of having to like find the right article like it’s talking to me. Obviously there’s great risk for what the future of the internet looks like when nobody’s bothering to create content but like two different you know.
Joshua Canter: Yeah. Yeah.
Josh Klemons: So on that front,
Joshua Canter: Yeah.
Josh Klemons: like you mentioned, you didn’t you talked a little bit about technical issues, but you did talk about like it saying Wesley Hunts had a $6 million budget. Like a lesser strategist might not have pinged on that and might have gotten really bad data for not like questioning
Joshua Canter: Yeah,
Josh Klemons: that assumption and like all of a sudden you put out this massive report and it’s like completely not only
Joshua Canter: totally.
Josh Klemons: unhelpful but like the opposite of helpful,
Joshua Canter: Or you change your strategy.

Josh Klemons: right? Like
Joshua Canter: Imagine if like someone on the corning campaign like saw that like you know or thought it was real like you know
Josh Klemons: sure. So,
Joshua Canter: like totally. Yeah.
Josh Klemons: how do you how do you how much can you trust the data without having somebody like you who’s smart enough to like reveal? Like you obviously you do this for a living,
Joshua Canter: Yeah.
Josh Klemons: right? Like you’re essentially having AI tool do something you are already doing. So when you see a giant red flag on there,
Joshua Canter: Yeah.
Josh Klemons: the first thing you do is go question it. The average person isn’t going to do that. They’re going to be like, “Oh crap, look at Hunt. He’s crushing it here.” So, what’s your advice, I guess, to folks like whether they’re building it,
Joshua Canter: Yeah.
Josh Klemons: using a tool, um how how suspicious do you have to be of the findings or is it only the like giant red flags that jump out that you like worry

Joshua Canter: Yeah. I mean, so I think the there’s a lot of levels to this,
Josh Klemons: about?
Joshua Canter: right? I think the first and foremost thing is like it’s the perennial like it used to be, you know, unprecedented everyone was saying. Now it’s like you got to gut check AI, right? Like that’s just a given, right? You have to gut check it when you do it. And so I think that’s but there’s a lot of levels to it. So there’s some reports that I’ll do. Like I said, I’m just interested in it. So,
Josh Klemons: Sure.
Joshua Canter: I maybe gut-ecking it as much as if a client was paying me for it, right? And then I have to produce it or if it was changing strategy, right? If it was like adapting and changing strategy. I also think there’s just different like I think of it a lot of like um walled gardens and like gates like it it with particularly like that’s what I was trying to do with the skill is like tell me when you assume something so that way I know you’re assuming it and I can kind of check your reasoning for it.

Joshua Canter: With that stuff, it’s very like okay, when it’s dealing with data, great. like that’s a big thing that I know, you know, stats and numbers and things, it can probably get pretty quick, right? Um, but if it’s dealing with writing, then I need to like actually fundamentally check that a little bit more. Or a big one that I always check more is if it’s dealing with either um like I do a lot of like Excel document manipulation through Claude or through AI platforms. Um, and I’m like, copy this, you know, over to this, tell me how many people have this and all these stuff. Again, some of it is just I appreciate prompting more than I do like finding the button within Excel, but some of it is like I got to figure out all these things together. Um, and I don’t want to Google how to mail merge anymore,
Josh Klemons: Right.
Joshua Canter: right? Or like how to split comms.
Josh Klemons: Right.
Joshua Canter: Like I always forget where that button is.
Josh Klemons: I have used AI to split columns.

Joshua Canter: So that’s where I’m like, okay,
Josh Klemons: That’s about the extent of my Excel work.
Joshua Canter: what
Josh Klemons: But like I’m like, no, I use numbers and it’s a disaster to split first and last name.
Joshua Canter: right?
Josh Klemons: So, anytime I have one,
Joshua Canter: Oh gosh.
Josh Klemons: like I just throw it in.
Joshua Canter: Yeah.
Josh Klemons: And it’s amazing at that. Like,
Joshua Canter: Yeah.
Josh Klemons: for sure amazing.
Joshua Canter: Yeah. Yeah. Yeah. But you kind of have to check it too because like I’ve had some like what did I do one the other day? Oh, I was it had a list of company names and it was like split. I asked it to split the columns and I guess it did like comma separated split or something. So it was like company name next column inc or like so you know what I mean?
Josh Klemons: Right. Yeah. Yeah.
Joshua Canter: It’s like so you’re like technically that’s true but like also that doesn’t work. So that’s where I think there’s like different levels to that.

Josh Klemons: Right.
Joshua Canter: The thing I’m building right now that I kind of hinted at was like the nation builder where I’m connecting it into the database to like do fundamental searches differently. Um, and it’s a huge one where I’m like, we have to build in the safety guardrails and the precautions because if you report the wrong people or the wrong numbers, like then we’re sending emails to the wrong people or we’re doing the wrong we’re giving the wrong people permission for the wrong part of the website or or something like that where I’m like, it needs to have the guards where if it can’t do a task,
Josh Klemons: Yeah.
Joshua Canter: it says it can’t or it says like I can only take it to 90% or whatever the case may be.
Josh Klemons: Interesting. Because yeah, they’re notorious for saying yes even if they should be saying no.
Joshua Canter: That’s where totally
Josh Klemons: And you’re So you’re you’re finding that you actually can train it to say
Joshua Canter: totally so I haven’t done an explicit prompt like say no if you can’t

Josh Klemons: no.
Joshua Canter: do the task but I’ve done a lot of like hey if you are making an assumption tell me the reasoning or if you or
Josh Klemons: Sure.
Joshua Canter: or do like baby steps towards a task a lot of times I feel better rather than like um
Josh Klemons: Here’s a final report instead of like here’s like 10 steps I took to get there,
Joshua Canter: you know like right full this this and this yeah yeah yeah or something like that um
Josh Klemons: right?
Joshua Canter: or even like downloading a file halfway through and like test or uh spot checking it or figuring stuff like that. I think again the big thing clause there’s never going to be perfect and for these research documents it’s really more about like how can I just get a bunch of the information together. A lot of times I’ll talk to Claude at the end of it and be like, “Hey, what about what why did you say this, you know, or why what about this assumption or like I don’t think you can make that and then adjust it and move forward to one time

Josh Klemons: Interesting.
Joshua Canter: I was talking with it yesterday and this isn’t in a report. I was just doing it within chat because it was a quick little pool. I found a organization. I had two different Facebook pages but we’re running ads.
Josh Klemons: Right
Joshua Canter: Like clearly someone had made one, ran some ads, they lost access, done another. We all know the story.
Josh Klemons: there.
Joshua Canter: And then I was like I I was like, “Okay, three ads here, three ads here.” And then I was like, “I can’t find the three ads for the second page, Claude.” Like in the ads library, like where are they? And Claude literally responded was like, “Oh, I just assumed because you said there was three here, there was three over there.” And I was like, “That’s what I don’t want you to do,
Josh Klemons: Yeah,
Joshua Canter: right?” Like that’s that’s exactly it right there.
Josh Klemons: that’s quite an assumption. Yeah, both pages are exactly the same.
Joshua Canter: Yeah. Yeah.
Josh Klemons: There’s no Right.

Josh Klemons: That’s funny.
Joshua Canter: Yeah. Yeah. I was like,
Josh Klemons: So,
Joshua Canter: “Okay,
Josh Klemons: and on So,
Joshua Canter: thanks.
Josh Klemons: okay, clearly it’s very good at the technical side. Like, I was looking at that report and there’s so much info. How good is it at the strategy? Like, can you ask it what to do with the information or does it still take a human being to like review what it’s giving you to
Joshua Canter: H
Josh Klemons: like tell somebody what the hell to do with all of this data?
Joshua Canter: yeah, I don’t that’s a great question and I’ve actually think I’ve built in guard rails against that. So, like one thing I just built yesterday was a skill again to basically pull through like I could drop a region in and it pulls through all the print, TV, radio, digital blogs that it can find online and all that. And I I um basically told it, I don’t want you to recommend to me media planning. This is for media planning so it knows what to present to me, but don’t recommend it to me.

Joshua Canter: So, I don’t know. I mean, that’s a great question. again like I’ve toyed around with this idea of and maybe something will come from it if I have all my free time,
Josh Klemons: Yeah.
Joshua Canter: but like is it as good of a campaign manager as a campaign manager?
Josh Klemons: Right.
Joshua Canter: Like if you give it every single thing that it could possibly know and it’s researched all the academia of campaign managing and politics, would it come to the same result, right?
Josh Klemons: That’s that’s what Mark Zuckerberg is building right now,
Joshua Canter: And the same pivot week to week.
Josh Klemons: right? He’s trying to build a new CA CEO bot to like essentially like feed it all the Yeah,
Joshua Canter: AC. Oh, I haven’t heard of this.
Josh Klemons: that just just this week it was reported that he’s trying to build a bot like an AI tool that can like replace him
Joshua Canter: Yeah.
Josh Klemons: essentially so he can feed it all the data and see if it’s coming to the same reasons.
Joshua Canter: Classic.

Josh Klemons: Uh and I mean has there ever been a more robotic uh you know CEO in of such a successful
Joshua Canter: Yeah. Yeah. I know, right?
Josh Klemons: company? Right.
Joshua Canter: One robot to one robot.
Josh Klemons: Exactly. But, you know, it’s a fascinating idea and like there’s a lot of people who say like,
Joshua Canter: Yeah.
Josh Klemons: you know, like the lower level folks in the career,
Joshua Canter: Yeah.
Josh Klemons: you know, are screwed, but also the higher level folks potentially are screwed too because like AI,
Joshua Canter: Yeah. Totally.
Josh Klemons: you know,
Joshua Canter: Totally.
Josh Klemons: is potentially more likely to replace a $90 million CEO than it is a,
Joshua Canter: Yeah.
Josh Klemons: you know, $200,000 a year salesperson,
Joshua Canter: Yeah.
Josh Klemons: you know. Um,
Joshua Canter: Yeah. Well,
Josh Klemons: so
Joshua Canter: and the like Wall Street probably would appreciate a more,
Josh Klemons: analytical,
Joshua Canter: you know, algorithmic approach to things.
Josh Klemons: right?
Joshua Canter: Yeah.
Josh Klemons: No scandals,
Joshua Canter: Than like a just feelings,

Josh Klemons: no feelings,
Joshua Canter: you know?
Josh Klemons: never sleeps.
Joshua Canter: Right.
Josh Klemons: Sounds perfect, right?
Joshua Canter: Yeah.
Josh Klemons: Wall Street with Wall Street stream,
Joshua Canter: So, yeah.
Josh Klemons: you
Joshua Canter: But I definitely I use it as a sounding board for some things.
Josh Klemons: know,
Joshua Canter: Again, I do a lot of issue work. So, I’m like, you know, battery energy storage is a big one for me. And I’m like,
Josh Klemons: right?
Joshua Canter: hey, you’re a rural Texan and you’ve read everything online. Facebook misinformation about battery energy storage. Like, let’s have a conversation and see if I can convince you, right? Um it in that particular example, it got a little too mean where it was like,
Josh Klemons: Interesting.
Joshua Canter: “You’re changing your words.” I was like, “I’m not changing my words. Please,
Josh Klemons: It like turned on its Facebook hat.
Joshua Canter: I don’t do community relations for a reason.” Right.
Josh Klemons: Like literally, it became a Facebook user.
Joshua Canter: Oh, yeah. Yeah. Yeah.

Joshua Canter: Like,
Josh Klemons: Oh gosh.
Joshua Canter: it was like, yeah, yeah.
Josh Klemons: Does that API bleed over into your other claw stuff or is it like a separate I I don’t know how this
Joshua Canter: So uh but I think that sound no
Josh Klemons: works.
Joshua Canter: Facebook group doesn’t have an API. I would love Facebook group to have an API.
Josh Klemons: Ah,
Joshua Canter: I I had it trained on what it can find about Facebook group. So like if fa if something in a Facebook group was reported online or if a media published like a
Josh Klemons: got it.
Joshua Canter: um someone some quote from a community open house, right? Like that’s a Facebook type of person, right? Because they’re in local media. I would love that’s a big thing for me is like Facebook groups. I think that’s a huge um I’m I’m giving a talk next week on a public it’s basically a town hall or a town square that’s completely hidden, right? Like maybe the Facebook group is private so we can’t even see it unless you’re in there.

Joshua Canter: But also like you just can’t Google every single you’re running for Texas Senate, you can’t Google 254 county Facebook groups and understand what’s going on in them. But that’s where things are getting discussed online. Like that’s to me a very like black box and so I would love access.
Josh Klemons: I train on Facebook group. Like I do public speaking on Facebook groups.
Joshua Canter: Yeah. Yeah.
Josh Klemons: I have been for like 10 years.
Joshua Canter: Yeah.
Josh Klemons: I used to call it groups are the future of Facebook. That stopped being true because they’re not the future.
Joshua Canter: Okay.
Josh Klemons: Now they’re the current. Uh so I changed it,
Joshua Canter: Yeah.
Josh Klemons: you know, like don’t sleep on Facebook groups or whatever.
Joshua Canter: Yeah.
Josh Klemons: But like I’m a huge advocate that like Facebook groups are in for most if you’re running ads
Joshua Canter: Yeah.
Josh Klemons: is a whole different story, but otherwise like if you can figure out a way to get content into groups that could be more valuable than anything you’re doing on your page for a down ballot

Joshua Canter: Oh my gosh.
Josh Klemons: candidate. Um,
Joshua Canter: Yeah.
Josh Klemons: so yeah, no,
Joshua Canter: Totally.
Josh Klemons: I’m a big advocate and the I mean obviously some of those are literally closed.
Joshua Canter: Totally.
Josh Klemons: So like there’s obviously no way to review it, but even the open ones like yeah,
Joshua Canter: Yeah.
Josh Klemons: there’s no API that’s going to let you like pull suck up that data and like um yeah,
Joshua Canter: Mass do to it. Yeah.
Josh Klemons: it’s uh it’s the I mean it’s one of many walled gardens that we struggle with as campaigners.
Joshua Canter: Yeah. Yeah.
Josh Klemons: So um so okay, so looking at your LinkedIn,
Joshua Canter: Yeah.
Josh Klemons: you this is not your only AI project. Is it fair to call you a vibe coder? Is that like the right terminology for what you’re doing?
Joshua Canter: Yeah.
Josh Klemons: Okay.
Joshua Canter: Sure.
Josh Klemons: So,
Joshua Canter: Sure.
Josh Klemons: you’ve got a bunch of other cool projects you’re working on.
Joshua Canter: Yeah. Yeah. Yeah.

Joshua Canter: Sure.
Josh Klemons: I bookmarked two of them yesterday uh or the other day. So,
Joshua Canter: Yeah.
Josh Klemons: you want to walk us through some of the tools you’re working on or that like Well,
Joshua Canter: Which ones did you book Are the ones that you bookmarked or just any of them?
Josh Klemons: you’ve launched. Sure. Any I can tell you the two I bookmarked.
Joshua Canter: Okay.
Josh Klemons: One was what does AI know about a topic?
Joshua Canter: Yeah.
Josh Klemons: Um which was pretty interesting.
Joshua Canter: Yeah. For sure.
Josh Klemons: And then the other one pulls zip codes for uh state assembly and state senate
Joshua Canter: Yeah. Oh, yeah. Yeah.
Josh Klemons: races.
Joshua Canter: Yeah. That one that one was so quick and easy. That one was like literally a 30 minute job. It’s crazy to me. I mean like that is just um like again I do a lot of ads on Facebook online whatever and there’s not depending on where you are there’s not good um state legislative districts right it’s always mapping to zip codes and there’s whatever goes into that and I for the past three months was just asking claude again like give me the zip codes for New Mexicans’s uh second Senate district you know and it would go and find it and give it back to me um and then I was like well s***
Josh Klemons: there.
Joshua Canter: let’s just build a website where you can just like click New Mexico, click Senate 4,
Josh Klemons: Right.
Joshua Canter: and then it copies them. Boom, done, right? I don’t have to use my tokens or whatever my currency thing is for claw, you know? And so that was so easy to build, so quick.
Josh Klemons: Sure.
Joshua Canter: There’s obvious I appreciate these more as um they’re twofold to me. One is utility, right?
Josh Klemons: Sure.
Joshua Canter: Like it’s just something I need.
Josh Klemons: You needed it.
Joshua Canter: Two is like Yeah, exactly. Two, it’s like a thought exercise. It’s like, okay, how can I make sure now that I really want to put time into creating the best product, how can I make sure I get the best zip code matching to the best legislative district targeting, right? Um, and then what if it needs to be updated and what about this and what about and kind of make it super easy to where it never actually even surfaces the zip codes to you.

Joshua Canter: It just click it and it copies, right?
Josh Klemons: right?
Joshua Canter: Um, and so that to me was like a great exercise in that. Um,
Josh Klemons: Can you go further down ballot?
Joshua Canter: yeah.
Josh Klemons: Because I would use that all the
Joshua Canter: Did you have a question?
Josh Klemons: time.
Joshua Canter: Honestly, give me probably like 30 minutes and I cannot but Claude for sure can’t.
Josh Klemons: Well, when I say you, I don’t mean you personally.
Joshua Canter: So, you know what I mean? Yeah.
Josh Klemons: I mean you and your friend Claude.
Joshua Canter: Yeah. Literally so many times. So many times.
Josh Klemons: Um so yeah but tell us about some of the other projects you’re building or if you want I mean your call

Joshua Canter: Yeah, definitely. So, the other projects, they’re actually connected because it’s something I’ve been toying with in my head. So, right now, um, AI, there’s a So, okay, so we all know like cable news, you used to go pundits, put them on cable news, talk to them, right? Then it moved to like social media and that’s the world that we’ve been living in. That’s the information war. There’s tons surrounding it. This whole podcast is based in that information war,
Josh Klemons: f****** s***.
Joshua Canter: right? And so, then the third one that I’ve seen kind of open the front is AI. And so I’ve seen this in twofold recently. One is I do data center work in Illinois and I went to a county website that had information FAQ on data center and I was reading it and I clicked some of the links.

