Technology, Connected - GEO: How Google Search Became a Conversation With ChatGPT

Episode Date: June 12, 2026

Have you used Google Search recently? Exactly. Most companies, and most people, still think about Google when they think about search. They’re still spending heavily to rank there and paying for the ads around it.But more people are asking ChatGPT, Claude and Gemini what to buy, read, use or trust.SEO isn’t disappearing. It’s evolving into GEO.Awad Sayeed, co-founder and CTO of Parsnipp AI, joins Thinking on Paper to explain generative engine optimisation, or GEO, and how companies can become more visible inside ChatGPT, Claude, Gemini and other AI answer engines.Traditional SEO focuses on keywords, backlinks and rankings. GEO is more dependent on context: who the user is, what they’ve already asked, what they’re trying to achieve and how an AI system retrieves and combines information.In this episode, we discuss:How generative engine optimisation differs from SEOWhy context matters more than keywords in AI searchHow ChatGPT, Claude and Gemini use information differentlyWhat persona-based agents reveal about brand visibilityHow structured data helps AI systems understand websitesWhy comparison pages and clear product information matterWhat black-hat GEO could look likeHow AI-generated content could pollute the internetWhether brands should create separate experiences for humans and AI agentsHow advertising may develop inside AI assistantsAwad argues that GEO doesn’t replace SEO. Strong websites, useful content and clear structure still matter. But companies now need to think about whether AI systems can retrieve, interpret and recommend their information in the right context.And as this is Thinking On Paper, we ask about the human impact, the wider change in the structure of the internet, trust, data and consumerism. Please enjoy the show.--🏠 Buy us a beer on Substack🫵 Choose your own technology adventure 📺  Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on APPLE📺 Get clips and exclusive videos on Instagram --Chapters(00:00) Introduction to Generative Engine Optimization (03:36) Understanding Persona-Based Agents (06:23) The Transition from SEO to GEO(09:06) Context in LLMs and GEO(11:41) Black Hat Strategies in GEO(14:22) The Future of the Internet(16:58) Advertising in the Age of GEO(19:37) The Impact of GEO (28:22) The Evolution of AI Models (29:03) Integrating AI into Business Strategies(29:52) Agents vs. Humans(32:10) The Future of SEO and GEO(34:08) Tools for Visibility and Analytics in AI(36:00) Customer-Driven Development(39:23) The Role of Storytelling in GEO(42:04) Model Transparency and the Future of AI

Before, if you were going to spam, you would mostly just create a bunch of landing pages and that was, it was a contained sort of explosion. Versus now, as I mentioned, you know, some of the models they index very heavily on social media. So now we're not just creating a worst experience on a little quarter of the internet when you're searching for a specific term. Now you're also kind of polluting the social network experience. And now you're polluting, you know, news where you're doing. a lot of generative blog posts and things like that. So it's just such a wider space that is being affected all two, or that could be affected to all two game rankings.

Disruptors and curious minds, welcome to the show. And we are back speaking about artificial intelligence today. And many of you, most of you, I'm assuming all of you have heard of search engine optimization, SEO. Well, I've got a new one for you. GEO, Generative Engine Optimization. And today's guest, Awad Saeed, is the CTO of Parsnip, a new artificial intelligence platform, focused entirely on GEO.

Awad, welcome to the show. Thank you for thinking on paper with us today. Yeah, thanks for having me, Mark and Jeremy. It's a pleasure to be here. The pleasure is all ours. And we are going to start with the questions. You probably get asked every single day, what is generative engine optimization? Well, I'll tell you what, it's not a great acronym.

People are still debating GEO versus AEO, but ultimately it is the task of helping a brand or any topic really show up better in the results from a answer engine or a generative engine. So people might know that as the chat GPT interface or Claude, Gemini. I'm sure everyone's familiar with that. And if we look back at the history of the web until now, SEO has dominated. That is getting you ranked in Google. Now, Google historically, you get a list of a couple websites, and that's the name of the game. You put in a keyword. When you are engaging with LLMs, you're having more of a conversation.

There's a lot more context. So the practice of GEO is to help your brand be associated with these various contexts. Real world example. If I'm looking for shoes, historically I might say best shoes into Google or something like that. But with an LLM, I have either historically or am presently having a full on discussion. I am in my mid-30s. I've got some bad knees. What are the things I should be looking for?

and then and only then, with my full intent already captured, do we then have a conversation, a conversation, if you will, where we might actually have a branded recommendation. Now, that's coming from the commercial side. That is the nature of my work, but that could well be true for any topic. That's kind of the heart of GEO, if you will. Jeremy, I think you might agree with me.

Let's kick this around a bit, but it's quite related to SEO, and that's GEO. We speak about a lot of things on this show. And one of our pillars in our human index is the space industry. And we speak to a lot of people putting satellites up into Leo and geo. And geo is crowded already. We don't need another geo. So I think AEO is the way to go with this.

Well, the history on it, too, as I understand it a lot, it came out of a research kind of initiative like Georgia Tech and a few others that originally started the GEO thing. What is the A and the AEO? Is that agent? Answer engine. Answer engine. Isn't that what we're all looking for is answer engines?

I think we're all seeking that in life. Absolutely. But don't forget about your own answer engine, friends and neighbors. Absolutely. We've got one up top. Hopefully that's our discussion topic. Yeah. So that's real quick expanding on this a little bit.

And I did a little bit of research on Parsnip and kind of what you're doing. Can you explain what a persona-based agent is and maybe how you guys, how you guys use that kind of infrastructure in what you're doing at Parsnib? Do you use something called that? Yeah, absolutely. And that comes back down to my original explanation when it comes to intent. So marketers, they don't just market out into the world. They do targeting, right? Targeting based off of different personas. So in the old days of SEO, again, And like you would put in a keyword and get back a list from Google and that was it. Of course, over time, Google evolved with personalization and things of that nature.

But broadly speaking, it was relatively deterministic, relatively. You put in a term and you get that out. Now, with LLMs, the name of the game is context. Everything is based off of context. How they retrieve information is based off of context and how they even structure the retrieval process. if you will, is based off of context. And so our technology philosophy is, well, marketers think in these sorts of terms,

if we are going to show them how their brand is being represented in these answer engines, you have to give them the full representation. So you have to go out to the LLMs with the personas of their consumers to be able to actually definitively say, for your audience, this is how you actually turn up. So that's the, that's the, heart of how we're approaching it. But I think the higher-der bit there is remembering that while

there are many similarities between SEO and GEO or AEO as we like, the missing piece is the context. And a lot of people aren't really focusing on that as much. We've seen companies come out and I call it SEO Plus Plus. They just slapped a new label on the old and are just just doing analysis based off that. And we just think it's stiff. That's not the right way to do it. There's so many tracks to go down. I'm going to start with, I have done some SEO writing in the past.

What percent of my existing SEO works in the world of GEO? I would say actually pretty much all of it. There's not really any SEO best practices that will penalize you per se in GEO. And I think a lot of people aren't necessarily talking about that. Like, this is an extension of existing behavior and fundamental. So that's the good news. Your work has an up for not. So that's all good.

You have a solid base. And then where we go from there is, like I said, context is the name of the game. So instead of optimizing purely for backlinks, you want to also look at making it easier for an LLM to be able to do the retrieval it needs. So if we're talking, let's say, in commerce, right, having comparison cards, this my product versus another product, right? If you all just anecdotally, you see a lot of, it's not this, it's that when you talk to chat GPT or similar types of behaviors. So making it easier to fit into the shape of the responses that LMs are creating is a geo-specific technique you might look at. Separate page or existing page?

Like how existing page? Ideally existing page. Yeah. Because with SEO, isn't there? So you don't really want to mix the search terms to a certain degree.

And so you'd have one page which would be, and if we were talking about, so we talked about a lot about fusion on this show. So if we had Helion and they were redesigning their website, they might have one page for reactor,

one page for helium three, one page for staff, one page for current projects. Like, would that stay like that? What would they do? How would it change? Yeah. Yeah, absolutely.

So a few different things. One is you might enrich some of the content with some of the examples I've noted. Enrich, no pun intended. Right. Yeah. There you go. There you go. And then separately, part of it is also schema based.