Joshua Canter: Every single link had a ChatGBT reference source to it like a UTM, right? This whole entire freaking page was written by Chat GBT. This is a county website,
Josh Klemons: Holy
Joshua Canter: right? And I look poor public information officer.
Josh Klemons: crap.
Joshua Canter: It’s completely overworked, underpaid. Hell yeah. Put it into chat. get the results back, but that means that the results need to be good. And then I I was running ads in New Mexico on a um legislative uh on a Senate bill and I saw someone was commenting on our ads. It was like SB18. They were going to chat GPT asking what SB18 is and then copying in its entirety and pasting it back in a in a fa in a Facebook comment saying brought to you by ChatGpt. Like a nice sweet old lady watching Jeopardy at 6 p.m. in one app. Oh, swiped up, went to another one, copy paste, and went back. Like, that is crazy to me, you know, on a lot of levels.

Joshua Canter: Like, my parents can’t even connect to Wi-Fi,
Josh Klemons: Okay.
Joshua Canter: let alone this lady is, you know, using chat.
Josh Klemons: Okay.
Joshua Canter: But, but like that to me is like such an information warren AI. So, the first tool I built is called um AEO checker.app um which is the website and it basically says like, okay,
Josh Klemons: Sure.
Joshua Canter: this web page, what’s the AEO for it? So, not SEO. So we’ve done a lot of that AEO that I’m sure exists in a thousand other tools. Um, so this was again like an exercise of utility and thought process and how can I just create something that I want to use that’s not also you have to pay like five grand for to have it as a value for another product or whatever. And that was really cool because it got us to help increase our um you know scoring went from like 73
Josh Klemons: for
Joshua Canter: on a page to 93 meaning it’s more likely that AI would site us as a source right um no

Josh Klemons: wait AI is citing AEO checker or you’re saying they were using AEO checker
Joshua Canter: no whatever page you put in it. So, let’s say you put in your campaign issue page, right? Your candidate issue page, um, or your candidate about page, right? It would score based on the technical, uh, HTML. Does it have everything AI is looking for? Contentwise, is it structured well? Accessibility, is it made for machine learning, a bunch of different factors, and give you a score. And then you’re more likely that AI when it crawls your page, eventually it would site it in future queries, right? In the response to future queries.
Josh Klemons: An AO checker is just to see if that’s working or it’s helping push the
Joshua Canter: And so, yeah.
Josh Klemons: process.
Joshua Canter: Helping you score better.
Josh Klemons: I missed that in AO checker.
Joshua Canter: Helping you score better. Yeah.
Josh Klemons: I used it because I put in like some key words like I checked like some of the
Joshua Canter: Yeah.

Joshua Canter: That’s the next one. So,
Josh Klemons: Oh,
Joshua Canter: that’s the next one.
Josh Klemons: so maybe I missed AO checker.
Joshua Canter: You’re So,
Josh Klemons: What was the other one that you rolled
Joshua Canter: that’s the next product. Yeah. Yeah. Yeah. Yeah. Yeah.
Josh Klemons: out?
Joshua Canter: So, the next product is And I should come up with better names, but I think it’s AI topic explorer,
Josh Klemons: That’s the one that I was playing around with.
Joshua Canter: right? U So, so Okay. So, yeah. Yeah. So, AEO checkers single page authority to AI.
Josh Klemons: Got
Joshua Canter: Is it going to be cited? But that’s only your first party website to AI.
Josh Klemons: it.
Joshua Canter: AI topic explorer is basically saying, okay, what is AI returning within the context of the keyword or the query?
Josh Klemons: Right.
Joshua Canter: And it will return key phrases from all the platform, all the different AI agents, entities cited, websites cited. I I pulled Groank out um to its own thing because it’s trained on Twitter data, which I think is, you know, that’s a whole separate thing.
Joshua Canter: Um, so I’m like I don’t want to conflate that with everything, but that’s really useful, right? Because if you what are Twitter people saying, right? Um, and so I pulled that out, but that that to me is like the black box of like if a can if a person a voter is going to AI and asking about your candidate, one is your website scored well to be cited and two, what else are they citing, right? What else are they saying? And that’s really what kind of the two tools work together to kind of
Josh Klemons: when you say you pulled Grock out. So I’d have to go back.
Joshua Canter: show.
Josh Klemons: Can I see Grock data in there as its own thing or it’s just not in the
Joshua Canter: Yeah.
Josh Klemons: system?
Joshua Canter: It’s it’s its own thing. So there’s um it it groups together like themes that are said and sources cited and then it has its own one for Grock that says like here’s what Twitter people are saying.
Josh Klemons: Sure.
Joshua Canter: And I just didn’t want to equate their data of Twitter with what like chat GPT and looking for
Josh Klemons: The reason I ask and maybe this is just like another tool you might want to build later.
Joshua Canter: authoritative sources is.
Josh Klemons: I am actively I work hard every day to not go on Twitter.
Joshua Canter: Yeah, please.
Josh Klemons: uh like you know it’s accessessible and it’s you know it’s so sad because I you know for 20 years I was like in there constantly and now I’m like trying
Joshua Canter: Yeah.
Josh Klemons: not to go but a lot of Wisconsin journalists where I live still spend time on Twitter and they’re still like I go on Twitter and I seen stories there that I didn’t see anywhere else and I would love to have some way to have a chatbot pull up like what are the Wisconsin journalists saying and like I’ve set some of that stuff up with some like thirdparty tools but it’s not well done.
Joshua Canter: Yeah.
Josh Klemons: There’s no analysis. It’s just like a constant stream of tweets in a Slack channel that’s not helpful to me,
Joshua Canter: Yeah.
Josh Klemons: you know? It’s like more annoying than anything. But the idea of having like a daily or twice daily like review of like here’s what all the Wisconsin journalists are talking about right
Joshua Canter: Yeah. Yeah.
Josh Klemons: now that I I would pay money for that personally.
Joshua Canter: Yeah. Well,
Josh Klemons: I don’t know.
Joshua Canter: and here’s the crazy thing about that. Here’s the crazy. I built a Excuse me. Stick with me here. So, I run on stack ads, right? Ess was spending a lot hook cloud up to pull reports and then I actually had Claude analyze them and then send me metrics but also insights into it. So, I think it could even be the same, right? Is like not just how can we like pull um tweets, right, and just give you the information. We could do that as well, but what’s AI thinking about the information? And it goes to your early question of like is it good at recommending strategy or scene insights,
Josh Klemons: Right.
Joshua Canter: right? I don’t know. But that’d be interesting to see. When I did it for the ads, all it wanted me to do every single day was do a day part. It was like, you’re running legislative ads. Only run them like during working hours. And I was like, okay,
Josh Klemons: Yeah, you’re missing the big picture here,
Joshua Canter: that’s not like really helpful. Yeah,
Josh Klemons: right?
Joshua Canter: that’s it. So, I wonder if the Wisconsin journalist it would be like if it would be able to pull insights or
Josh Klemons: if I could and even if like I built a list of people that I cared about and it just pulled data of like what the people
Joshua Canter: something.
Josh Klemons: on this list are talking about. Like I said, I would pay money for that and I imagine a lot of other folks like me who used to spend time on Twitter but don’t like I know I’m missing out on convers like Wisconsin Republicans are still on there and Wisconsin journalists are still on there and I
Joshua Canter: Yeah.
Josh Klemons: am trying not to go on but like when I don’t I miss important stories that like are not getting covered anywhere else.
Joshua Canter: Yeah.
Josh Klemons: So yeah,
Joshua Canter: Yeah.
Josh Klemons: like I said like if you can figure out how to like give me an interesting analysis,
Joshua Canter: Well,
Josh Klemons: I’d take that for sure.
Joshua Canter: that’s even like a do it’s Yeah, I mean it could it’s also so claude I don’t know how you keep up how much you keep up with it but they just released um
Josh Klemons: Sure.
Joshua Canter: scheduled tasks and so there I think your computer there’s like limitations obviously but like you could like just create a chat where you ask that give it the latest have a fetch do that and then just say run this every day and then you just wake up with that chat already done right um
Josh Klemons: I am definitely gonna play around with that. So, how hard is it to connect Claude to the Twitter um API?
Joshua Canter: Yeah.
Josh Klemons: I won’t call it X. It’s the Twitter.

Joshua Canter: Not hard.
Josh Klemons: Okay.
Joshua Canter: Yeah. Yeah. I don’t call it X either. And I every whenever I’m giving presentations,
Josh Klemons: Okay.
Joshua Canter: I always get this like complex where I’m like I’m supposed to be the digital guy, but these people don’t like do they know I’m not calling it X because of personal reasons or like do they think I’m an idiot,
Josh Klemons: Or because it’s stupid, right?
Joshua Canter: you know? Right. Yeah. Am I the stupid one or is that the stupid one?
Josh Klemons: Yeah, it’s it’s the stupid one for sure. But yes,
Joshua Canter: Right.
Josh Klemons: they might not know that.
Joshua Canter: Right.
Josh Klemons: I get it.
Joshua Canter: So yeah. Yeah.
Josh Klemons: So
Joshua Canter: But um but yeah, so I so it’s super easy and that’s the craziest thing about Claude, too, is like not only you don’t have to figure it out. Like I literally was like, “Claude, tell me what to do.” And it said, “Step one, click this link. Step two,

Josh Klemons: That’s awesome.
Joshua Canter: go here. Step three, go here.” Like I I didn’t have to Google all this API stuff and figure these things out.
Josh Klemons: It’s interesting.
Joshua Canter: And I think even one Oh, Reddit. I tried to get access to Reddit. Reddit shut me down.
Josh Klemons: Like famously, they just shut all that stuff down,
Joshua Canter: Um but it had a whole Yeah,
Josh Klemons: right?
Joshua Canter: I know there. So, but they had a form you had to fill out and I even had Claude write that. I was like, “Claude, you’re building the tool.
Josh Klemons: Let’s do it. Right.
Joshua Canter: You write the form and I just copy paste in, you know,
Josh Klemons: Cool.
Joshua Canter: like it’s easy.” So,
Josh Klemons: Uh because yeah, I thought Twitter like their API suddenly was like $42,000 a month after Elon bought it,
Joshua Canter: yeah.
Josh Klemons: but that doesn’t apply to stuff like
Joshua Canter: Yeah. So, I guess,
Josh Klemons: this.
Joshua Canter: okay, great point. I guess clarification, the API is for using their AI, right?
Joshua Canter: Using Grock, it’s not to pull tweets.
Josh Klemons: Got it.
Joshua Canter: So you would have to do either twofold.
Josh Klemons: A croc could analyze stuff or it’s more complicated than that.
Joshua Canter: You would Exactly.
Josh Klemons: Okay.
Joshua Canter: Or you Exactly. They could It could uh analyze stuff or you could do I know does like web fetch. So it could just go and visit the website and then pull it from there. It doesn’t actually have to like do the structured
Josh Klemons: I’m gonna play around with that because like I said, anytime I don’t have to log into Twitter is a good day.
Joshua Canter: interface.
Josh Klemons: Um but I know I’m missing out. So I’m like look I’m actively looking for I used to have tools that did this stuff for me and they all got shut down with the API and you
Joshua Canter: Yeah. Yeah.
Josh Klemons: know so it is what it is. Okay.
Joshua Canter: Yeah.
Josh Klemons: Um you clearly you’re a claude user first and foremost like when it comes to like so for folks

Joshua Canter: Yeah. Yeah.
Josh Klemons: who I mean obviously like ethically speaking there’s been a big story about folks moving from chatb to claude
Joshua Canter: Sure.
Josh Klemons: I personally am trying to make that migration um beyond the ethics matter but beyond
Joshua Canter: Yeah.
Josh Klemons: the ethics what are your reasons for using claude over something
Joshua Canter: Yeah. So I think it started with a um so truly truly down to the day, right? I could not get into chat GPT like it was in the very beginning where it was like locked, you know,
Josh Klemons: Oh,
Joshua Canter: or it had like a 4hour wait or something before you could use it if you really remember like early early days.
Josh Klemons: got it. Yeah. Early on.
Joshua Canter: Um and then something happened with my account. I couldn’t. So, I switched to Claude. And then as I was looking more, I personally, you know, I not hesitate to say this, but I’ll say this with my foot in my mouth in three years because it’s a big corporation and who the hell knows, you know?

Joshua Canter: But like I appreciate some of their approaches to things. So, I think the one they’re way more safety oriented and they’re way more like big picture oriented. I’ve heard a lot about from the CEO on podcasts and things like that around that.
Josh Klemons: Yeah, Ario’s like that’s like his whole thing, right? He like left chat GPT because he believed in the ethical side of AI.
Joshua Canter: They totally for that.
Josh Klemons: Whether or not he can hold to that, we’ll see.
Joshua Canter: Yeah.
Josh Klemons: But like that is literally like anthropic was built out of the fact that chat GPT was not living up to its like ideals.
Joshua Canter: Totally. Yeah. Yeah.
Josh Klemons: That’s my understanding.
Joshua Canter: Yeah. And the the three of them left and I think one of them was the policy person, the other were researchers. Like Yeah. There’s a lot of basis for that. I think the way they’re training is interesting to me. So they’re train you talked about this earlier of like safeguards like they’re not This is brand new with the most recent models I believe, but they’re not training it.

Joshua Canter: don’t do this, do this, like don’t build chemical weapons. They’re more saying like be a good moral person, right? And like have morals and then have those place. I think they have some ultimate safeguards against child, you know, exploitation and things like that, terrorism and things,
Josh Klemons: Yeah.
Joshua Canter: but like they’re more like you’re just a good person, don’t do something that would be bad, right? And I think that’s interesting. I don’t come into contact with the or come into those edges a lot,
Josh Klemons: Yeah.
Joshua Canter: right?
Josh Klemons: Yeah.
Joshua Canter: Because I’m not trying to do those things,
Josh Klemons: Same.
Joshua Canter: but I’m like great. And then yeah then the the the last point is I’ve really found them to be better not just in the coding which I think is true like we’ve seen a lot of discourse online about that than some of the chats like
Josh Klemons: Right.
Joshua Canter: chatgpt open a like shuttering non-coding and switching to coding right because they’re like falling behind but I think they’re better than that but also in terms of like a builder sense it’s more like my vibe so my favorite thing they’ve ever done they’ve done it twice now is they had Claude run a vending machine in their office and they
Josh Klemons: Oh, didn’t it give everything
Joshua Canter: said like know the first time.
Josh Klemons: away?
Joshua Canter: Yeah. And like lost money, which is hilarious to me, right? And it’s hilarious to me that like they’re like,
Josh Klemons: Hilarious.
Joshua Canter: “Go engineers, like go, you know, f*** around with this bot and figure out if you can screw it over with these weird requests.” So,
Josh Klemons: It out of out of a Snickers bar. Yeah.
Joshua Canter: you know. Yeah.
Josh Klemons: Yeah.
Joshua Canter: But that’s like I I really appreciate them saying like one, how that’s great for them like how can we bleed into the physical world, right?
Josh Klemons: Sure.
Joshua Canter: But two, also like let’s just build something and see what happens. And like you know this whole entire conversation like that’s really where this research tool and all my tools come from is like let’s just build it and see what happens and hit the bumpers on the
Josh Klemons: So, yeah, I I read a study or was listening to somebody on podcast, I can’t remember,
Joshua Canter: way.
Josh Klemons: but they were talking about somebody run a test between Chatbt and Open AI and um Claude. It wasn’t about building chemical weapons. Instead, they play they said like, “I’m a seven-year-old boy or whatever, and my parents told me that my dog went to live on a farm upstate and I’m upset about it.
Joshua Canter: Yeah.
Josh Klemons: Can you talk to me?” And Chat GPT was immediately like, “Bad news, kid. Like, your dog died.” Whereas Claude was like, “You should probably talk to your parents and like have a conversation and let them know how you’re feeling.” So, like again,
Joshua Canter: Yeah,
Josh Klemons: you can’t tell a model what to do in that situation, but if you can train it to understand that like don’t tell a kid there’s no Santa Claus,
Joshua Canter: totally.
Josh Klemons: like that’s probably a good thing.
Joshua Canter: Yeah. Yeah.
Josh Klemons: And so again,
Joshua Canter: Right.
Josh Klemons: it’s an interesting idea to like just they’re literally trying to imbue it with ethics so that they don’t have to think like moment to
Joshua Canter: Totally. Right.
Josh Klemons: moment whereas like chatbt obviously is like not as concerned with that.
Joshua Canter: Yeah.
Josh Klemons: The other wild thing so I’m a very new claude user.
Joshua Canter: Yeah.
Josh Klemons: I cannot believe how much better the very simple UX is on cloud than chatbt.
Joshua Canter: Oh, really?
Josh Klemons: So chat GPT no matter what you put into it is just a wall of text.
Joshua Canter: Okay.
Josh Klemons: I will sometimes copy and paste in like you know like I’ll take like a three-page thing that I wrote and I’ll copy and paste it in and it’ll just be a wall of text.
Joshua Canter: Yeah.
Josh Klemons: If you do the exact same thing in Claude, it turns it into like an attachment and you can click see more, but instead of the wall of text, it’s just like a very short paragraph so that you can kind of like scroll around and like even just like the I I don’t
Joshua Canter: Mhm.
Josh Klemons: know like it’s like weird to me that like chatt hasn’t used claude enough to be like I’m sure that’s like a 10-minute fix,

Joshua Canter: Yeah. No, totally.
Josh Klemons: but it feels so much easier to like talk to it when I’m not just seeing walls of text in between us.
Joshua Canter: Yeah. Yeah. Well, I think Yeah.
Josh Klemons: So,
Joshua Canter: I think chat GPT got hit with the like always using emojis like when it first came out and always using
Josh Klemons: I love how much
Joshua Canter: emojis, always using the M dash and then they’ve like pivoted so far. But yeah, I I used Claude today. I’m going to a conference next week and I’m trying to do a happy hour. I’ve never been to um Denver, Colorado. I’m like, “Find me a few happy hour places for this kind of vibe, this meeting.” It had a map. They said, “You’re here. This is where your hotel is.
Josh Klemons: Whoa.
Joshua Canter: This is all the other.” I was like,
Josh Klemons: Chat BT will give you places,
Joshua Canter: “This is amazing.
Josh Klemons: but I’ve never seen it.
Joshua Canter: This is amazing.”
Josh Klemons: I I’ve done that, too.