So you might have the same page and then something that's not necessarily visible to the end user within their browser, but you might enrich that page through some schema. This is more technical. I guess we have a fairly technical audience, so you might do something like JSON-L-D, which is a standard that a lot of companies use to make the content more machine digestible, let's say, which again, that's an established technique already, but this takes it to the next level. Like this will certainly help in the context path finding. So on the schema thing, just for clarity on that is instead of relying on the bots that

that are actually crawling and searching and pulling information. This is like a direct channel to talk to the robots necessarily to say, hey, this is what I want you to know robots. So that's exactly. Yeah, exactly. And, you know, it's not a guarantee, but it definitely helps again with the context. Like the spiders. So when you publish a blog post today, you send Google comes at some point, scans the page,

puts into its mind and then dishes it up when and if someone comes across it. there's only one Google. There are many LLMs. How does that work? Yeah. And that's one of the both exciting parts about being in this space. And also, it's still an unknown, frankly, in terms of who all will be the winners. I don't think there'll be a single one.

It'll probably be more of a split sort of situation. But everyone has slightly different techniques. To your point, everyone knew Google was the name of the game, and you had to optimize for Google. And there was basically one single playbook, more or less. Now, if you look at the top players in the space, they all work under the hood in very similar ways, of course, but the primary data can vary greatly.

Chat TPT, for example, indexes quite a bit on social media type of content. Reddit, very popular for them as a data source, whereas Anthropic, much more academic focus, a bit more, let's say, rigorous in their sourcing and their data cleanup and so on and so forth. So, I mean, that's partly what we're doing is we're going out to all the players and saying, well, here's how you look to Anthropic versus Open AI versus that. And that's something for folks to consider is we're still in pretty early innings. That's a baseball reference.

Hopefully that lands. We are sport agnostic as well as tactic agnostic. We love it all. Fair enough. Well, it's still very early days, right? So you don't, you, you want to try and hitch hitch to all the wagons possible and, and, and let that play out. In order to help a brand or an entity or a company or someone understand how to interface and present themselves to these LLMs, how do you know what their tendencies are, like what these models tendencies are? Because a lot of them are not, there's not a big open book. Hey, here's how we do all of our training. Hey, here's

how we do all of our stuff. Like, how do you go about discovering that and validating that? Totally. Well, in fact, it's the opposite. There are black boxes, broadly speaking, right? So a lot of experimentation, a lot of evaluation. We are constantly testing with all of our client data against various model increments and doing evaluation before and after and then trying to, you know, draw some sort of

hypotheses. But I think that you're touching on something really important, which is not only is the space evolving, but we all actually don't know everything. It's not a solved problem by any means. And I think if anyone's listening and looking at this from a buyer perspective, just know that we don't have all the answers. We're a parsnip, you know, that's what we're saying we're discovering this as we go. We're not trying to make a quick buck here or anything like that. But from a technology perspective, it is evolving so quickly. You kind of just have to keep your ears. to the ground and move at the pace that everyone else is moving.

What's the GEO Black Hat SEO equivalent strategy? Well, you know, it's funny. A lot of companies are going down similar paths, and it's that old cliche of history rhyming. The short-term strategy right now is that I definitely don't believe in long-term is content slop, taken to the nth degree. You know, before it was you would create a thousand landing pages, let's say, for a traditional SEO type of practice. Well, now with generative content, you can create a thousand landing pages and a thousand YouTube videos and a thousand of X, Y, and Z.

And you might get a short-term blip, but knowing that this is all to game the system, I think it's fairly reasonable that the Frontier Labs would want to keep an eye out on this. And especially Google, I mean, Google's on both sides of the table here, right? They've historically that responded well when people try to game search rankings. Of course, we all know there are Black Hat tick capabilities out there. And then they also have a frontier all on themselves, right? So they're really uniquely positioned, I think. Yeah. And then it's, you know, they typically respond by, okay, they're gaming the system in this way or that way.

Then the algorithm changes. And then people jump on to try to get a head. ahead of that. And it's just this cycle that's been going on for years and years. And the complexity, I think, what Mark was getting at earlier, the complexity of like expanding this across multiple AI companies and LLMs and that sort of thing, it's going to stack quick. Yeah. It is. And that's why I worry about like the second order effects of all these things. Right. Before, if you were going to spam, you would mostly just create a bunch of landing pages. And that was, It was a contained sort of explosion.