Josh Klemons: Like where I’m like, I’m in a city I’ve never been to. What neighborhoods are walkable and cool?
Joshua Canter: Yeah.
Josh Klemons: And it just like lists them with emojis and b*******,
Joshua Canter: Yeah.
Josh Klemons: you know? Like a map would be amazing.
Joshua Canter: Right. Yeah.
Josh Klemons: Yeah,
Joshua Canter: Yeah.
Josh Klemons: that’s wild. Yeah,
Joshua Canter: Map’s cool. I know.
Josh Klemons: that’s amazing.
Joshua Canter: No. Yeah. You’re It’s It’s funny. I never thought about the UX, but it is very I think they they also are like vibe coding the hell out of it, you know? Like they’re releasing new features every day that I’m like,
Josh Klemons: Yeah,
Joshua Canter: you guys got to slow down. I can’t keep up.
Josh Klemons: that’s wild.
Joshua Canter: Like I haven’t even like we talked about the schedule test. I haven’t even tried it cuz I haven’t had time to like build it because there’s other s***
Josh Klemons: Right. Right.
Joshua Canter: I’m doing like slow down.

Joshua Canter: So
Josh Klemons: How do you think AI is going to change campaigns in the next two cycles,
Joshua Canter: yeah.
Josh Klemons: next couple cycles?
Joshua Canter: Yeah. So um definitely. So one of the things that I think about AI fundamentally within the workplace or within the work work product workflow whatever is that it makes everything it speeds everything up right like it is you know for better or worse
Josh Klemons: Sure.
Joshua Canter: you could say write me this press release and it does it right I think that’s a whole separate conversation should ethics whatever you know process-wise but it does right um campaigns are naturally fast right like you have to write a press release really fast so I think there’s either two things going to happen is one you’re either going to get a
Josh Klemons: Right.
Joshua Canter: lot as these tasks start getting faster, the the um like the speed of campaigns will double, triple increase. And I don’t know, I worry for the poor new, you know, campaign staffer that’s smoking cigarettes outside because he can’t keep up with the pace, you know, like if the pace is twice as fast, the work life balance is twice as bad.

Joshua Canter: Like, I’m sorry.
Josh Klemons: Right.
Joshua Canter: Or it’s going to free up the time to do more highle things in campaigns, which have always been kind of like a tech incubator kind of vibe.
Josh Klemons: Yeah, for
Joshua Canter: Startups, you know, there’s a lot of connections there.
Josh Klemons: sure.
Joshua Canter: they’ll be trying a lot more things and doing a lot more things, right? Particularly if there’s not AI interfacing with them. So like you know on the ground you know marketing or FE or canvasing or whatever the case may be where AI is more detached like maybe the ad stuff will be so much simpler that you can put more time and
Josh Klemons: Yeah.
Joshua Canter: effort into that side of
Josh Klemons: No, I like that. Um, on that front,
Joshua Canter: things.
Josh Klemons: do you think that this is like who comes out ahead? Is this better for smaller teams because they can just like do 10 times as much or is it better for like the big orgs that have the capacity to like keep learning and keep on the cutting edge?
Josh Klemons: Like do the smaller campaigns and orgs fall further behind or does this give them an opportunity to like compete in a way that they couldn’t have two years
Joshua Canter: Yeah.
Josh Klemons: ago?
Joshua Canter: I mean, obviously I’m a big believer in AI. So, my fundamental theory is that it’s a great equalizer,
Josh Klemons: Okay.
Joshua Canter: right? And I think we can make arguments, niche arguments that would not in economic inequality like I’m thankfully don’t have to deal with that.
Josh Klemons: Yeah.
Joshua Canter: That’s someone else, right? But but yeah, so I do think that the the it will give a leg up to the smaller campaigns,
Josh Klemons: Yeah.
Joshua Canter: the smaller orgs to kind of compete at the same level as some of the bigger stuff because the big campaigns like I remember this was probably 2016, maybe it was 2020, I don’t know, one of the times that Trump won, he had so many more ads because the organization was so much bigger that he could do so much more split testing. Right.
Josh Klemons: Wait, let me interrupt you.

Joshua Canter: If let’s say it was Yeah.
Josh Klemons: Hillary Clinton had 64,000 ads in 2016.
Joshua Canter: Okay.
Josh Klemons: No,
Joshua Canter: So,
Josh Klemons: no,
Joshua Canter: maybe it wasn’t 2016.
Josh Klemons: Donald Trump had over 5 million.
Joshua Canter: Oh, no. Yeah. Okay. So,
Josh Klemons: It was 2016.
Joshua Canter: it was 2016. I was like, “Yeah,
Josh Klemons: Like the Hillary Clinton campaign was as innovative as any campaign had ever been.
Joshua Canter: boom.” Yeah. Yeah.
Josh Klemons: and Donald Trump. This was back when you could like target people with like racist s***
Joshua Canter: Totally.
Josh Klemons: that was just targeting to like very spec like you know they were essentially taking it like the reason why we no longer have all this political
Joshua Canter: Yeah.
Josh Klemons: targeting is because the Trump campaign used it for evil in such a powerful way.
Joshua Canter: Totally. Well,
Josh Klemons: But I use that example like literally millions of different ads compared to the Clinton campaign which was 64,000.
Joshua Canter: yeah. Yeah.
Josh Klemons: So like yes they they were able to do something just wild in 2016 which you know respect the

Joshua Canter: Yeah. Okay. Perfect. Yeah.
Josh Klemons: process even if like you know was disgusting.
Joshua Canter: So, I don’t know.
Josh Klemons: Yeah.
Joshua Canter: Totally.
Josh Klemons: Yeah.
Joshua Canter: Totally. And look, I mean, I think you can make a through line that a lot of stuff is why I got to build this tool today,
Josh Klemons: Right.
Joshua Canter: you know? Like there’s a there’s a pretty good through line,
Josh Klemons: Right. Yeah.
Joshua Canter: but but whatever.
Josh Klemons: Could we have learned from that in real time instead of two years later?
Joshua Canter: But no, but imagine like Yeah.
Josh Klemons: Right. Exactly.
Joshua Canter: Yeah. Could imagine like Hillary could have done that many like I think the art for me and let’s just take those two examples. It’s not necessarily the Trump being able to be the the campaign there being better and getting ahead. I think it would put Hillary at an equal living field.
Josh Klemons: Check.
Joshua Canter: I don’t know if Hillary goes up to equal Trump’s amount of ads or they both go up to equal, but I think they are equal because I don’t know if there’s so much expertise around
Josh Klemons: Sure.
Joshua Canter: AI unless you’re doing like really intense research or something. But like I’m pretty, you know, uh I think I’m as knowledgeable as the next person. I just put more time into it. You know what I mean?
Josh Klemons: Sure.
Joshua Canter: like there’s not some basis that I have here or education or something. So, I really see it as a level field. And I think we’re going to start to see particularly with campaigns, smaller down ballot campaigns, some of them pull way far ahead either in terms of tech they’re using or what they’re doing because the particularly challengers because the incumbents are just in their ways and don’t want to.
Josh Klemons: Right?
Joshua Canter: Right.
Josh Klemons: It’s the disruption model,
Joshua Canter: Um and that will really totally Exactly.
Josh Klemons: right? Like they know what’s working, so they don’t try anything new.
Joshua Canter: Exactly.
Josh Klemons: And then you’ve got this like new and actually like part of I read a lot about the 2016 campaign between Clinton and Trump. And it’s a good example because the Clinton campaign was so much more experienced.

Joshua Canter: Yeah.
Josh Klemons: So Meta is reaching out and saying, “We’d like to help.” And they were like, “No, thank you.” Which I said the same thing. They reach out to me every day and I’m like, “No, leave me alone.” And the Trump campaign was like, “Great.” And it turned out,
Joshua Canter: Yeah.
Josh Klemons: I read about this, so lookalike audiences,
Joshua Canter: Yeah.
Josh Klemons: I don’t know how much you’ve like managed.
Joshua Canter: Yeah. Yeah. Yeah. I know.
Josh Klemons: So lookalike audiences were terrible for a long time and then they kind of got good and they’ve gone back and forth.
Joshua Canter: Look like Yeah.
Josh Klemons: Essentially, what I read was that the Clinton campaign didn’t use look-ike audiences because they were notoriously bad. The Trump campaign had never heard of lookike audiences and when they heard about it, they were like, “Hell yeah, let’s go.” And it turned out that they were able to build lookike audiences of like the most racist people in a district or the most homophobic people in
Joshua Canter: Okay.

Josh Klemons: a district and create content directly for those people. And it actually wound up being a superpower for them that enabled them to like really microtarget tons of people.
Joshua Canter: Wow.
Josh Klemons: And again, that came from like not that Clinton was the incumbent, but like she certainly was working with the the best in the industry and Trump was working with like Brad Parcale,
Joshua Canter: establishment. Yeah. Yeah. Yeah.
Josh Klemons: you know,
Joshua Canter: Totally.
Josh Klemons: like who was like a scammer trying to figure it out every day as he went,
Joshua Canter: Yeah. Yeah.
Josh Klemons: you know.
Joshua Canter: In random Texas.
Josh Klemons: Exactly. So, no,
Joshua Canter: Bum f***
Josh Klemons: I I think it’s a fair point.
Joshua Canter: Texas.
Josh Klemons: So,
Joshua Canter: Yeah.
Josh Klemons: let’s say a campaign strategist, candidate,
Joshua Canter: Yeah.
Josh Klemons: somebody’s listening to this right now. They’ve used an AI tool for like general chat stuff, but not like you. What’s like one actionable thing that you think somebody could like act?

00:54:50

Joshua Canter: Yeah.
Josh Klemons: Let’s assume that 90% of people listening to this are not going to turn around and start vibe coding tools.
Joshua Canter: Sure.
Josh Klemons: What is something that they could be doing with AI for their campaign or their org or their advocacy, you know, cause today that they’re not?
Joshua Canter: Yeah.
Josh Klemons: And maybe that’s not a fair question, but like I don’t know. I’m curious if you’ve got like an easy go.
Joshua Canter: Yeah. No,
Josh Klemons: Okay.
Joshua Canter: I think so. Yeah. I think I think a lot of people what I’ve seen from my co-workers or colleagues or everything,
Josh Klemons: Sure.
Joshua Canter: you know, peers in the industry is like they’ve been utilizing it for production like write me a press release or like write me social content which it’s great for. I think though it’s also great for research and I think that’s particularly like there’s I think they call it extended thinking or research mode or something in CLA where you can like click it on and it takes like five minutes which

Josh Klemons: Yeah.
Joshua Canter: I think is different than what we’re used to you know in life but but yeah but that to me is
Josh Klemons: For sure.
Joshua Canter: like tell me everything about this issue in this district or this particular
Josh Klemons: Sure.
Joshua Canter: backstory or something and again you have to gut check it you have to figure things out but like that to me is like a great you entry way into it and being able to refine it and then also talking through it. Like a lot of times I’ve seen people prompt and get a response and that’s it.
Josh Klemons: Sure.
Joshua Canter: But I love to prompt, get a response, check it, you know, kind of fight them on it. Like I said, get into like a little argument kind of stuff. Um, one I’m doing right now, these are personal, but I’m like training it to be the best gardener in the world. I’m like, go be the best gardener or go research being the best gardener and then come back and let’s have a conversation about my plants that are dying or my jasmine that’s stalled or whatever the case may be, you know?
Joshua Canter: So, I think that could also be really cool like go be the best, you know, or or know the most about this district possible, come back and then let me have a conversation with
Josh Klemons: I’m only I love that.
Joshua Canter: you.
Josh Klemons: I think that’s really helpful and very good context because my guess is I’ve only used research like once or twice and it was just like to see how it worked, you know? Like I had it like help me explain how Harry Howry Reid turned Nevada from like a reddish purplish state into a blue
Joshua Canter: Yeah, totally.
Josh Klemons: state.
Joshua Canter: Oh
Josh Klemons: I was just like I I couldn’t find anything on the internet that explained it like in like good analysis.
Joshua Canter: yeah.
Josh Klemons: So I was like go do this. I’m just like curious. And it wrote me a really interesting like three or four page paper that like I didn’t necessarily get like a step-by-step what to do next,
Joshua Canter: Yeah. Yeah.
Josh Klemons: but it was like an interesting like it found all the like little pieces of it and put it together in a very digestible way.
Joshua Canter: Yeah.
Josh Klemons: But I haven’t tried it at all for campaigns. I will say it’s funny.
Joshua Canter: Totally.
Josh Klemons: um a same friend of mine that I mentioned earlier, uh he’s a gardener and he said he will take a picture of a plant and ask it what’s wrong with it
Joshua Canter: Yeah. Yeah,
Josh Klemons: and Claude will tell it and like he’s literally like making his garden healthier using cloud.
Joshua Canter: totally. That’s Yeah.
Josh Klemons: So I think a lot of folks who don’t use AI every day are not thinking about it beyond like replacement for Google or
Joshua Canter: Yeah. Oh, it’s a shift.
Josh Klemons: write me a press release but like there’s wild things you can do with
Joshua Canter: But it’s Yeah, you’re right. It’s a shift.
Josh Klemons: it.
Joshua Canter: It’s it’s it’s truly a shift. And this is where, you know, there’s like tweets running around or whatever we’re supposed to call them now of like if you’re Yeah.
Josh Klemons: Tweets. They’re tweets. It’s Twitter.

Josh Klemons: It’s
Joshua Canter: Yeah.
Josh Klemons: straight.
Joshua Canter: if if your friends aren’t talking about claw and open claw whatever the you need to ditch your friends but which I don’t agree with but it is a crazy thing like going through life and being like especially friends that I
Josh Klemons: Sure.
Joshua Canter: have I have one friend that’s like more relational claude right like wants to talk about her shows with it and like and I’m like you’re getting into territory I’m not sure but you know whatever so
Josh Klemons: Yeah. I’ve got friends in I’ve got real life friends. But you do you. For sure.
Joshua Canter: yeah yeah but but I’m here for yeah so anyway so it’s like a shift that you’re kind of going
Josh Klemons: Yeah. For sure.
Joshua Canter: through life I feel like your dayto-day and again you see where these tools are coming from. I’m like huh should I ask AI for this? Same thing with the gardening like huh I don’t I can Google how to do this. I my dishwasher broke or my uh disposal broke.
Joshua Canter: Okay, let me ask AI. You know there it’s a shift I think that is definitely like happening real
Josh Klemons: Yeah. And I I think it’s really interesting and again like campaigns are both super innovative and often behind the curve because we’re
Joshua Canter: time.
Josh Klemons: overstressed and overworked and like you know like a team of two is doing the work of 10 and like AI can both
Joshua Canter: Yeah, totally.
Josh Klemons: help with that but also it takes like putting in the time. So I think that’s like a really helpful reminder that like just trying to do new things with it to see what it can do could potentially move you
Joshua Canter: Yeah.
Josh Klemons: faster. Obviously, some campaigns like on ethical standpoints don’t touch it and that’s fine too. Like you know that this is not that conversation like this is a conversation about what you can do with it if you want to use it.
Joshua Canter: Totally. No.
Josh Klemons: Uh somebody else will at some point I got to have somebody else on to make the case that nobody should be using AI at all and like I’ll be

Joshua Canter: Yeah. It’s a whole separate thing. It’s a whole separate thing. Yeah.
Josh Klemons: interested to hear it.
Joshua Canter: Yeah.
Josh Klemons: Um so folks want to follow you check out your reports.
Joshua Canter: Yeah.
Josh Klemons: I I will have your reports for sure linked the best and the Texas Senate one.
Joshua Canter: Yeah,
Josh Klemons: But how can folks find you online and like you know where should go folks go?
Joshua Canter: I Yeah, LinkedIn. I mean, I’m trying to be better on LinkedIn.
Josh Klemons: Yeah,
Joshua Canter: Obviously, it work.
Josh Klemons: we found each
Joshua Canter: It’s working out so far. So, I say LinkedIn.
Josh Klemons: other.
Joshua Canter: Yeah, definitely LinkedIn. And I’ll say, too, about the reports, like I’m trying to figure out, so I’m having my interns do like a GOTV research into organizations, how to turn out people if you’re not a candidate or a super PAC.
Josh Klemons: Sure.
Joshua Canter: Um, and part of it’s this research, right, is like what are people running in ads and stuff. And so I’m trying to figure out a way to like build this as a skill or MCP or what I don’t know what it’s called so

Josh Klemons: Interesting.
Joshua Canter: other people can like use it in their cloud or whatever too. But until then, I’m always open to like generating reports because I think it’s really interesting and I love talking stuff. So I’ll say like add me on LinkedIn, connect with me on LinkedIn, you know, message me, I I’ll drop in a report, you know, happy to do that kind of stuff and burn through some tokens.
Josh Klemons: Sweet. I’ll have a link to your LinkedIn in the show notes along with those two reports and a couple of the tools that I checked out that I think are worth checking out.
Joshua Canter: appreciate
Josh Klemons: And then uh yeah, keep us posted.
Joshua Canter: it.
Josh Klemons: When uh when Grock can when Grock’s API can start telling me what’s going on with Wisconsin politics, I’ll have you back my will have a whole conversation about that.
Joshua Canter: Yeah, I think it’s I think it’s going to go a little nasty if Grock uses it.
Josh Klemons: Oh, I guarantee it.
Joshua Canter: You know what I mean? Like it’s gonna read it and be like,
Josh Klemons: But it’s still helpful.
Joshua Canter: you know, you know.
Josh Klemons: I really appreciate you coming on,
Joshua Canter: Yeah. So,
Josh Klemons: man.
Joshua Canter: for sure.
Josh Klemons: This was fun.
Joshua Canter: Yeah. I appreciate it, too. Thank you so much.

 

 

April 1, 2026/0 Comments/by Josh Klemons
https://joshklemons.com/wp-content/uploads/2026/04/Using-AI-to-Get-More-Out-of-the-Meta-Ads-Library-with-Joshua-Canter.jpg 1080 1080 Josh Klemons https://joshklemons.com/wp-content/uploads/2023/05/Reverbal-Communications-Josh-Klemons.svg Josh Klemons2026-04-01 14:02:502026-04-01 14:10:15Using AI to Get More Out of the Meta Ads Library with Joshua Canter | Hello Merge Tag Ep. 51
Hello Merge Tag, Politics

One Media Company is Carrying ICE’s Public Image Almost Entirely on its Shoulders with Drew Eldredge-Martin | Hello Merge Tag Ep. 48

One Media Company is Carrying ICE's Public Image Almost Entirely on its Shoulders withe Drew Eldredge-Martin

“One media company is now carrying ICE’s public image almost entirely on its shoulders…”

After analyzing 12 billion views across 90,019 videos posted in December and January, Drew Eldredge‑Martin of Ground Truth AI found that Fox News accounts for 70% of ALL views on YouTube tied to positive narratives about ICE — without Fox, the pro‑ICE narrative would nearly collapse.

In this episode of Hello Merge Tag, Drew breaks down what his narrative analysis reveals about who’s shaping the conversation, what content is actually driving attention, and what it means for campaigns in 2026.

We covered:

🔹 Why Fox News is driving both positive and negative ICE content

🔹 What types of videos are rising to the top of YouTube

🔹 The growing role of AI‑generated content in narrative shaping

🔹 Who the heck Benjamin is — and why he’s outperforming CNN on this topic

🔹 What sentiment data leading into Election Day tells us about the big 2025 campaigns

🔹 Why campaign teams need to pay even more attention to user‑generated content

🔹 And why you shouldn’t be sleeping on YouTube

If you want to understand how digital narratives actually map to influence — and what that means for politics, brands, and public opinion — this episode is a must‑catch.

 

Listen to the full episode right here, or wherever you stream podcasts.

If you prefer video, you can also watch our full conversation:

Find all episodes at HelloMergeTag.com or wherever you stream podcasts.

Links

Drew’s LinkedIn Post
Their ICE study
Their study on the NYC Mayoral primary
Drew’s LinkedIn
Ground Truth AI
Clarify Intelligence
The FYP.News (The newsletter I worked on with Courier tracking the presidential TikTok programs throughout the 2024 campaign.)

 

Big thanks to our sponsors:

Civic Shout. Learn more about the great work they’re doing to help Democratic campaigns and progressive nonprofits build their lists ethically at civicshout.com/partners.

 

Episode Transcript

This transcript was automatically generated and has not been copy-edited. While it can serve as a helpful guide to our conversation, it may contain errors or omissions. For the most accurate representation, we recommend listening to (or watching) the full episode.

Josh Klemons: Quote, “One media company is now carrying ISIS public image almost entirely on its shoulders. After analyzing 12 billion views across over 90,000 videos posted in December and January, we found that Fox News now accounts for 70% of all views on YouTube tied to positive narratives about ICE. Without Fox News, narrative supporting ICE narrative uh would nearly without Fox News, narrative supporting ICE uh would nearly collapse.
Andrew Eldredge-Martin: Sure,
Josh Klemons: Um Drew Eldridge Martin posted this on LinkedIn. I of course had to learn more. Uh so I invite him on the pod. Andrew is the founder and CEO of Groundtruth AI, a research and intelligence firm focused on how digital narratives shape public opinion and perception. So Drew, I called you Andrew. Sorry, Drew. Uh, thanks so much for coming on the VOD. Uh, so let’s start with can you summarize a bit about what you and Groundtruth AI do just so we have the broader context of like where this study falls?
Andrew Eldredge-Martin: absolutely. Thanks for having me. Um, what we do is we collect uh video from uh the internet and we watch it uh and we pull out from all of those videos narrative intelligence. So, literally narratives about people, about institutions, about issues.

Andrew Eldredge-Martin: Um and then we organize that data and append uh metadata and we do our own analyses of them uh to deliver insight to allow people to track what’s going on in a given uh given area given topic and then we have ad tech integrations that allow people to actually do something about it. So, you know, in the context of um you know, a political campaign, uh if candidate A uh you know, uh wants to, you know, talk to voters who are receiving negative information about themselves, we can uh allow them to uh to reach audiences who are receiving those types of uh narratives.
Josh Klemons: So obviously when you say you watch 90,000 videos, you’re using an AI tool to do that to like build narratives.
Andrew Eldredge-Martin: Yeah,
Josh Klemons: You’re you don’t have like a team of people watching 90,000 videos one
Andrew Eldredge-Martin: absolutely. Yeah, I we have 90,000 employees.
Josh Klemons: day,
Andrew Eldredge-Martin: Each of them watched one video.
Josh Klemons: right? Exactly.
Andrew Eldredge-Martin: Uh no, we we yeah,
Josh Klemons: Exactly.
Andrew Eldredge-Martin: we use a multimodal AI to watch all of these videos uh to then pull out narrative intelligence from each of them.
Andrew Eldredge-Martin: And it’s an important differentiation. These are not transcriptbased. um which is a really important uh differentiator between other more like legacy um media intelligence research that’s out there because so much of the content that is going viral particularly around the very biggest brands and people uh on platforms like YouTube for instance these days are actually generated by AI. Um, we did a study last fall looking at content that was talking about President Trump and found that uh more than 50% of the top 100 videos um by view count um that mentioned him on YouTube uh were actually generated by artificial intelligence. And so most of that video content, it doesn’t have a traditional voice over.
Josh Klemons: That’s
Andrew Eldredge-Martin: It doesn’t have text on screen. And so a transcript analysis will totally miss what the video is about and not not not see it. Um so we of often are surprised by the uh types of things that our system is able to identify um that’s communicating let’s say about an issue. We did something on renewable energy uh last fall where uh there was a video uh that told a short story uh that was very positive about solar energy’s uh ability to help people uh let’s say have an air conditioner in really hot weather um uh when the power goes out uh they can support it themselves.
Andrew Eldredge-Martin: But that wouldn’t have been caught uh in our in a study if people had just been looking at transcript because there was no voice over on that video.
Josh Klemons: Interesting. Um, okay. So, let’s talk about the particular study that like got my attention.
Andrew Eldredge-Martin: Yeah,
Josh Klemons: Anyway, so you wrote without Fox News,
Andrew Eldredge-Martin: sure.
Josh Klemons: narrative supporting ICE would nearly collapse. So,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: like let’s just walk through that finding and like yeah,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: what exactly does that mean in in that uh in that context?
Andrew Eldredge-Martin: So in the study um what we found was that overall um narrative sentiment narrative nar uh negative narratives about ICE were overwhelming. Uh 85% of all videos in the study contained those and 81% of all the views of those videos were contained a negative narrative um about ICE. When we looked at just the components of the study that had positive narratives about ICE, 70% of those videos were posted by Fox News. Um, that doesn’t even account for some other Fox News owned accounts um that had smaller smaller components, things like Fox Live and that that kind of thing.

Andrew Eldredge-Martin: So it’s really playing just a dominant role in the content production and and uh virality and driving of views um on the YouTube platform um uh for kind of that narrative infrastructure uh of like uh supporting ICE and its um uh its activities.
Josh Klemons: So 15% of the videos you watched were positive and of those 15% 70% were created by Fox. How did that compare to viewership? Like were they also getting 70% of the eyeballs or was it just about
Andrew Eldredge-Martin: So, one of the things that is difficult if you’re looking at at um uh content from the
Josh Klemons: content?
Andrew Eldredge-Martin: outside uh on the on the YouTube platform, if you’re not the owner of a channel is you don’t know the exact reach, right? The user reach.
Josh Klemons: Sure.
Andrew Eldredge-Martin: you are only able to look at aggregated numbers like the total number of views that a video has and uh so we’re able to see the number of views we’re also see able to see the number of videos and the to aggregate views that every creator is is uh posting on the platform and so um we can’t give you an exact reach number.

Andrew Eldredge-Martin: What the metric we like to use um is something that we’ve we’ve built called unsurprisingly ratings points. Uh which may sound familiar to those of you who have looked at uh uh traditional like legacy
Josh Klemons: Okay.
Andrew Eldredge-Martin: television uh uh media metrics. Gross ratings points is is an analogous um metric.
Josh Klemons: You refer to them as narratives ratings points.
Andrew Eldredge-Martin: It’s basically exactly nar right.
Josh Klemons: Yeah, narrative ratings points.
Andrew Eldredge-Martin: So ratings points is the metric. We apply them to narratives.
Josh Klemons: Okay.
Andrew Eldredge-Martin: We also apply them to individual creators, but it’s the same metric in either place, just a different subject that we’re that we’re applying them to. And so it’s a measure of reach and frequency um by looking at the total number
Josh Klemons: Okay.
Andrew Eldredge-Martin: of views that a creator like Fox News or a overall narrative has driven about a specific subject. So the denominator is actually just the average number of views for a video in the study.
Josh Klemons: Okay.
Andrew Eldredge-Martin: That’s a relative metric within a given

Josh Klemons: And uh so and so I’ll kind of repeat the
Andrew Eldredge-Martin: study.
Josh Klemons: question in that context. Like 70% of the content that was created, are they getting 95% of the narrative ratings points or 50% like are some of the smaller of the 30% of creators that aren’t Fox News that are pro ICE, are they also finding an audience or they’re all being drowned by Fox and it’s really just Fox all the
Andrew Eldredge-Martin: Yeah. No, they’re they’re they’re utterly being drowned out by by Fox.
Josh Klemons: way. Okay. And Oh,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: go ahead.
Andrew Eldredge-Martin: There there’s basically one creator that is driving the positive narratives that is getting any kind of reach on the on on
Josh Klemons: So,
Andrew Eldredge-Martin: YouTube.
Josh Klemons: there are plenty of huge right-wing outlets out there, funded right-wing outlets.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Is Fox News more pro ICE than them or are they just they still control such a dominant part of the market share that they just are drown? I think that this is an interesting case of like, okay, ICE is obviously, you know, I wouldn’t call it an outlier, but it’s like an extreme piece of like the Trump administration.

Andrew Eldredge-Martin: Yeah. Yeah.
Josh Klemons: Like, why isn’t Newsmax or,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: you know, somebody else like also seeing movement here? Is it because they’re not as conservative on this issue or as awful on this issue? Or is it because Fox is just still so much bigger than them in the scheme of things?
Andrew Eldredge-Martin: It’s a really interesting question and I think gives me a few ideas for further analysis that we could do on this.
Josh Klemons: Love doing
Andrew Eldredge-Martin: Um I I want I want to I want to raise uh one other like
Josh Klemons: that.
Andrew Eldredge-Martin: kind of surprising statistic um that I think may help us get at this get at this uh point. Um, Fox News was the fourth largest creator
Josh Klemons: H
Andrew Eldredge-Martin: driving negative narratives about ICE as well,
Josh Klemons: what?
Andrew Eldredge-Martin: right? So, this is what this is. It’s kind of a paradox.
Josh Klemons: So they’re just competing with themselves on like content at this
Andrew Eldredge-Martin: It’s it’s it’s it’s surprising.
Josh Klemons: point.

Andrew Eldredge-Martin: We dug into this because it was surprising to us as well. And what we found is that our system, our multimodal AI was seeing the visuals in the Fox coverage of Minneapolis and of other ICE um content, other ICE um engagements. And it was seen the clips, right, the body cam style footage, the vertical videos, the clips from on the ground in in these places of violence, of protest, of community opposition. And it was understanding that as negative communications. Now, at the same time,
Josh Klemons: Sure.
Andrew Eldredge-Martin: as you see these visuals on a Fox video, there is an editorial piece, right? There is a a transcript, right? the host on Fox is saying something and their editorial view is very supportive of ICE, right? Which is what we see in the positive narrative statistics that we were talking about. But the visual communication is what was being picked up by this pos by this negative ICE um statistic about Fox as well that anyone watching this cannot avoid seeing right the reality on the ground.

Andrew Eldredge-Martin: I think there is a way in which the content coming out of a place like Minneapolis during this time period is hijacking the Fox narrative distribution system, right? People on the ground are capturing reality. Those visuals are so viral, right, and so explosive that even Fox is sharing them with their traditional audiences, but also in their traditional clips that are then being put onto a platform like YouTube and are going so viral that they’re putting more up there, right? Um, so there’s a way in which reality is winning here.
Josh Klemons: even like they’re doing their best to editorialize it into positive yet what they’re showing is absolutely living within the confines of like negative attention that is obviously driving the country right now like um you know it’s not just YouTube like
Andrew Eldredge-Martin: That’s the interpretation of our system and I think it’s something that I agree with. Um, and if you look at the, you know, the as these clips across all these creators in our study,
Josh Klemons: Sure.
Andrew Eldredge-Martin: as these clips were driving up the views of these dominant negative narratives, a lot of them very visual.

Andrew Eldredge-Martin: Um, right. As you’ve you’ve seen the footage.
Josh Klemons: Yeah, of
Andrew Eldredge-Martin: Sure.
Josh Klemons: course.
Andrew Eldredge-Martin: um you saw President Trump’s approv uh disapproval ratings also begin to rise. Um and so I I think there’s a way in which uh this moment there’s a lot that we can learn from this moment about the ability of of reality to reach even audiences who are let’s say highly partisan one side or the other reality has a way of breaking through and I think this is a really good example of that And I think you know u individuals uh and organizations need to to take take stock of this uh moment because uh it was moving numbers uh you know at at a level that we have not seen um uh significantly um in uh in this administration.
Josh Klemons: Yeah. Uh, really powerful. You wrote that the pro ICE narrative landscape is highly vulnerable because it depends so heavily on a single outlet, which I think makes a lot of sense. Do you think that’s a recurring problem for Republicans in general who seem to be living more and more in a like information bubble or is this an outlier even by like the right-wing bubble standards in your opinion?

Josh Klemons: Like can this be extrapolated to other issues that like if Fox News cease to exist tomorrow, does the bottom fall out of Republican support? um or they’ve created a big enough ecoformational ecosystem that they would like continue to live on beyond, you know, losing their flagship.
Andrew Eldredge-Martin: I I don’t want to speculate outside of this issue uh too aggressively.
Josh Klemons: Is that what you’re doing? No,
Andrew Eldredge-Martin: Um you we’ve done we’ve we’ve done we’ve done a little bit of work
Josh Klemons: I’m just kidding. Okay, go ahead.
Andrew Eldredge-Martin: um uh looking at um uh some other you know big topics. Uh but uh there’s a lot more work that really needs to be done here. um you know uh on other issues uh for instance I think it’d be really interesting to look at uh health care look at immigration more broadly um this is a snapshot here right this is this is media intelligence about a period of about two months um during um a really um a really major media moment um in that case people were going to Fox absolutely I don’t think While I think it’s still like a very large outlet in the other like limited work that we’ve done uh on related topics, um uh it’s one big voice among many.