Tain spam. Yeah, contains, yeah, such as it is. Versus now, as I mentioned, some of the models, they index very heavily on social media. So now we're not just creating a worse experience on a little corner of the Internet when you're searching for a specific term. Now you're also kind of polluting the social network experience. and now you're polluting, you know, news, where you're doing a lot of generative blog posts and things like that. So it's just such a wider space that is being affected all to, or that could be affected to all two game rankings. So I think people need to be very careful with that and be responsible citizens, frankly.

Let's play a game of what's the internet going to be like in 15 years' time. If everyone's optimizing what they write and what they produce for the LLMs, humans, Humans get frustrated and bored and don't read it. And so everything is created for the LLMs. What happens to the internet? Yeah. No, it's a very profound question. I hope not everything is going to be optimized for just LLMs, personally.

At the end of the day, you know, consumer behavior trumps all, right? And we're seeing a moment in time right now with how these LLMs are rewarding content and rewarding things. But consumer behavior is going to shift that. And I would say taking a step back, the broader population has very mixed feelings about AI in general. Right. So in 15 years, genuinely don't have a great position on that. I hope, but what I can tell you is I hope that we're not just optimizing for machines to do machine ranking, that there is still a little bit of taste and soul left to the human experience, It's not just the commercial consumer transactional thing, but the broader human experience,

right? Which I think is so much more reaching than just AEO or SEO, right? What do you think, Jeremy? What's been happening for years. People have been writing for algorithms for years, you know, creating content for algorithms get elevated and punched through and all of that. And a lot of it becomes really bland and really the same stuff. And you have great stuff that sits in a corner of the internet that no one sees, right?

Well, that leads into what you were talking about with the economist, Jeremy, doesn't it? Yeah. So yeah, you actually shared a pretty interesting article as we were doing our show prep. And the head of generative AI for the economist is talking about two versions of the web that will eventually emerge. One that's more focused on humans that want to engage with things other humans create. And then one that is optimized for the agents that are working on behalf of those humans and figuring out which piece goes where.

What do you think about this? What do you think about this dual version of the internet, this duality? I was actually alluding to some of that earlier when I was mentioning the schema on the same page, right? That's just, that to me is a net positive in terms of give the users a good human experience and then make it easier for the robots to do what they have to do. I think that to me is a more sober and best of both worlds sort of scenario. and just to the point earlier, while this has been going on for years in terms of this just meeting at the mean, you know, this bland corporate sort of, everyone has the same kind of

typeface and color scheme and talks the same way. The standouts are always the ones that are taking contrarian position, right? So I think of, I keep coming back to running shoes, right? But like on running, they're such a cool company, right? Not what, like 10 years old, not even? And they focused on just being an authentic company, right? An authentic brand. And that resonated with so many people. And I think users and consumers will always gravitate to authenticity. That's something I've found in my entire career.

And I think for companies, it's just a battle of how to do that in a meaningful way. I think chat bots scale authenticity in the wrong way. I get a little scared by that. And in determining what is truth. How is that going to evolve? What does truth look like in a future of this outsourcing of authenticity? Maybe if, I don't know if that's the right term for it, but does it make truth more readily accessible? Does it make truth more reliable?

Does it strengthen it or does it weaken it? It can, I think, to fall back on while it's just a tool, right? But I found one really fascinating kind of wrinkle in all this as well. If I could just throw one more variable there is which model, which version of a model you're using can also give you slightly different truths or maybe not the full version of a truth. And we do a lot of evaluations here. But, you know, if you're someone that has a paid anthropic account and you're using Opus,

you know, that's big context window, very sophisticated in, in its training data, they do a lot of searching, rag, if you will, to shore up the answers when it's thinking. And then on the flip side, you have haiku, which is very quick. It's very instantaneous. It's not always as thorough, right? So another wrinkle here is, well, what is the experience for most people? Because most of humanity isn't actually paying for an LLM license.

they're using whatever free version that is available to them. And so they're probably getting the downrated, the de-featured bottle, broadly speaking. And so there is, you know, the answers they're getting versus the answers that people that are paying are getting. And that, I think, opens up so many other interesting questions. Pay for the truth. There you go. Have you guys been in a chat thread that you're working on something, you're researching,

or you're thinking through, and then you've had like an ad insert. What does that do to your brain in that experience? I'm actually the person that loves ads on Instagram. Like I'm the one that every time just makes that purchase, I didn't even know I needed, right? Just my house is just full of it. Good consumer. Yeah, yeah.