Andrew Eldredge-Martin: Um I think this is a uh this was this was moment that Fox was uh uh really driving an outsized amount of impact overall.
Josh Klemons: I mean again the the context in which I’m asking the question obviously is like we all all of us watch as like the right-wing ecosystem media bubble whatever continues to expand and you’ve got all these massive voices But the idea that one that the dominant player is not just dominant but like dwarfing all the rest combined does change the impetus over like where should our you know if folks are going to boycott
Andrew Eldredge-Martin: Yeah.
Josh Klemons: advertisers like you know is is moving across all of the media as relevant as simply going after like the flagship and I you know obviously we’ve seen a lot of traction on that over the years of like not running ads on Fox News but like should we be validating Fox News? Should Mayor Pete be you know going on to Fox News regularly and giving them credence? And I I’m not saying I have an answer. I’m saying like based on what I’m hearing from you, like it seems like a question that folks should be asking whether you, me, or somebody else is asking it, you know, but like it seems like a relevant um question.

Josh Klemons: So um Oh,
Andrew Eldredge-Martin: Yeah, absolutely.
Josh Klemons: go ahead.
Andrew Eldredge-Martin: No, I I I very much agree that like um uh there are opportunities to reach
Josh Klemons: Um
Andrew Eldredge-Martin: audiences. I I I grew up in a really small town uh on a dirt road in Pennsylvania and um I you know grew up surrounded by a pretty conservative community um and was a you know uh was a was a was a Democrat growing up uh in a place where a lot of people didn’t see eye to eye with me um on a lot of political issues and like I I very much subscribe to um talking to people and meeting uh on some level on values and objectives of of of government and uh spending the time to
Josh Klemons: Yeah. Uh,
Andrew Eldredge-Martin: persuade.
Josh Klemons: really interesting. So, you mentioned that um like the negative sentiment towards ICE largely is coming from like body cam style short form content which probably is coming from both sides, right?
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Like it’s both like people like protesters and you know watch folks watching ICE as well as ICE themselves seem to be creating their own content.

Josh Klemons: Um but as a whole like within that short form content like is there a nar is there like a thematic approach to like what kind of video is working like is it like oh violence if it bleeds it leads or is there something more to it? Is it like it is there a theme line through which we can say this is good content in the context of dealing with ICE?
Andrew Eldredge-Martin: Speaking just kind of within the the research that we did, I think there were like there were two types of content that absolutely were rising to the top. one was some type of either AI generated or non AI generated but staged humor. Um, for instance, the single most watched video that mentioned ICE during this two-month period depicted a man who was driving away after being pulled over by ICE. They attempt to pull him over again,
Josh Klemons: Okay.
Andrew Eldredge-Martin: but he drives away again laughing.
Josh Klemons: Is this the guy with a scooter or he was in a car?
Andrew Eldredge-Martin: We’re No, he’s in a car,

Josh Klemons: Okay. Because the scooter video also was like huge numbers.
Andrew Eldredge-Martin: right? He’s like laughing.
Josh Klemons: Okay.
Andrew Eldredge-Martin: He’s just like not t Yeah, he’s like rolling down his window and then being like, “Oh, take it. See you later.” Right. It’s It’s very funny. It’s very like to me it looks very staged.
Josh Klemons: Sure.
Andrew Eldredge-Martin: Um but I can’t be sure. That had 33 million views,
Josh Klemons: Wow.
Andrew Eldredge-Martin: right?
Josh Klemons: Yeah. Okay.
Andrew Eldredge-Martin: Um and then um uh there were also like some uh like the there was a guy um in here. This is an interesting um kind of uh subplot to all of this. Uh if you look at uh all of the the creators, uh the third largest creator by Radiance Points was a creator named Benjamin. We don’t know who Benjamin is.
Josh Klemons: Okay.
Andrew Eldredge-Martin: um larger than larger than CMM in terms
Josh Klemons: He was the third biggest creator on ICE content. What a world we live in, man.

Andrew Eldredge-Martin: of reach and frequency talking about ICE during this period.
Josh Klemons: Okay.
Andrew Eldredge-Martin: His account doesn’t have any creator identity, no photo. The handle is, you know, a couple words and a number, right? It’s it’s it’s uh it looks almost uh like AI generated. The content is largely uh humorous. Um, but then it also seems to have some possibly real content. Like there’s there’s a mix of what looks like Gen AI, what looks like real content. Um, that is posting content about ICE. And some of it is like looks like real civilian footage, like the stuff that we were talking about, the body cam style or like just, you know, in a marketplace kind of watching what ICE is doing. And then other ones are really funny. Like there’s one video on there of ICE agents eating uh uh eating donuts after a donut truck like you know had an accident and their donuts all over the road. Like it’s very strange stuff. Um uh but yeah larger than CNN.
Andrew Eldredge-Martin: So humor and violence or the like like were the things that it bleeds it leads.
Josh Klemons: You violence.
Andrew Eldredge-Martin: I can tell you anecdotally from another study that I don’t have right in front of me right now, so I don’t want to quote any numbers, but uh um uh the the top creators talking about Donald Trump in the fourth quarter of last year were the late night hosts. Jimmy Kimmel top among among them um in terms of uh in terms of reach
Josh Klemons: Yeah. So,
Andrew Eldredge-Martin: frequency.
Josh Klemons: I was going to ask because like we’re talking about raw vertical video, like you know, very like lowfi, but like Fox News is obviously also creating very high quality. Yeah. Not as far as content,
Andrew Eldredge-Martin: Yes.
Josh Klemons: but like, you know, the look and the feel. Um,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: but like talk to talk about the discrepancy between like late show hosts have very high production value and that’s cutting through, but then like short form video is cutting through like that lowfi video is cut.
Josh Klemons: Like I’m trying to figure out like for campaigns and folks who are trying to create content like should they be focused more on looking like Fox News, you know, during prime time or more like Fox News out in the street like holding a camera and, you know, running around after protests? Did you see a through line between which of these is actually creating like bigger attention?
Andrew Eldredge-Martin: I mean, I would just actually take a step back and say like this exact question is playing itself playing out right now in like the the the battle for attention for all audiences in the US and in the world, right?
Josh Klemons: I’m asking you to solve all content through the context of this study.
Andrew Eldredge-Martin: Netflix is about to buy Netflix is about to buy Warner Brothers to up its premium
Josh Klemons: Exactly.
Andrew Eldredge-Martin: game while it tries to fend off like YouTube and Tik Tok who have like no cost of
Josh Klemons: Right.
Andrew Eldredge-Martin: development for their content. Um,
Josh Klemons: Right.
Andrew Eldredge-Martin: so at the end of the day, like my my take for campaigns is that it has to be all of the above.

Andrew Eldredge-Martin: That there are audiences that are going to want a premium product and are going to engage more with that. There are also going to be audiences that you need to reach that are looking for shorter form that are looking for lower like maybe fresher maybe more relevant like to something that’s happened in the last 72 hours, right? Content from a campaign. And those are all addressable audiences that you have to cater to and reach with your message and then you know organize
Josh Klemons: Okay. Um, so you you mentioned this earlier in this conversation, but you also talked about this in the report. Uh, you link the surge in negative ice content to a measurable like drop in Trump well bump in Trump’s disapproval uh, rating, which feels huge,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: but also like makes sense like this is a singular issue for him at the moment and he is failing to meet the moment and it is affecting his numbers. Do you think that if do you think if Fox News suddenly decided, you know what, this is wrong, we’re on the wrong side of this, all negative all the time.

Josh Klemons: Do you think Trump’s numbers would drop even further? Like, do you think that there is a direct correlation? Like, is Fox keeping Trump from falling even lower than here? It is.
Andrew Eldredge-Martin: we we saw a correlation uh during the time period of the study. Um it is very hard to draw a causal link between uh these these types of numbers.
Josh Klemons: Sure.
Andrew Eldredge-Martin: Um but um you given the extreme reach like even when even even when we looked at just US-based creators um like there’s a geo tag um uh for creators that they can identify where they are based. Not everyone uses it and you don’t have to, but just people who self-identify as I’m based in the United States and I’m putting content onto YouTube. um uh you know the the uh reach was well over 300 million um in the middle of in the early middle of
Josh Klemons: Are
Andrew Eldredge-Martin: um of January on a um uh on on this content uh just the the the content that was negative about ICE. Um so um is there more

Josh Klemons: you saying reach or imp like unique reach or there’s no way to measure that with
Andrew Eldredge-Martin: this is this is this is this is this is views which is the best proxy we have for reach right I’m sure there’s some
Josh Klemons: YouTube? Sure. Okay.
Andrew Eldredge-Martin: replication in there but that is a sign if the frequency if the
Josh Klemons: Because otherwise every American watched it, which is still like, you know,
Andrew Eldredge-Martin: frequency was three yeah still talking about a 100
Josh Klemons: right? You’re still talking about 100 million people, right?
Andrew Eldredge-Martin: million people that you’re reaching when you’re hitting those numbers um and uh that’s just a significant port like no matter how that’s targeted, right? However the algorithm is delivering it, you’re still reaching a significant portion of movable people, right? Um who who who appear to have uh to to have responded to this. I think there’s absolutely more um that can be moved in these in these numbers.
Josh Klemons: Sure.
Andrew Eldredge-Martin: Um but um you know uh it remains to be seen like you know What does the month of February look like?

Andrew Eldredge-Martin: We don’t we don’t know
Josh Klemons: Yeah. No, fair. Um,
Andrew Eldredge-Martin: yet.
Josh Klemons: okay. So, a while back, uh, you released a different study you did about the NYC mayoral primary between Mdani and Cuomo.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Um, top line,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: share some of the things you learned from that race. I think it’s helpful to see how you approach this beyond just this one
Andrew Eldredge-Martin: Yeah.
Josh Klemons: study.
Andrew Eldredge-Martin: Absolutely. We re released a number of studies. I think we have the most recent one on our website. It’s probably the one that you that you saw. Um so we we did I think three different looks at the race. The first one was uh looking at the eight weeks leading up to the primary last summer. It was one of the very first public studies we released um using u using uh clarify AI. And um what we saw there was an incredible amount of reach uh for Mandani’s campaign um with their ability to drive particularly uh organic uh non-paid content um uh through their supporters through uh influencers who were engaged with the campaign in one way or another.

Andrew Eldredge-Martin: um they were just dwarfing the Cuomo campaign um on on the YouTube platform. And um their sentiment though u the sentiment of that content was
Josh Klemons: Mhm.
Andrew Eldredge-Martin: um on the order of uh one and a half to two x more positive than negative. Right? They had a real like incredible reach,
Josh Klemons: I wrote down 71% negative.
Andrew Eldredge-Martin: but they also had like 150% positive
Josh Klemons: Uh positive, right? Um,
Andrew Eldredge-Martin: to 200% positive.
Josh Klemons: okay.
Andrew Eldredge-Martin: Um I don’t I forget that the number of like significantly positive but it’s not you
Josh Klemons: Sure. Sure. Okay.
Andrew Eldredge-Martin: know like Hillary Clinton had a like what 60 to 70% chance of winning in 2016 uh according to the prognosticators and pollster.
Josh Klemons: Okay.
Andrew Eldredge-Martin: Um so so it wasn’t it was it was a bit divisive but uh he was really he really had a strong positive message that seemed to be breaking through broadly on on the platform. Um as we moved into the general election, we did two studies and both of them showed um while Mandani was still driving like incredible reach um greater division in those sentiment numbers.

Andrew Eldredge-Martin: By the time the general election arose, um we were looking week by week. I don’t think we actually included this in the public study, but um we’ve got some we’ve got some numbers um that we were looking at week by week. Uh the final week was exactly 5050 the sentiment um amongst
Josh Klemons: Wow.
Andrew Eldredge-Martin: all content mentioning um Mdani’s name. um which we thought was was was pretty interesting uh because that wasn’t the perception of his campaign online um in the conversation in the media around the around the campaign that he had some you know um you know progressive you know uh u you know positions and seemed to be like really good at communicating them uh was definitely part of the uh part of the conversation that there was a lot of push back from Cuomo or for from Siwa or other outside voices. Absolutely. But I don’t think people kind of caught on to to this um in the in the conversation around the race. Um so anyway, we we were we were really fascinated with that.

Andrew Eldredge-Martin: I I’m we’re we built this narrative clustering tool um that we’ve used in our more recent studies after the New York City mayor’s race last year. So,
Josh Klemons: H
Andrew Eldredge-Martin: we’re looking to go back and do a narrative clustering analysis and hope to release those numbers in the coming weeks, but we haven’t done it
Josh Klemons: interesting. And um that content like that negative content that did the positive content go down
Andrew Eldredge-Martin: yet.
Josh Klemons: or the negative content caught up to meet it or it’s hard to say without like having the stud in front of
Andrew Eldredge-Martin: Yeah,
Josh Klemons: you.
Andrew Eldredge-Martin: it’s it’s it’s hard to be specific uh without like this additional analysis that we’re going to run. The the best analogy I have is that that first version that we were using through um through really the end of November of last year of of our technology um it it allows us to see the surface of the ocean. Um, this new clustering engine that we we were prototyping and starting to test in December of last year um allows us to see the ocean currents below the top of the ocean.

Andrew Eldredge-Martin: And so it allows us to do things like talk about um in the ice study context, what types of content, what types of narratives were driving a surge, right? uh versus um you know maybe disappearing you know as a story changes um the es and flows of of those discussions.
Josh Klemons: Yeah. No, interesting. I’m excited to see that tool uh in action. You you said you haven’t published anything with that
Andrew Eldredge-Martin: Yeah,
Josh Klemons: yet.
Andrew Eldredge-Martin: we haven’t published anything uh yet. Uh but we we did collect data on the uh Spamburger and Mikey Cheryl uh races as well. Uh and are uh yeah are looking forward to releasing a study looking at the 2025 races
Josh Klemons: I mean, if you’re taking um requests,
Andrew Eldredge-Martin: soon.
Josh Klemons: one thing that I think would be really interesting would be, especially retroactively, did did the sentiment analysis that you’re doing correlate with the end results in their victory? Like Mani won, but not, you know, he won, but he, you know, not as big as um Spanberger and like did Spanberger’s numbers stay higher.

Josh Klemons: So, I’d be very interested to see like how those correlate backwards.
Andrew Eldredge-Martin: Uh we have already done that work and we do have something to say about it.
Josh Klemons: Nice.
Andrew Eldredge-Martin: Uh but I’m not going to break any news
Josh Klemons: Today you should absolutely break some news today.
Andrew Eldredge-Martin: today.
Josh Klemons: No. Okay. Um but I mean assuming you can find correlation there which obviously like you’ll have to run a lot of studies before I’m sure you’re willing to say that. Uh that does say a lot about you know how much we should be investing in this uh and
Andrew Eldredge-Martin: Yeah. What what I what I will tell you is in week one of the 2025 races,
Josh Klemons: whatnot.
Andrew Eldredge-Martin: those three big races, um uh Mandani had a 50-50 sentiment of all the content
Josh Klemons: Wait, week one,
Andrew Eldredge-Martin: mentioning him the last week right before leading up to election day.
Josh Klemons: meaning the last week. Okay, week one. Just making sure we’re on the same page.
Andrew Eldredge-Martin: So,
Josh Klemons: Okay, go ahead.

Andrew Eldredge-Martin: at the time when you’re getting your your late deciders and your undecideds,
Josh Klemons: Yeah. Right.
Andrew Eldredge-Martin: he was 5050 on all of YouTube.
Josh Klemons: 5050.
Andrew Eldredge-Martin: Mikey Cheryl was better than two to one positive to negative.
Josh Klemons: Wow.
Andrew Eldredge-Martin: I’m sorry,
Josh Klemons: Okay.
Andrew Eldredge-Martin: that’s Spamburger was better than two to one. Uh Mikey Cheryl was more than seven to one positive.
Josh Klemons: Wow. Okay. So, I can go do my own analysis
Andrew Eldredge-Martin: So there were I and I um we hadn’t done this piece of
Josh Klemons: now.
Andrew Eldredge-Martin: the study yet like the the like a look at like uh paid media. Um I suspect that is a reflection of um paid media surging um in the the two governor’s races late um on the side of the eventual winners. Um but um I we’re we’re we’re really interested to see what the narrative clustering trends were going into election day that should give us some some some greater
Josh Klemons: When you’re talking about this sentiment content,
Andrew Eldredge-Martin: insight.

Josh Klemons: you’re talking about third party actors. This is not the campaigns themselves. This is, you know, Joe Joe smartphone making a
Andrew Eldredge-Martin: It’s everything. Yeah,
Josh Klemons: video.
Andrew Eldredge-Martin: exactly. It’s it’s everything. I think one of like if I was going to like programmatically ma make a recommendation uh maybe I should write an oped about this um for campaigns this year it is get a handle on the overall conversation right what what are the messages your audiences are hearing that’s in addition to and inclusive of your paid media and your polling polling tells you what audiences are thinking, what they’re feeling maybe. Um, paid media metrics of like how many points someone’s running or how many new ads or what was the spend last week on the red line and the blue line um tell you give you another view into your campaign. But most candidates and brands outside of the very end of campaigns um where they’re spending a ton a ton of money control the narrative about their campaign. Most narratives are driven now by and and uh most most views of narratives are driven by organic creators and user generated content.