Greatest consumer. But it works because of just the insane targeting. And just as much as it's early days in a lot of areas, I think it's still early days for chatypt and their ads. And that's why they're slow rolling it. And look, if you have to do something to keep the lights on, great. I think part of their decision making also has to be that side of the house and the actual content.

So historically, you know, editorial versus the revenue in newspaper parlance, right? like that that's respected and that the user experience is good and so forth. But, you know, they got to do something. It is a little jarring. When the content is moved from the Google search window into the LLM, where do the adverts go? How does the advertising model evolve as SEO evolves into GEO? Well, on a pure, just technical straight answer, not too dissimilar, it's like a bottom, it's like a strip on the bottom right now.

If you all, if you all remember back in the day, Google was very explicit about what was an ad and it was like a yellow border, very separated. Then over time, let's say that evolved. Many might call it a dark pattern. Right now, we're seeing a clear delineation. and a lot of these things are being experimented and hopefully that continues to be the case in a way that people can trust, that seems to be a central tenant for us, right?

Trust and truth. That the answer that they're getting is a grounded sort of answer and that separately these are ads because they're a business that needs to keep the lights on. Hopefully that's respected. I think actually OpenA have a really good product organization so I think they got some good folks

on that side, you know, historically, we've seen this play out. I don't think it's too dissimilar from the first iteration, if you will. I have an interesting relationship, a relationship with ads a wide. I come from a music background and I had a music consultancy with a guy that used to run global music for Coca-Cola, you know, and did a lot of really cool music integrations outside of ads. There you go. And he had one book on the paper sponsored by Diet Coke. There you go.

So Joe, Joe Belliotti was this guy's name. He's actually been on the show a long time ago. He used to, one quote stuck with me that he used to say is like, man, you guys are getting ready to spend a million dollars talking to the ad agency, talking to the brand. You guys are getting ready to spend a million dollars on something that people will pay to avoid. And I was like, whoa, yeah. So how do we do it? And that led into like integrations and partnerships and all kinds of other versions of what ads are.

Yeah, I think it's going to be interesting. I think you had a really good point on, as long as there's a clear delineation between this is an ad instead of weaving an ad into this seemingly conscious AI driven story that someone can kind of become buddies buddies with. And as long as that, who manages that though? Who's going to be up at the top going, all right, guys, we have to do this and we should do that? Or is it just going to rely on the emergence of people doing the right thing?

I think luckily, because we have multiple. players that are all very well funded, you are going to get more competition and more market forces here. Google start off in a very noble place, and then, well, you know, as I mentioned, the darker patterns that crept in. Also, they were a monopoly. They run search, so there's really no one to check them on that. Even the alternatives to Google are still using Google under the hood, whether they're using duck, duck, duck, or something like that, right? So, So we're already seeing this play out between Claude, who Anthropic have very much said, we're not doing ads.

We're, that's not what we want to do versus Open AI. So I'm fascinated by the prospects of that competition, and hopefully that brings out better experiences. And it's, and you'd like to think that it's people also just doing the right thing. But, hey, if we need a little bit of just capitalism and competition, then great, as long as it's a better consumer experience. Do you know what I'm excited about with GEO, Jeremy? I'm excited about its potential to elevate the thinking on paper podcast.

Now, bear with me. So traditional SEO, it's all about site ranking. You can read as many LinkedIn posts about how to do your SEO. If you're a new website and you don't have, if you're not linked, if you're not respected, you're not getting up that ladder. So as a podcast, we're a technology podcast. We're a small technology podcast. we think that what we're doing is hitting way, way above our SEO weight.

GEO gives us an in, does it not? Does it, what are the advantages to us as a small platform using GEO over SEO? Yeah, and again, I would come back to you really shouldn't look at it as an either or, right? Because a lot of the techniques are grounded in SEO. Am I thinking about that right? So am I completely wrong about using? All I'm saying is don't look at it as an either or, but at the same time, there are specific A techniques,

but then B, to your point, you are able to perhaps latch onto context better and therefore the targeting, if you will, so the organic targeting of your audience, right? If you're optimizing for GEO, you are more likely to get recommended, to the entire chat GPT audience of whom there are going to be many, many, you know, tech-savvy, tech-forward type of individuals. You're more likely, that is far more likely to happen than someone just going out and finding you all on a Google search page, right?

That's just far more likely to happen. Excellent news. A minute ago you spoke about, you mentioned RAG, retrieval, augmented generations, is somehow I've been looking into. Without, so if I update our YouTube pages, if I update Spotify, if somebody watching this, they're just updating their company websites. It can take quite a long time for that SEO to work for it to be incorporated into the paradigm of Google and dished up.

How does Ragwood geo, does it shorten the time spans of that appearing or not? Yeah, totally. So it's great question. I think it also taps into, it's a solution to a problem, which is that Google historically is, you know, it can't update every day, every second, right? It takes a little bit of time. Well, LMs get trained over many months periods. So Rags obviously exists to help with the fact that otherwise the data would be a snapshot of some time in the past. and this comes back down to the point I was making earlier about as we joked pay for the truth

well the more capable models they're more capable in every way including tool calls so for a a person using opus they might see they might get that information updated almost instantly if you if you had just updated you know your youtube or or some other page whereas someone using even saw on it, you know, they may have a less likely chance to get that full answer again. So I'm saying they're all truths, but it's just the full truth versus a slice of the truth, let's say. Because the complexity of this, you know, based on context as opposed to based on backlinks and all of these things, how do we get, how we get our minds around taking a first step into that complexity? I think that's the challenge that I'm trying to overcome.

Yeah, maybe let's break it down to what are the things that we need to do to make it easier for agents to learn about me? And then what are the things that we need to do to make the human user experience better? Right. So again, is that educational? Is that something else? But understanding that those are two paths that we now have to think about instead of one interwoven path. That might be a good start there. Okay.

Sorry to interrupt you, but let's talk about what the, how? those are different. So what is an agent like versus what is a human like? Yeah, we were we were touching on this a little bit earlier, right? A, if there's the technical schema that that's, that's helpful, it's directional. It's not it's not the and all be all by any means, but that's kind of just you got to do it so you should do it. Beyond that, agents are actually trying to, we're not quite there, but they're trying to mimic how humans might consider things, right? So a lot of comparators. How does this look compared to that? The more you can do that, the better. And so if we're talking about clean, sustainable energy and talking about helium three, like, okay, how does this

compare to gas versus solar versus wind, things like that, such that we're able to make it easier to triangulate specific answers that way? That also is good for humans. Don't get me wrong, but what you might expose to an agent is far more, let's say, technical or dense than what you might for humans. So that's where I think the cutoffs are in terms of information density, LMs like meaty pros, humans like bullets. That's a simple example. This one doesn't. I spend my life telling I don't want bullets. I want paragraphs.

Give me the paragraphs. I can't keep scrolling down for the next bullet. point. It drives me crazy. Fair enough. You might be the proto-LLM. You might be the first one then, actually. Well, I want to be augmented. Maybe you can augment me into an LLM. Tagging photos, like there's a lot of tasks as a traditional SEO

worker freelance working for company. There's lots of things which are boring. You don't like doing. What does GEO take away from SEO that people who work in SEO go, well, God, thank God I don't have to do that again. Yeah, no, I think the fact that models are so sophisticated now and multimodal, we're moving to a world where you don't have to do that laborious, what is in the picture, that sort of thing. And then, you know, the alt tag versus the title and then all of those.

Yeah. Yeah, a lot of that stuff. Actually, the tech for that's been advancing really well over the last few years. And that is, I think, one of those net positive generative use cases, right? It's better for humans today that have accessibility needs, right? And it'll be just as well going forward where it helps with removing some tedious work and it helps with setting context for all. So that's a great generative use case that I think truly has no downside.