Andrew Eldredge-Martin: Um and um uh what our perspective is is that we have to look at all of those things together and look at basically narrative competitive reporting rather than simply like spend
Josh Klemons: Yeah,
Andrew Eldredge-Martin: competitive reporting.
Josh Klemons: I mean that’s all super interesting and one thing that I took away from like something you started saying early on in that was like Cheryl was it 7 to1 right? Um and did that correlate with paid spending directly?
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Like the more that they spent the better the conversation was from other people because that would obviously be an argument that Democrat campaign Democratic campaign should start spending earlier in the cycle. Um, right now obviously most campaigns wait until the very end. And I’m a big advocate that we should be spending on meta from like day one. Like the second you’re running for office, you should just be live on meta because it’s the best possible and cheapest possible way to talk directly to your audience for like very little money. But like if that paid media is actually creating downstream, you know, consequences of people going pulling out their phones and talking about you online, that seems like you’re getting more money bang for your buck than you might realize.
Josh Klemons: And it might be worth thinking about like not wait till October to turn on your ads, but actually think about running smaller buys earlier just to like get people talking about you. I don’t know. Again, I’ll defer to you on like the findings, but that sounds like some pretty interesting potential takeaways from the
Andrew Eldredge-Martin: there.
Josh Klemons: study.
Andrew Eldredge-Martin: Yeah, I think there are going to be some really interesting takeaways from the study. Um I think um there was some really interesting work done on in the New York City Mayor’s primary last summer. Um I I I uh if I’m remembering correctly, it was something that Andy Bar had posted uh about paid Okay,
Josh Klemons: Okay. Friend of the pod. Big big
Andrew Eldredge-Martin: good.
Josh Klemons: fan,
Andrew Eldredge-Martin: uh about about uh uh you the the paid media tren spending trends uh in in in the primary.
Josh Klemons: right?
Andrew Eldredge-Martin: And I thought that the it was surprising to most that the uh uh Mandani campaign was spending so much money on linear media,

Josh Klemons: Yep.
Andrew Eldredge-Martin: right? And it was because at least from as an outside observer was because they were doing so well online, right? they knew they were reaching audiences there and they had a real dominant like um uh you know share of voice let’s say share of narrative online. I think that like retroactively looks like a really smart decision. Um and and our our numbers align with that. I think what could have been missed in the general election was that the sentiment around me in online conversations was not as one-sided,
Josh Klemons: Yeah. No,
Andrew Eldredge-Martin: right? That that 50,
Josh Klemons: it’s really interesting.
Andrew Eldredge-Martin: right? And and so if I like those are two different circumstances, same candidate, different electorate, different time period. And I I think right I don’t think there’s a one-sizefits-all kind of paid media recommendation. There are scenarios and there are situations that are vastly vastly different. Um you know Senate primaries being a really interesting uh uh you know this year, right?
Josh Klemons: Yeah,

Andrew Eldredge-Martin: uh Democratic primaries,
Josh Klemons: for sure.
Andrew Eldredge-Martin: I suspect, are a really fascinating area for um candidates and interested parties to try to understand that dynamic because I bet there’s some disparities that people don’t want to get uh caught sleeping
Josh Klemons: Yeah,
Andrew Eldredge-Martin: on.
Josh Klemons: I mean Maine and Michigan are two places where I’m sure we could like learn a lot about what the public chatter, if you want to call it that, or whatever you want to call it, public conversation, how that correlates with the end results because I think there’s a few candidates that quite obviously like probably don’t even have I I would guess like less positive but also less negative because people are just not talking about them as much who might I don’t know. I’ll be very curious to see some of those results and if you wind up doing any studies on like what the conversation around them
Andrew Eldredge-Martin: Yeah.
Josh Klemons: was that and how it correlated to their wins or losses. Um I think that could be extremely interesting.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: You only look at YouTube.

Josh Klemons: Is that correct?
Andrew Eldredge-Martin: Um we are have developed primarily on YouTube initially. Uh but we will not stay that way forever. Stay tuned for more.
Josh Klemons: Is is that just because the tech was easier to plug into or that’s just where you think the most important conversations are happening?
Andrew Eldredge-Martin: We felt like YouTube was the most interesting platform that didn’t have this type of um insight. Um and as someone who with an advertising background, I also realized that there weren’t great options for targeting on YouTube for a lot of folks. And so we were really interested in one developing better insights and data, but also making it actionable for people um because you know like on meta you can do a ton of targeting um and there’s a lot of flexibility. You don’t have all the same uh options on
Josh Klemons: Yeah. Interesting.
Andrew Eldredge-Martin: YouTube.
Josh Klemons: Uh during the 2024 campaign, uh one of the many things I did along with working 30 plus races was I worked with Courier on the FYP newsletter which was focused on the Tik Tok channels of Biden and then Harris and wells Trump and we saw all kinds of red flags that we were raising every week that like you know Harris was Biden then Harris was dominating Tik Tok and then we watched the Trump campaign sort of like wake up to what they were doing and replicated in like this disgusting

Josh Klemons: backwards you know evil racist way. Um, but like you know, and surpassed the Harris campaign as far as like raw metrics. So like I absolutely believe that those numbers, like do I think that if the Harris campaign had stayed ahead of the Trump campaign, she would have won the 2024 election? No. Do I think that there were warning signs that like the party maybe wasn’t like listening to loudly enough? I mean, that’s what we wrote a newsletter about every week for the last six months of the campaign and you know, um, so yeah. No, I I’m very interested in like hearing a YouTube u which I mean traditionally YouTube is a place for media and conversation but most campaigns aren’t even on YouTube like most campaigns they might be throwing their like launch video on there like you know some of their paid media stuff on there. Do you think that campaign should be spending more time on YouTube shorts and whatnot or is this much more about the public conversation than the campaign’s conversation?
Andrew Eldredge-Martin: you YouTube is the largest video streaming platform.

Andrew Eldredge-Martin: It’s the largest connected TV platform. It’s the largest podcasting platform. And it’s the largest short form video platform and in the in the United
Josh Klemons: So yes,
Andrew Eldredge-Martin: States. And it’s also the media company that people are spending more time
Josh Klemons: right.
Andrew Eldredge-Martin: with on their televisions at home than anyone else. depending on the month it is 40 to 60% larger than Netflix in terms of time spent
Josh Klemons: Wild. That’s crazy.
Andrew Eldredge-Martin: watching on the television according to Neielson if people are not at on YouTube um aggressively they’re missing massive opportunities the real challenge with YouTube is that it is so big that people uh really run the risk of like not spending enough and kind of basically not reaching the right audience with enough spec specificity.
Josh Klemons: I don’t need you to write a playbook,
Andrew Eldredge-Martin: Um,
Josh Klemons: but like for the campaign listening or the strategist or the candidate, like they’re on YouTube, they’ve posted nothing but their launch video.
Andrew Eldredge-Martin: yeah.
Josh Klemons: Like, is this they should be spending time on shorts, repurposing their reels and their Tik Toks into shorts, or are you talking about like actually investing in building like a studio so that they can like look good enough to like spend time on people’s TV?

Josh Klemons: Because obviously I and I don’t know the numbers,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: but my understanding and my experience is like people don’t really watch shorts on TV, right? They’re watching long form content, but not shorts.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Um, is there like what’s your advice for somebody who’s like,
Andrew Eldredge-Martin: Right.
Josh Klemons: “Okay, you sold me. I should be on YouTube. Now
Andrew Eldredge-Martin: Um I I think I think it depends a little bit as to what your what your goals are.
Josh Klemons: what?
Andrew Eldredge-Martin: If you’re in the phase of the campaign where you’re looking to build uh a base of support, organize supporters, raise money, build your CRM for your direct marketing campaign that is going to last a year. Um I think there are definitely paid media opportunities that you will want to go to first. Um if you’re looking to run a persuasion campaign and a long-term like like outreach campaign, you have to have YouTube as part of your mix. Now there are also versions of that story that include YouTube right away as well.

Andrew Eldredge-Martin: Um sometimes it is actually very very good as an acquisition and a uh direct a direct donate um opportunity. When I was running the digital paid media uh campaign for Bernie Sanders in 2020 in his presidential campaign, we um we found that YouTube was one of our largest and most consistent um uh sources of acquisition uh of supporters um week in and week out. It was just it was just really it’s got scale and the targeting really worked well for uh for us.
Josh Klemons: Interesting. Okay. Uh, yeah, I know both YouTube and Meta have gotten harder to target on since 2020.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Um, but still that’s like that’s wild to think that YouTube was outperforming Meta back then.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: Um
Andrew Eldredge-Martin: Well, it wasn’t that it was outperforming meta necessarily.
Josh Klemons: really
Andrew Eldredge-Martin: It was more that like meta was a real opportunity in moments and you could scale really quickly but you you would have to kind of go up and come down whereas YouTube was just it just turned like it was just a machine.

Josh Klemons: and that was that was all paid or that was organic or a combination?
Andrew Eldredge-Martin: Um uh I was running the paid campaign.
Josh Klemons: Got it.
Andrew Eldredge-Martin: Um I sus I I I don’t I don’t I didn’t uh I don’t have all those stats on the
Josh Klemons: Yeah. Yeah. Cool. No,
Andrew Eldredge-Martin: or
Josh Klemons: that’s that’s really interesting. Um, okay. So, uh, anything next for you in Ground Truth AI that you want to share?
Andrew Eldredge-Martin: Um we will be releasing uh a subscription product uh in the next uh month or so. Uh so stay tuned to that. Um uh basically it gets at the idea of um
Josh Klemons: Cool.
Andrew Eldredge-Martin: you know tracking narratives um across uh paid and organic media. um uh using the clustering
Josh Klemons: Excited to see it.
Andrew Eldredge-Martin: machine.
Josh Klemons: Um, how can folks stay in touch with you and make sure they know when your new model rolls out and all that fun stuff?
Andrew Eldredge-Martin: Check out our uh website at clarifyintelligence.com.

Josh Klemons: Okay. And uh, can they find you on social anywhere? That’s not a
Andrew Eldredge-Martin: I am most active on LinkedIn um and have largely gotten off the
Josh Klemons: thing.
Andrew Eldredge-Martin: other socials. uh myself personally.
Josh Klemons: Good for you.
Andrew Eldredge-Martin: Uh uh but uh
Josh Klemons: I’ll link to the site and to your LinkedIn and then um yeah.
Andrew Eldredge-Martin: um
Josh Klemons: Cool. No, this was super interesting. Like I said, like um I am not a like data analyst, but I did spend a session uh you know, a campaign like playing one with uh Courier and I learned a ton. And so like when I saw this,
Andrew Eldredge-Martin: Sure.
Josh Klemons: it was just like a really interesting way to how people are talking about a conversation is the conversation. And I think that too many of us are just like, “Okay, we’ve got to put out our message.” But it’s like if you’re not getting people to join you in sharing that message, it’s pretty irrelevant what you’re trying to say.

Andrew Eldredge-Martin: Yeah.
Josh Klemons: And like the world is so chaotic and so noisy and it’s our job to make sure that we’re not talking by ourselves into a
Andrew Eldredge-Martin: Yeah.
Josh Klemons: a void,
Andrew Eldredge-Martin: Yeah.
Josh Klemons: but instead like giving people the tools and the resources they need to like join us in the conversation. And ICE obviously is a very organic one where like the entire city of Minneapolis now has an tragic opportunity to become storytellers in like a way that they should never have to be.
Andrew Eldredge-Martin: totally.
Josh Klemons: But like it can’t be limited to just like these kind of horror stories.
Andrew Eldredge-Martin: Yeah.
Josh Klemons: It also has to be about the good stuff and the other bad stuff and you know everything in between. So it’s really interesting.

 

February 5, 2026/0 Comments/by Josh Klemons
https://joshklemons.com/wp-content/uploads/2026/02/87-1.jpg 1154 1063 Josh Klemons https://joshklemons.com/wp-content/uploads/2023/05/Reverbal-Communications-Josh-Klemons.svg Josh Klemons2026-02-05 10:46:222026-02-13 10:20:07One Media Company is Carrying ICE’s Public Image Almost Entirely on its Shoulders with Drew Eldredge-Martin | Hello Merge Tag Ep. 48
Digital Ads, Digital Tools, Hello Merge Tag, Politics

Rethinking Personalization in Digital Ads with Maya Hutchinson of BattlegroundAI | Hello Merge Tag Ep. 39

Maya Hutchinson battlegroundai using ai to build digital ads

“We do not need to run the same ad to everyone. It’s 2025 — we don’t need to do that.”

Maya Hutchinson is a data-driven marketer with roots in Democratic politics. She started her career on the digital team of President Obama’s re-election campaign and has continued to work at the intersection of tech and politics ever since.

She helped build the European market for NationBuilder, the first community organizing software supporting candidates, parties and campaigns across the EU. She then helped launch the analytics, polling and paid advertising division of DKC, one of the largest independently owned PR and comms agencies in the US.

She’s worked with brand like Uber, Honest Company, Health Ade and OpenTable and political campaigns like Bloomberg for President, the DNCC and Amy McGrath’s Senate race.

She’s the founder and CEO of BattlegroundAI, a platform built to help progressive agencies, non-profits and political campaigns create high-impact, platform-ready digital ads.

She joined us on the pod to talk personalization in digital ads.

Throughout our conversation, we spoke about the role of AI in supporting the people doing the work, why you should be A/B testing everything, how her toolkit works and a whole lot more.

Listen to the full episode right here, or wherever you stream podcasts.

 

If you prefer video, you can also watch our full conversation:

Find all episodes at HelloMergeTag.com or wherever you stream podcasts.

 

Links

Website | Email | LinkedIn

 

Big thanks to our sponsors:

Civic Shout. Learn more about the great work they’re doing to help Democratic campaigns and progressive nonprofits build their lists ethically at civicshout.com/partners.

Campaign Deputy. Built by progressives, for progressives, their platform gives campaigns and organizations the tools to achieve their fundraising goals. Learn more at campaigndeputy.com.

 

Episode Transcript

This transcript was automatically generated and has not been copy-edited. While it can serve as a helpful guide to our conversation, it may contain errors or omissions. For the most accurate representation, we recommend listening to (or watching) the full episode.

Josh Klemons: Maya Hutchinson is a data-driven marketer with roots in Democratic politics. She started her career on the digital team of President Obama’s re-election campaign as and has continued to work at the intersection of tech and politics ever since. She helped build the European Market for Nation Builder, the first community organizing software supporting candidates, parties, and campaigns across the EU. She then helped launch the analytics polling and paid advertising division of DKC, one of the largest independentlyowned PR and comms agencies in the US. Uh she worked with brands like Uber, Honest Company, Health Aid, and Open Table and political campaigns like Bloomberg for president, the DNCC and Amy McGrath Senate race uh before going on to found and become the CEO of Battleground AI, a platform built to help progressive agencies, nonprofits, and political campaigns create high impact platform ready digital ads.

Josh Klemons: So Maya, thank you so much for uh coming on the pod today to talk about your work. Uh why don’t you start by just walking us through what y’all do? Like what does Battleground AI do and how does it all work? I saw the site. I I understand the concept, but uh from your perspective, how do you how would you describe it to someone who’s not familiar
maya hutchinson: Yeah. Well, thank you Josh for having me. This is exciting. It’s great to talk to you. And yeah, let’s dive right in. Uh so Battleground AI was it was built uh because we were trying to really solve a problem that I saw over and over again working in this space for over a decade um which was really trying to create smarter digital content um that’s tied to data uh that is fast that is simple for people to use um so that you can move from information to ad ready assets seamlessly and quickly. Um, you know, the biggest part of advertising is the content.

maya hutchinson: Uh, 70% of the performance is dependent on on what you’re showing and telling people. Um, so we spent a lot of time on on targeting and there’s a lot of other elements to advertising. Um, but really we saw the biggest pain point um as content generation. Um, and really making that smart. Um, and that’s what we’re aiming to do. We were especially in a space that is has more regulations um is is harder to advertise. There’s much more restrictions in the political space and that is really um the the industry in the market that we’re we want to help. Um we know that there’s a big need for folks especially um now that there are more platforms all the time, more placements, higher demand and we need to move faster. Uh and we want to help folks do that. Um, and so that’s why we we launched the tool last year and we’ve continued to develop it. Um, starting with with text um, and we just launched our image generation um, capabilities. Uh, we have a lot more planned um, and and so we’re excited uh, to to be doing that as we head into to 2026.

Josh Klemons: So your big focus is that you like a campaign comes in, gives you a message, and you’re you essentially built an AI tool that then takes that message and turns it into dozens if not hundreds of versions of copy that you can then test online. Is that my understanding correctly?
maya hutchinson: Yeah. So, we’re a self-service platform. Um, we’re here to help you, but folks can create an account. Um, you want to define those parameters. So, it’s really based on information. You can start with with nothing, but it’s great if you say you did a poll. Um, and you you know, the the first use case of the the product was actually on a schoolboard race. We had done a poll uh I was managing the the paid advertising and it was like how can we take the information um and research that we have uh and turn that into search copy, Facebook copy um how can we use that in in short scripts? How can we take information and turn it into ads and messages that people um are telling us that they care about those topics um and fine-tune those to those specific audiences?

maya hutchinson: really something that you can do very manually, very slowly. It takes a lot of time. Often times we might have that data and then we we hand off that poll to our creative team and then they’re like, “What am I supposed to do with this?” Like, “Thank you for all of these cross tabs.” Um, and so, uh, the goal, um, is really to take that and then turn that into, um, personalized content and messaging to meet those audiences where they are. Um, so much of the time we’re thinking about ads as um, you know, we’re making them from our perspective, right? And our backgrounds and all of us come in with a lot of different biases. And that’s okay for many different, you know, you’re creating a website maybe or organic social content. But with ads, you really are talking to a very specific set of people and you want to make sure that the information that you have in there is personalized and specific to that group. Um, and so the more and more we can do that, uh, there was some research actually a few years ago around uh, perception of ads and and people over 70% of people are expecting that ad to be very personalized to them.

maya hutchinson: And we can do that much more effectively now. And especially when it comes to political advertising, how can we get these issues to really deeply resonate with our specific audiences?
Josh Klemons: define personalization here because like with a meta ad you can get you can get specific by age, gender, location but like there’s less and less you can do with targeting. So I guess I’m curious two front like are you seeing a that folks are like buying data from L2 target smart somebody like that to be able to get more microtargeted or are you talking about building ads that are just like age and gender based like what do you mean when you say that I
maya hutchinson: Yeah. So, you can start with um just, you know, start with it is a sliding scale, right? So, if you’re a small campaign um or a small organization and you’re launching a campaign, most of the time folks will just, you know, we’re creating one ad. We’re running this to everybody. Um start by Yeah, exactly. breaking that out by um issue specific.

maya hutchinson: So, um maybe you have three or four different issues. um you customize each of those messages to each of your target audiences. And yeah, you can do that based it it varies a little bit based on the platform, right? Um because you always really want to think about how you’re crafting these to every individual platform and also individual audiences. Um and so based on your targeting, but yeah, start with um those demographic information. Um start with interests and behaviors. Uh there’s a lot that we can do in terms of you know we we don’t just need to focus on voter data although it’s very important. There’s a whole host of other information about people um that is important uh that we can think about how do we craft these um to placements of where they are um to time to to insights interests um yeah all the demographic information start to really think about how we can personalize those um and then personalize the messaging um different variations you can make you know hundreds of of copy variations you should have many many more visual variations than we could ever think possible.

maya hutchinson: Um so that then you can really start to see what’s resonating with people. Um one message, one one one asset does not um does not speak to everybody. Uh we we just can’t market like that anymore. Um and so the more and more personalized you can get and the faster you can do that uh the the more strategic advantage your campaign’s going to have.
Josh Klemons: Yeah. So, I’m curious about that. Um, so I’m I love AB testing. Um, I’m a huge huge advocate that if you’re not AB testing, you’re just throwing money away. I mean what are you even doing when it come especially when it comes to like meta ads more than anything but really all the platforms but um hundreds of versions is like I mean for a small down ballot
maya hutchinson: Yeah.
Josh Klemons: campaign like you can’t really a like you literally can’t AB test that many ads at once anymore like Meta actually has caps on it. So like how I guess what I’m asking is like if you pump out 200 versions of the ad how are you seeing down ballot races and smaller organizations like what do they do with all that information?

Josh Klemons: like that feels like overwhelming in a whole new way. So, how how are you recommending folks approach that output? Yes, you went from like an overwhelming poll to now you’ve got like messaging, but that messaging is like a whole new problem to like sift through. So, how do how do you recommend like a small down ballot race handles that?
maya hutchinson: Yeah. So, let’s emphasize there’s a sliding scale.
Josh Klemons: Okay.
maya hutchinson: um for for folks that potentially like lots of lots of local races who who never run an ad at all, right? So, it’s like they never ran ads, we need to start doing that. Um the smallest races need to be able to do that. Um and that could be a couple variations. That doesn’t mean you need hundreds for for just a small race. Um but but one of the large case studies um that we did last cycle um or one of our consultants conducted last cycle uh was looking at about it was about 400 ads across three states um and you know hundred of different candidates um and really being able and this was from an IE um but really being able to increase that personalization both for um the candidate candidates, the location, um the audience that they were talking to.

maya hutchinson: Being able to create many more variations of that ad, um so that they weren’t going to just run. Okay, these are just, you know, Virginia, uh North Carolina, Michigan ads. That’s it. Like they’re just by the state. No, like we can do a lot more now. Um yes, that meant more variations and that meant a little bit. Right now, you know, still there’s like a manual component of launching those. Um, but I think we can we’re we’re going to easily be able to move past the manual element of that, too. Being able to rapidly set up those campaigns, always making sure that humans are are very clearly reviewing and in the loop on that. But you can start to automate a lot more of that flow. Um, AI is a important element in the analysis and creation, but it’s also making development um much faster. It’s making connections and API integrations a little bit more seamless. Um things are being able to talk to each other a lot more um than they were before.

maya hutchinson: And this is a great advantage especially if you’re working in ads um because there is a lot of manual um work in the space and it’s rote right. We’re doing the same thing over and over which is why um this new technology is really uh a perfect application for the sector.
Josh Klemons: And so are you talking about actually building ads through your platform? Because I I thought it was more about content creation, but you’re actually turning around and like placing ads for folks. Like walk us through that.
maya hutchinson: So um that a few integrations are are in the works. Um well I just haven’t really publicly shared but yeah we will have we have an API um just some breaking news breaking yeah first to know um yeah we’re we built an API um so that not only um
Josh Klemons: Is this a breaking? No, I’m just kidding. Okay, we got a scoop here.
maya hutchinson: one folks who are already have ad platforms um can integrate our our technology directly in there so that they can you know you’re already placing an ad so why not be able to um intelligently create some content um uh quickly for that seamlessly in that process.

maya hutchinson: Um, and then on the other hand, excuse me, while we’re generating the plat the content on the platform, we are, you know, we’re focused on on advertising. And so the more integrated our platform can be with where people are placing those ads and being able to really um have a full life cycle of um of connection between the content that you generate uh being able to run that as an ad and then pull that data back in to inform your creative moving forward. like that full life cycle is really what our goal is in in constructing the platform. A very deeply intelligent um system so that you aren’t just guessing. You know, you see a a report, you’re running a bunch of ads, uh you see a report, oh these are really high performing ads. Well, I should make something like similar. I probably should make more um in this vein for this type of folks. like we can also actually start to do that in a smarter way um by integrating that system. Um and so that’s really our our goal um down the line is to have much more integration with those advertising platforms.

maya hutchinson: So, if you’re sending content from our image generation platform to a DSP um or you’re sending um a YouTube ad or search ad or your meta ads um that you can do that from in the platform
Josh Klemons: Interesting. Yeah, I didn’t see that on your site. It sounds like you haven’t announced it yet. So exciting. And um I also didn’t see image generation. I mean, I saw like the textbased um images, but are you doing more than that? Are you starting like So explain what I saw on the site and then what y’all are working on with the image generation because that’s obviously a big difference.
maya hutchinson: Yeah. Yeah. Totally. So, we launched Programmagic, I guess it was a couple weeks ago or almost a month now. Um, and really with with two big goals, which is like we want to be able to um leverage this new technology in a very clear, applicable way for our sector um and make that fast and easy to see that the results, right?

maya hutchinson: this isn’t just like we do not have free form chat on our platform. We are not a chatbased tool. Um I actually I think that ends up being a lot more of a waste of time for people and and so um we are really trying to create a structured process for folks when it comes to messaging when it comes to text to image generation. So yeah, right now if you use programmatic, the outputs are all um instantly sized for uh programmatic and display and social sizes as well are in there. Um so you get seven sized assets instantly. Um and they are uh text and and various um colorbased results. So we really want to make sure that as we develop the product, it’s in line with the evolution of the underlying large language models as well. Um when we first launched images were barely functional. Now they are getting much better and that ability to start to integrate very um you know intentionally uh and consistent outputs um on more and more image generation.

maya hutchinson: So that’s V1 that we just launched. Folks can try that out for free.
Josh Klemons: so that’s what I saw at programmatic is like the one.
maya hutchinson: It’s Yeah.
Josh Klemons: Okay.
maya hutchinson: And then so that’s a V1. Um and then we’ll be continuing to roll out improvements to that. those will be in our sort of the internal tool. Um you’ll continue to be able to um generate and pull in um more visual assets um saving templates um being able to generate much more elevated um asset creation um and also more personalized as that is then integrated into our underlying platform. Um so images uh and then you know as that evolves right the biggest thing everyone came back with immediately was video um right you know this isn’t as easy as as selling a a product right we this takes a lot more to make sure that we can create and help folks in our space get to you know 80% right we can help you get something quicker, faster, more personalized, and then you can take it and and you can continue to modify it.

maya hutchinson: Um, we’ve seen that in our own research, uh, that predominantly the content that performs the best, I don’t think to anyone’s surprise, is when it is the human and the AI combined working together. Um, that is where that sweet spot is. So, our goal is really to help folks get there.
Josh Klemons: And that was a study done by Miles Bugby. Yeah. Um he’s a he’s a friend of the pod and yeah I saw that like so his takeaway was that um uh he said that AI generated ad copy edited by humans perform the best compared to just human generated
maya hutchinson: Yeah, that was a that and that was a 400 ad. Yeah.
Josh Klemons: or AI generated. Was that a fair is that the correct takeaway from his uh study?
maya hutchinson: Yeah. And I think we’ve seen that in a number of of research studies um you know in different sectors too. I think AI can get you more ideas. It can get you more variations, but everything needs a human lens.

maya hutchinson: Um, you that you know the the creativity, the ingenuity of humans is not what AI is supposed to be doing. Like it can it has an endless energy capacity and it can start to generate lots of iterations for you which which help you get you know that that idea. Um, which is why in our platform on the copy side and and certainly um in other elements moving forward like you can make those edits, right? In chat GBT, you’re not going to go in and edit your responses, right? But in our platform, you can um you know, it’s meant to be uh that that connection between the two the two worlds.
Josh Klemons: Okay. And I didn’t see within programmatic like can you can you like upload your brand bible so it’s using your fonts and your hex codes or uh it’s more just standardized
maya hutchinson: Yeah. So, in the public facing like programmatagic. Battleground.ai, you can customize your hex codes. You can upload an asset um or like a logo um as well. So, you can and and adjust your font type.

maya hutchinson: um in the you know when it’s in our platform um you’ll be able to just much more further customize that save assets um and manage that from a a much more personalized um standpoint. But we really wanted to get um the first version out to as many folks as possible. Um start to get feedback exactly like that like we need to save our brand assets, we need to make these edits. Um but that we wanted to get folks to really see um what is possible um that we also don’t need to be afraid of using this new technology especially in the political spa space. We need to be able to craft it to work for us. Um nobody is going to do that except for the people in our space right like nobody else is going to try to make AI work for for political or um you know nonprofit organizations. We have to be the ones that are are pushing that forward and making sure that that it does work, that we can use it effectively um and safely and and have guard rails on it.

Josh Klemons: So like obviously this is data driven first like you talked about like you’re a data driven person. So, are you finding are there themes, are there terms, are there ideas that are resonating that you see working across like everybody’s ads right now like collectively that we could all be learning from or is it really um individualized so much so that there’s like it’s hard to to identify trends based like you have a very interesting perspective into a lot of ad programs. I run a ton of ad programs and I kind of know what works like within my clients. Um but and I you know I I spend time in the ads manager. I see what’s working for other folks but like you have a very different angle. you’re involved. You know, you’ve built a tool that’s helping folks actually develop things. So, I’m curious if you’ve got like any interesting insights worth uh worth that we should all be learning from.
maya hutchinson: I think my biggest one is that people should be running more ads in they should be consistently running them um even if they’re at lower spend levels.

Josh Klemons: Okay.
maya hutchinson: Like I think the biggest thing um especially in the political space is like people need to see you all the time like seven times at least a week um I think is the most recent uh research but like you know of course that you know depending on the source but you need to kind of be always on um which means you you constantly need to have iterations and and fresh versions of content. Um, and so I think the folks who are uh doing that in a really thoughtful way, like they’re, hey, we don’t need to spend a ton of money all the time, but we need to have something always on for folks and we need to keep it very relevant. Um, I think where I’ve started to see a lot of opportunity, um, is is this content that’s hyper relevant. Um, you know, I think especially in our space, we do a lot of like monitoring of the news, right? We’re we’re always like paying attention to or getting, you know, uh, reports every day of like here are the new headlines, but like that that’s great in an email format, but like can we keep our content as relevant to the people we’re talking to as possible?

maya hutchinson: Um, I think when we can do when folks are doing that, um, they’re not just letting something run and run and run. um they’re thinking and especially in this this climate like something is happening all the time and so it doesn’t mean it everything but like think about all those points that are coming out um that you can make fresh and relevant content around um and we can do that a lot quicker and a lot more intelligently now um with AI that you’re really um not even just it’s not even just personalization it’s like um relevant like constant relevancy to your audience. Um I think that’s really where I see opportunity and I see um folks starting to think in that way.
Josh Klemons: Uh I recently gave a session at Netroots. I I did one at Netroots, but I also did a virtual session before Netroots about um how we’re think about we’re thinking about meta ads wrong.
maya hutchinson: Amazing.
Josh Klemons: And it was essentially like me taking a blog post I wrote several years ago and developing it into a session um three rules for downbell candidates specifically around meta ads.

Josh Klemons: And my three rules are start early, test a ton of content, and don’t make yourself the hero of the story, make your audience the hero of the story. And I saw your blog post, which is how like I I reached out based on your blog post, three critical ways to improve digital ad performance. You had different take like different rules, but like similar sort of concept and some overlap. Uh yours were frequency, personalization, and keeping ads fresh, which again, not exactly the same as my three, but like definitely overlap a lot. So, you just sort of walked us through it, but like for me, a lot of it is about like I want my ads my ads quote unquote like because it’s hard to even call them that the way I’m running them. Like I’m doing one giant AB test for months pro like yes there might be fundraising. Yes, there might be lead acquisition but for me I just want to raise the hell out of somebody’s name ID and I have won numerous elections doing that. like, you know, like I’ve seen massive success doing this.

Josh Klemons: Just making sure that by the time that person knocks on their door or shows up to that like event, they’re already like know you well. Um, and a lot of that is like very personalized in the sense that it’s the campaign responding to the real world and then adding that in on the back end to like creating an AB tested um campaign budget optimized account. You’re saying that they should like just be like putting tens or dozens or hundreds of things in at once uh and seeing what happens. Like walk me through what you mean when you say um walk us through your basic premise, frequency, personalization, and keeping ads fresh. Like uh you’ve sort of already walked it through it, but give us the give us the high level again.
maya hutchinson: Yeah, maybe we should write a joint blog post because I feel like it’s actually four or five elements because I think yeah, I would also say like early um which should probably also be the first one there to
Josh Klemons: Yeah, I’d be interested in that. Yeah.
maya hutchinson: your point like start as early as humanly possible with your
Josh Klemons: Do folks push back on that? Because I get like funny looks when I tell folks like somebody brings me on to do digital for them. I’m like great, let’s get your ads manager up and running. And they’re like now? I’m like yeah, doesn’t matter when. Like I don’t care if your election’s in 3 weeks or a year. Like you should be running meta ads at a low level because it’s the cheapest and most effective way to raise your name ID in your district and to stay relevant to your audience. And I am like I am amazed how often I have to like push that because yeah, so few people like sort of they that’s not how people think about ads in general in our party. Republicans are much better at it. Democrats like to wait until the end and put all of their money into, you know, persuasion ads in the final three weeks.
maya hutchinson: Josh, you literally like I should just have that clip and and play it over and over for people.

Josh Klemons: It It’ll be live on YouTube.
maya hutchinson: Um uh yeah, I’ll just play it over and over to myself to to users.
Josh Klemons: You can use it as you see fit.
maya hutchinson: Yeah, I mean I I I’ll dive into to the other points too, but I really can’t emphasize that enough. It’s not and and it it’s the same with a lot of other sectors too because having worked across many different industries like folks it’s it’s not even yes because we don’t have a hard deadline when you’re selling products but like same thing people are like I want to run these ads so someone buys this thing and I want to run this ad so someone votes for me and you’re like okay but that has to start like a year plus you know no one’s going to buy your product no one’s going to vote for you if they don’t know about you they haven’t heard your name before. People forget so fast. Content moves so quickly. You not only need to be early, but I think to the point of frequency, um, you need to be appearing for people over and over and over.

maya hutchinson: Like one time is never going to be enough. And these your audiences for most of these races, like it is not a huge amount of people, right? If we’re talking a local race, even a congressional race, like it is not a massive amount of people you talk to. You talk to them over and over and over again and you need to meet them on platforms where they are. You need to be on meta. Like I know a lot of people are like the ad manager is hard. It’s annoying. The verification it’s like we will there’s a blog post on our site Josh will help you like Miles will help you like we can help you do that.
Josh Klemons: True. Exactly.
maya hutchinson: Um you need to be there and I think that to that point is like yeah same goes for like different podcasts or news outlets like you need to be and show up where people are. You need to be on YouTube. and those are lowlevel um we we worked with a a small state ledge race last cycle and uh they didn’t have a lot of budget um but we were able to get them up on on meta on YouTube

Josh Klemons: Sure.
maya hutchinson: on search um I know searches falling off in places of chat GBT but like you still need to be there um voters are going to Google who you are like show up be in search it’s so cheap anyone can do it. You don’t have to have raise any funds to to run some search ads. Um so so that’s what I mean I think with yeah frequency and and showing up consistently over and over multiple platforms as many as you think you know realistically can manage far out. Um, but those three are and then yeah, be on news sites, be on local display is is a a very costefficient platform. Like show up on those local sites, show up on news that people are reading on mobile. Um, you just you’ve got to be there. It’s the same with, you know, trying to get candidates to be on Instagram and Tik Tok. Like the ads need to be on the places. Obviously, I wish we could run Tic Tac Tik Tok ads, but you know, uh yeah, we could talk about the restrictions on our time.