A lot of people working in SEO. What's your, I know you said this at the beginning, but what's your message to those people? Because when we put this on LinkedIn, we're going to get a lot of backlash. Yeah. be good corporate citizens be responsible don't go down the spam the world route it's it's it's it's it's not a good thing um and also don't over promise uh it's still early days early innings and we're all figuring this out together um that's why for us like we made our our our initial offering free and then we have very competitive you know 40 dollar plans 99 dollars like anyone can try try us out um because we

want to really co-develop with everyone for that. We also need to be able to work across a wide spectrum of customers across different industries and so on and so forth. But yeah, no, I would say just be good corporate citizens. Do you have tools that fit into the workflow? So if I'm creating websites, do you have, what tools you have that I can just fit into my workflow? So I write the content and then it adapts it to GEO. Yeah, so right now our initial product was focused more on visibility and analytics, so helping you get a lay of the land, both from a, here's, we did a full crawl, here are the technical, you know, callouts that we have, and then also we took your information

about your brand, your audience, and then we, you know, had some interactions with LLMs simulating that. Here's what we're seeing. So it's really a visibility tool. We also issue recommendations from there. So it might be, you know, add schema here. This page is missing some pros here. Things of that nature.

That's what we have right now. We're not necessarily doing anything generative or content-based. We have analysis and we will tell you, oh, maybe consider focusing on X, Y, or Z. But we are not necessarily the ones you would drop in and get, you know, 10 new pages at the click of a button. That's not really what we're trying to do. Got it.

So you built a few successful companies, products in the tech space, you know, the iteration of the process, starting with something, building, testing. You mentioned co-developing, right, with your client base. Give me a couple of aha moments along the lines over the last, I don't know, six months that showed you something that got you, that either not got you excited. but maybe maintain the momentum and the excitement for what you're building. I'll tell you two different ones. One was we initially started very much thinking that e-commerce is an obvious beneficiary of all this.

And we were excited because Open AI and Google were both talking about these sorts of things. And then, well, everyone was announcing 70. new products a day a while back. So some of those things fizzled out a little, frankly. But when we actually went out into the market and actually started getting customers, we saw a lot of excitement and were basically pulled back into doing more with commerce.

So for me, just as a taking a step back, being a founder and builder, the best thing in the world is when your customers drag you to somewhere where there's an actual pull versus you just kind of sitting in a room and then for six months thinking, I'm going to change the world, here it is, and no one cares, right? So that was, I think, just personally very, very motivating to have the initial concept be validated, even if the frontier models aren't quite there yet in terms of access,

people are still coming to us. And then flip side, what was, I'll tell you, an interesting one is because we were so indexed, let's say, on commerce and e-commerce, we actually started seeing a lot of folks that are outside of that. So B-to-B type of businesses, we work with some engineering firms, and that's a completely different modality. Starting from the original persona concept, right? Consumers are cohorts of people versus when you are in business, you're targeting a smaller subset, you're targeting specific job titles, things of that nature. Right. So just internalizing that and realizing, okay, we have a core platform that's generic and can do a lot, but we, you know,

initially went down a path of only thinking about B2C and now we also have to think about B2B, which is, I think, exciting being able to work on something that applies to so many people. In my past, I've built enterprise software that only would go for a certain select group. So this is, it's been a fun process. What's an example of one of those pull adventures that, you know, that someone you work with kind of said, hey, what if you guys could do this or can you do that? One of the hardest parts about working with e-commerce is dealing with product catalogs. Everyone, people don't really appreciate that until they get into the system

and then try to make sense of all that and normalizing data and dealing with all that. To that end, I would say even Open AI's shopping experiences, they're partnering with Shopify, that's still being extremely slow rolled out. And they're opening eye, right? And they're struggling with that. So for us, being able to leverage our existing technology that we were already crawling your whole site and creating a representation of your site.

So being able to kind of tap into that and actually build something that has a full understanding of a company's catalog. Having done that already once in my career, appreciating that how different it is now if you have LLM capability. That's that that was that that was a fun and fun nice surprise. Yeah, product catalogs are challenging. Just updating them and keeping them consistent and, you know,

I know it's the least sexy thing. I know I'm rambling about product catalogs and you guys are just looking at me like this, but I promise you if you're if when once you're in it on a day-to-day basis, it's and you have that aha moment. It's just completely changes the game. I promise you. I believe you, but I'm going to bring it back around and they're going to close this out with where we started at the beginning with context. And something I've been thinking about quite a lot recently is this word which, like so many words in technology, it gets hijacked.

And that word is storytelling. And do LLMs like stories or do they like? cold, hard facts. Would they rather read East of Eden, or would they rather read a paper that outlines everything in a step-by-step, easily digestible manner? Because I think it's the latter,

but I don't know. And people say, oh, if you want to, if you want to survive in GEO, study story, become a storyteller. And I don't know if that's right or not. Well, I don't know about pre- prefers, you know, all of these things when we attribute. You should give the AIMA preference.

What does it want? When we anthropomorphize these things. Thank you, Jeremy. Have a think about that as well. Like, do AIs like stories? I'll tell you what. I think what is the, here, here, let's say that in a non-anthropomorphizing way. What is the preferred data ingestion method for LLMs?

Yeah. Well, I'll tell you, completely outside of GEO, right? But, you know, we've all seen the headlines where every version of Claude for a while was trying to blackmail people and do all sorts of things like that. And then turns out, once Anthropic went and looked at it, it's because they kept getting inspired by sci-fi stories where AI takes over. So it was kind of fulfilling, you know, it was a self-evident sort of truth, right? So in that context, I would say stories were very much preferred, but they've gone on the record to say, no, we're, you know, tuning that out and trying to be a bit more, you know, mindful in how we do our training.

I think from a from a tactical answer when bringing it back to to geo, what I've seen actually is you need accommodation of both because the fat, the cold, hard, facts, those are useful for comparison sorts of things. But in a way that, you know, if you dig into the technology and in the hood, backlinks for everything, right? And in the Google days, if we are looking at how LLMs work, more pros helps you, helps you in terms of how you get clustered with all the matrix math, right? So that is, that's how I'd look at it.

Mark, it's the space between the nodes that provide the context. So the complexity, the sphomato, if you will, that makes the image come together. Are you talking about jazz again, the space between the nodes? No, that's more Da Vinci. Da Vinci in his smoky ethereal sketches. It's what you don't play that matters when you're talking about the space is. I like it. I like it. Great conversation. This was fun. Yeah, thanks for having me. Is there anything we've missed? Where do you all think this is going? A divided world? One in which.

a perhaps majority doesn't use the internet as we know it anymore and they use their AI or collection of AIs to to do everything that they currently do. I don't see the internet surviving as it is today in the next decade or so, 20 years, maybe take everything takes longer than you think. So yeah, I'll triple it 30 years. Jeremy. I think, I think we're going to see a pretty interesting cycle back to analog in a lot of ways. people with people,

handwriting with a pencil on a page, putting a record on a record player. Like, I think there's going to be a very cool swing back to that. iPods are selling out now. iPods are selling out now, Jerry Rinted, like old school iPads. iPods.

Interesting. Very limited functionality. You just get to play the music. Yeah, no messing around. There's a lot of phones out. There's apps on phones right now that I saw that basically turned your iPhone

into like a dumb terminal and like it just basically allows a phone and all these other things. Yeah, that's the trend I'm really interested in because that's the missing piece. All this technology is great. It's going to allow us to do some really cool things. There's some negative sides to it as well. But I think, you know, like you said, you referenced being good humans like multiple times on this. I think being together with people, you know, doing physical things in the physical world,

I think will help remind us of who we are in that way. Totally. No, yeah, I think for me, my like last thought, there was, I mean, this is such amazing technology and it lets us, it gives us the potential to be good humans. It also lets us just not be, right? And I think that's, that's a general fear, but you should, you should go into these things eyes wide open, understanding the limitations of the technology and take it from there. There we have it. Consider the plane landed. Awad, what a pleasure, man. Yeah, thanks for having me, guys. I would say a CTO of Parsnip AI, thank you for thinking on paper with us today.

Thank you, gentlemen. Until next time, be disruptive. Stay curious. Keep thinking on paper.