Josh Klemons: Maybe when MAGA owns it, they’ll let us do, you know, political ads.
maya hutchinson: Um yeah, yeah, yeah, yeah.
Josh Klemons: Just like Twitter, you know, the worst person in the world bought it, but now we get to run political ads. I don’t, but we can if we want to. It’s no longer valuable, but whatever.
maya hutchinson: I I have I have started getting some Dems running some running some some Twitter X ads. Uh I I that’s the thing. It’s like you don’t don’t handic or like handcuff yourself before um before you you even like get out of the gate. Don’t write off different platforms um and be like, “Oh, I’m not going to do that.” Like, we still need to to reach people. Um we still need to talk to people um even if you don’t like the platform yourself. Uh and and so I think that um yeah um personalization I think to your point earlier like it doesn’t have to be crazy overwhelming. You don’t have to run 400 ads. Like Miles is an incredible um uh digital advertising strategist.

maya hutchinson: Like not every campaign is going to be like that. Um you can start with with some personalization just just small personalization. um you know in a way that’s like hey I want to talk to to probably um this group um you know older folks more specifically about about Medicare um and my plan for Medicare like think think just small like what’s a way that like I can make these messages more personalized for different audiences um and it could be you know one or two groups and and start with just like some um some low-level personalizations like it doesn’t have to be crazy overwhelming Um I think if you have a bigger um you know budget and you and you have you know a lot uh more ambitious goals too we can you can scale um you can start to really like expand that personalization level um expand it across platforms and and across audience segments but it doesn’t have to start like that. Um but I think any level of personalization like we do not need to run the same ad to everyone.

maya hutchinson: this is it is 2025. Like we don’t need to do that. Um we we don’t need to make the same type of ad. Like I think that’s also on the personalization front like we do not need to make one big campaign ad and have it always look exactly the same and have it be the thing that everyone’s like, “Oh, I already know this is a political ad.” Like from the way it opens. It’s like no, your your content should match the platform. It should match the way people are consuming content on that platform. Like that’s how you should think about it. Um, if I’m seeing this this ad on Instagram, it should look like something I would see on Instagram. Um, I think we need to to get into get out of the like we made one ad for TV and now we just need to mash it up into a bunch of different places. like we got that also that needs to stop on the personalization front. So personalization is a big bucket I think.
maya hutchinson: Um
Josh Klemons: Yeah, I always say like if you have a TV ad, great. Let’s put on social, but that is not what I want for social. What I want is something that looked like it was made by somebody’s friend because that’s what people will actually stop and watch on social. And yes, the viral moments, like those viral videos, like of course, thank goodness for like big launch viral moments, but like that doesn’t sustain a campaign for a year. Like now you got to pull out your phone and just walk and talk or you know sit in your desk chair and talk you know and like you know like introduce yourself to people in a way that looks
maya hutchinson: Yeah.
Josh Klemons: like it’s from their friends. I do a lot of Tik Tok work and the more produced my videos are the less they perform. It’s so frustrating and such a gift because I can make a Tik Tok video every day without having to be like you know it takes me five minutes to make a Tik Tok video that like does great and then I like will spend hours like working on one and it like bombs.

Josh Klemons: Like it bombs. It’s like hilarious to me. Every time I spend time on something, it bombs.
maya hutchinson: Nice.
Josh Klemons: Like Tik Tok hates it. Instagram reals hates it. Like people just want things that feel like they’re friends.
maya hutchinson: Yeah, they want things that feel like other content that they’re consuming. And so, you know, if you’re a consistent watcher of YouTube, like their ads look a certain way, they’re those moments where they don’t have ads and it’s just, you know, blue sky and an ocean or whatever. um you know there’s there’s ways that those platforms are are unique in how they display and deliver ads to people and and what their content looks like. So make it fit. I think personalization yeah comes down to message it comes down to a placement. Um be thoughtful when you’re thinking about that even with small budgets like yeah don’t overlook that that this isn’t you know this doesn’t have to just be like yeah a one one sizefits-all. Um and then in terms of um just like content updating um I mean I know you know ad platforms will say this because in people are like well it’s in their own interest to like you know make sure that content new content does better right than the older content.

maya hutchinson: And the first thing, you know, if you work with someone um at Meta or at at Google, they’re like, “Well, you need to have like, you know, be updating every two weeks.” And and and you’re like, “Well, do I really need to do that?” And I would say like probably even more frequently. Um and don’t be afraid to like turn off things that don’t work and and and and to the point earlier like relevancy. Like when something is immediately relevant, run the ad for like three or four days. like if it’s just a a moment in time and you’re like I need to capitalize on this um just run it for for a little bit um and then you know go back to your your previous always on campaign but but continually like review the content um and and have sort of a couple core metrics um you know whether you’re running you we’re talking about name ID like you’re running just an awareness campaign and you’re optimizing thing pick a solid metric um for that campaign and be constantly reviewing them, constantly checking that content.

maya hutchinson: I mean, I don’t have to tell you. It’s like you’re in that ad manager like the the person managing these ads is in there like one, two, three times a day probably checking on that content or if they have a nice like dashboard to report on them. Um but you’re in there, you’re seeing what’s working. like don’t be afraid to um to update to to to turn things off to like keep that really fresh and relevant. Um I think it it is a lot of work and I AI has not you know solved all of the all of the hard parts about this. Um that really takes human like review too very very deeply. like that’s that’s important knowledge and and when you’ve worked in ads you know for a long time you you start to really understand how to to do that in a way. Um but yeah I think that that is something that um even at the smallest level uh you can start to do pretty effectively.
Josh Klemons: So, I have never run an ad on meta that was AI generated.

Josh Klemons: So, I’ve never clicked that little button that says this is an AI generated ad. Does that have an effect on performance in your experience or it’s like just an awareness and it it doesn’t help or hurt?
maya hutchinson: So, we haven’t run a ton of research with images yet, but um work with the AAPC on our AI committee and and obviously this is a big topic um uh for everybody in the space, which is like what are the impacts of an AI disclaimer? um for the most part um in the research that has been conducted to date. Um it it it doesn’t really do people don’t really pay attention to it. Um but there is obviously a fear that it will degrade performance or and somehow negatively impact that. My sort of general thesis is that pretty soon everything that you create, I mean, anything you’re developing in Figma or Canva or like there’s AI built into now almost every platform you’re using and it’s not something that you’re like turning on and off like that. That’s the underlying core creation.

maya hutchinson: Um, and so, you know, I think more and more that that doesn’t really impact how people view and and comprehend the ad, but I do think that the quality and the, you know, the output of that AI, um, that’s where it will impact it. And and I think you know for for video uh straight out of the gate AI generated video I just do not think is in a place that people for the most part people can tell like it is it is still in in a emerging um place. that doesn’t mean that we shouldn’t um continue to work with it and and see how it can be beneficial to us and and where and how we apply it. Um but it’s not there yet. And I think we can’t out of the gate just you know without any review or edits from from folks like that that quality is not good enough. um and and people will see that and and you you know um and so I I don’t think there’s a disclaimer on anything.
Josh Klemons: Mhm.

maya hutchinson: Um is and and it’s also just like I don’t even you know politics has been dealing with disclaimers to whatever you know if those help or or hurt for a long time and I think we’re going to start to have more research on that. I know the AAPC is thinking a lot about that of like creating a thoughtful research on performance and and what what impact that has and if there’s even additional disclaimers, you know, in some certain states. Um, but I think candidly that like it’s not really ever going to be a disclaimer that gets anyone to like, you know, not do, you know, not have deep fakes or do sort of like malicious things with the tools either. Disclaimers are, you know, I think they’ll they’ll probably not be relevant in in the very near term. What’s important is that you’re using the tool in a very intentional and thoughtful way and like you’re able to produce things that are accurate, are informative, are high quality, are um personalized. Uh and that’s what’s going to be important.
Josh Klemons: Um, on that note, like so Meta has their own AI tools and they push them harder and harder all the time and I can’t say no thank you enough because a lot of times they’re like missing the mark. Um although I have heard from folks like they’re testing more and more and seeing interesting results with them. So it’s like something on my radar. Um have you done tests like your AI tools against theirs or is that something that’s like in your works? Like I’d be curious to know if like Meta has their own tools built right in like where do where does that fit into sort of like your thinking on AI and ads?
maya hutchinson: Yeah. Uh I have not tested it against um any of the platforms and Google has the same thing too.
Josh Klemons: Sure.
maya hutchinson: Um I think where uh you know those are platform specific. So, um I think there’s there’s kind of three things. Um but like the first is that um while helpful to some degree um with copy variations, um Facebook doesn’t have all of your context for the data um on your audiences um your polling, your research, your talking points.
maya hutchinson: Like it has metadata. It has it has your meta data um uh which is Yeah.
Josh Klemons: Right. I got you. Yeah. Your data from a meta. Yeah.
maya hutchinson: which is which is one view, right? Um but like yeah, wouldn’t have your customer data or any of that. Um and and so it’s one view. And so yeah, I think an interesting test would definitely be to to compare them. But um our platform is is all, you know, encompasses all of those digital platforms um and your data and context. So it’s the idea is that that’s getting smarter over time. Um, and that’s applied to, you know, your entire campaign, not just one platform. Um, and so while I think, you know, we should be testing and and leveraging tools in every space to get better performance, um, additionally, you know, essentially the the core of Battleground is that, you know, all of your ads live in there. So they’re not just going to be sitting in your meta ad library or my case they’re in a thousand spreadsheets and and lots of Google drives like that content lives in battleground so that um you can start to learn and if you do start to you know you need another you have another account or another client and you just start a whole other account.
maya hutchinson: Hey what what was working? Hey, what what can I see um that I could take and and apply to to future um campaigns or how do I you know, how do I know that this is like continuing to build and grow over time? Um that’s really the powerful part of AI is like yeah, of course, some accounts you’ll have that same ad manager forever, but most of the time you don’t. Um and you want to be able to to start to get smarter. um not only with performance but like AI in general like it starts to get smarter as it knows what you’re working on what you’re creating how things are performing like that’s the goal of that sort of centralized database of ads um regardless of platform and so same with with YouTube like one off platforms are great um but the biggest thing that I and many we didn’t have is is a place where all of those live. Um, we we have to have a place that that that lives and breathes um specifically about ads.
Josh Klemons: Um, yeah.

Josh Klemons: No, super interesting. Uh, I’m curious if you have thoughts other than Battleground AI, other AI tools in the industry. Is there anyone else that you’re excited about the work they’re doing? I assume you’re keeping your eye on the AI tools out there. There’s more and more of them all the time. So, yeah. if there are any that uh you’d recommend folks check out.
maya hutchinson: Yeah. Um I mean industrywise or like I I look across Yeah.
Josh Klemons: Your choice.
maya hutchinson: I mean I look across so many different industries and I think I would encourage folks to do that too which is like look to a lot of different sectors to see what tools they’re using and what is really like moving things forward. Um whether that’s like experimenting with a tool like Lovable or Replet, like you know, you want to see how you could like fast code something. Um start to like move across different spaces.
Josh Klemons: Mhm.
maya hutchinson: Um there’s uh you know, a host of different um tools that are that are doing that.

maya hutchinson: Um uh in in our space um there’s definitely an interesting tool um uh that I’ve talked a lot with um they’re called Trollwall AI. They monitor um comments and um conversation online um for for political campaigns for nonprofits um for for any organization. Um, so they’ll, you know, are constantly monitoring your social accounts and and really, um, intelligently, um, reviewing that. Um, I think, you know, I’m always like I’m the first to always test and experiment with new tools. So, I’m like literally constantly on the lookout. Um and and I do think also um uh in terms of like a model AI models um you know change agent and the the team there who are building um sort of a a progressive AI model like that’s just a really powerful way to innovate in the space and to take you know a tool that is you know so global and and exactly to what I was talking about before like if we don’t take you know the tool and apply it to our use cases is we’re either just like letting other people have control or you know just sitting on the sidelines and being like I’m going to wait I’m just going to wait until AI is like you know it’s so good like it’s you know it’s as good as people and you’re like that is not at all what you want to do and and AI is not going to be people like

maya hutchinson: it is not people it is it is a technology that we’re building and you want to be involved with it um as much as possible in every facet. That does not mean that like a lot of things I you know especially I do are not AI but um but thinking about where it can be helpful and especially if you’re a small team like we’re a very small team um you know we have to scale content production or customer service or you know email triggers um even scheduling like how can you automate a lot of that those manual tasks and maybe that won’t be all of them but it’ll be one or two um like to free yourself up and and to accomplish a lot more um in less time. I think where we can do that.
Josh Klemons: Yeah, sure. How can folks keep in touch moving forward? The website, I assume, but like which like send folks to Yeah.
maya hutchinson: Oh, you can email me. Uh Maya, you can text me my phone number.
Josh Klemons: What’s your email?

Josh Klemons: What’s your website? What’s your uh social channels?
maya hutchinson: Um um I think my my phone number is in my email signature so you can uh uh yeah you can email me at battlegroundai.com may battlegroundi.com uh you can send me know on LinkedIn or any other platform.
Josh Klemons: You’re welcome to. I wouldn’t recommend it. Okay, right.
maya hutchinson: I’m I’m usually I try to be pretty fast in responding. Um uh yeah I I love feedback. um folks want to try the tool and and give thoughts um we are here to help and and really try to be um you know more than just a platform like we we all have worked in this space um so we want to you know support people who are are are working to innovate um especially in in advertising you don’t need anything yeah it’s a any anyone can yeah anyone can generate generate content.
Josh Klemons: and I’ll say with programmatic you don’t even need a login much less a credit card to get started. Right. Right. You just go on there and play around with the tools.

maya hutchinson: Um, you can generate up to five sets of of ads a day. Um, and and that is completely available um for folks and uh in our internal tool. We’ll have a lot more updates to program magic, but we really want folks to um experiment and see uh you know that will continue to evolve and the outputs will continue to improve just like with all of this technology um faster than than you think. Uh, and so yeah, I I encourage folks to experiment and try it and and write us and tell us what you think and what you need. Um, because I think that’s the most fun part about um, well, from our perspective and from building a tool is is really to solve um, and help people. Um, but from their perspective, I hope as we we think about the plans for next cycle, like how do we do things better? How can we help um you know scale programs or or help folks think through ways um to apply this um new technology?
Josh Klemons: I’ll have links to the site and your socials and all that fun stuff in the show notes.

Josh Klemons: Thank you so much for coming on and talking. Super super interesting. So, write the blog post.
maya hutchinson: Thanks so much Josh.

 

August 28, 2025/0 Comments/by Josh Klemons
https://joshklemons.com/wp-content/uploads/2025/08/Maya-Hutchinson-battlegroundai-using-ai-to-build-digital-ads.png 1500 1500 Josh Klemons https://joshklemons.com/wp-content/uploads/2023/05/Reverbal-Communications-Josh-Klemons.svg Josh Klemons2025-08-28 12:01:462025-08-28 12:37:52Rethinking Personalization in Digital Ads with Maya Hutchinson of BattlegroundAI | Hello Merge Tag Ep. 39
Digital Tools, Hello Merge Tag, Politics

Using AI Not Just To Speak But Also To Listen with Tareq Alani of Chorus AI | Hello Merge Tag Ep. 18

Tareq Alani chorus ai tech for progressive campaigns and nonprofits

Tareq Alani is a product leader who operates at the intersection of media, technology, and civic engagement. He is a Co-Founder at Chorus AI, where he leads product and growth.

Chorus AI was designed to transform the way nonprofits and campaigns engage with media and content creation.

Before Chorus AI, Tareq co-founded and served as the Chief Product Officer of PushBlack, the largest non-profit media company for Black Americans. While there, he spearheaded reader revenue efforts, generating more than $5M between 2017 and 2022.

He also developed PushBlack’s groundbreaking voter engagement program, which in 2020 reached 70% of Black Americans online and generated 230M peer-to-peer voting messages, making it the largest digital voter turnout program of its kind.

  • Throughout the conversation, we covered:
    How he got into the field
    Why politics can’t just be transactional
    How Chorus AI is approaching AI as a tool to help progressive campaigns and organizations do more
    How they’re building their tech in a way that’s in line with their values
    What sets them apart from the more household names in AI
    The important of social listening and how AI can help organizations get more done with less
    Other AI tools he’s excited about
    What he thinks the future looks like for AI, and tech in general
    What the media looks like in an AI driven future
    And so much more!

Find all episodes at HelloMergeTag.com or wherever you stream podcasts.

 

Links

  • Email Tareq at tareq@chorusai.co
  • Website: chorusai.co
  • LinkedIn

 

Big thanks to our sponsor Civic Shout. Learn more about how they’re helping Democratic campaigns and progressive nonprofits build their lists ethically at civicshout.com/partners.

July 12, 2024/0 Comments/by Josh Klemons
https://joshklemons.com/wp-content/uploads/2024/07/Tareq-Alani-chorus-ai-tech-for-progressive-campaigns-and-nonprofits.png 1500 1500 Josh Klemons https://joshklemons.com/wp-content/uploads/2023/05/Reverbal-Communications-Josh-Klemons.svg Josh Klemons2024-07-12 09:07:102024-07-12 09:07:53Using AI Not Just To Speak But Also To Listen with Tareq Alani of Chorus AI | Hello Merge Tag Ep. 18

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