AI is Eating Search

And the origin story hopefully, I don't get in trouble for telling this on the pod. The origin story is a little bit convoluted as I think it is for most startups with Scrunch. My co founder Chris and I, we had left Hearsay.

Chris was actually also a long time executive at Hearsay. He was the chief product officer for a long time. He's the first employee.

So we both know all those folks really, really well. Yeah. We were looking for essentially what to do next in our careers.

You know, thinking about starting a company and kicking around ideas, talking to people we knew in the industry. And as we were doing that, the elephant in the room was AI. Right?

Like, it just became really clear, I think, a couple of years ago that, like, it would be sort of foolish to start a company without thinking about what the impact of LLMs would be on the world. And you'd already be behind if you sort of started a company that wasn't in some way LLM native. So we went through an exploration process there.

And as we were talking to the people we knew the best who are often sort of enterprise y, large banks and insurance companies, that was a primary kind of audience for hearsay. It was a tough sell back then to to sell them anything related to AI. And the number one thing that people were probably asking us for, quite honestly, was like, can you put a chatbot on my website?

Right? Like, I'd like to have the widget. I'd like to have my version of ChatGPT.

I want people to come to my website, and a widget will pop up, and then people can type into it and ask my website questions instead of going to ChatGPT. And there are good versions of that now. The versions that were out at that time of that functionality, I'd say, were mostly not so great.

But basically, my core feeling about that at the time was like, nobody wants to use a chatbot on your website. I don't wanna use chatbots on people's websites. It's like, if if things pop up on a website when I go to visit it, I just like I I fly into a visceral rage.

I'm definitely closing the window if not if not closing the tab. So we didn't wanna do that.

You know, I think there's some evidence that people don't love it. I think Intercom's a little bit different because by the time you're engaging with, like, San or what have you, hopefully you're in a relationship to a certain extent with the business. So I do think that people have a little bit more tolerance for using these AI tools.

Like, when they're already kind of feeling some rapport with a website or with a business, they're more willing to like use your tools instead of saying in instead of saying in the environment they like to use. But if you're just coming to a website and it pops up, like people mostly, I think, don't wanna do that. People have responded really positively to ChatGrBT.

Most people I've talked to, and I'm live by the way, live in LA. I've lived in LA for a couple years since pandemic. So I'd say, like, more of my social circle is normies than it used to be.

Like, people love ChatGrBT. The experience people have of using ChatGrBT versus, like, browsing the Internet, sort of the old Google 10 blue links and clicking around, is, like, vastly more positive, you know, compared to the past. So people really feel, I think, like, an affinity for the tool, and they wanna use the tools they like.

They wanna use, you know, whether it's chatuchu.t or it's Claude or Proplexity or what have you. Like, they really like that environment.

It's convenient. It's productive. They don't have to browse websites that maybe aren't well designed for them.

People are not excited about the idea of like, okay, let me click around, find a website, and then engage with the chatbot there. In the same way that I think people aren't like, let me go to the website and use their search bar. Right?

People just wanna use Google. I do think that's that's true. And when we have that realization of like, okay, people are asking us for this thing, but we don't really wanna build it.

We don't necessarily think that's like the durable value. Started asking ourselves, you know, what is it? What are they trying to get to here?

And it came down, I think, to discovery and basically this realization that, like, AI was gonna change something about their website. It gonna change something about their customer journey and how people sort of interacted with their business, but not knowing exactly what it was. And as we started showing people as Search was coming out, how Chat Beauty Search was referencing their business, how it was surfacing their content, it was saying about their brand.

We just had the experience of like having a lot of folks, you know, folks who are like CMOs at like large insurance companies, or enterprise software companies, or large, you know, e commerce marketplaces. That's really scary. It's saying stuff about my business.

It's saying stuff about my brand. It's surfacing content from my website. And I don't really know what's happening here.

And so that's sort of the genesis of how we got into this business. More than focusing on SEO and performance marketing specifically, more like there's just a change in the way consumers kind of interact with the Internet. And I'd say that's still true today.

Like that's still sort of the core thesis of the business is like the consumer experience of the Internet is changing really, really quickly for the first time in like quite a long time. Yeah. So I'd stop I maybe I'll stop there.

But that's sort of the the origin story. Yeah. And I know, as you know, most people here are technical in the audience, so it would be nice to dive into that.

Yeah. So what we do starts with what you said, which is we monitor prompts. Basically, go out and we sort of simulate consumer interactions with the major AI platforms.

So we kind of go just by by basically like usage. So ChatuchParty obviously is is among the highest usage. AI overviews could be considered up there as well if you consider that in the same category.

AI mode, perplexity, and you can kind of get down the list from there. We definitely don't cover everything. I'd say our ambition is ultimately, like, to sort of be wherever people are, wherever the consumer is, wherever our customers' audiences are.

But today, we primarily focus on sort of the the biggie. So Chat2PT, whether it's search or trained model knowledge, Gemini, Perplexity, Claude, which is important for, you know, not necessarily huge in terms of raw number of users, but the people who do use Claude tend to be like a very valuable audience, especially for some types of company. And then also things like Meta AI, for example, which I don't think gets necessarily remarked upon a ton in the AI enthusiast, AI developer community.

But like, it's a silent monster, right, because of Meta's distribution and reach. So it's expanding all the time. You know, we'll we'll have more platforms live, like, probably by the time this podcast comes out.

But we sort of start by focusing on like, what are kinda you said it before, what are the normies using? What are they doing? What are they seeing in these tools?

So now that you have searched, they have the backlinks. But when you don't have search on, there's no way to figure out why Amato is saying something. Is that a battle that basically people cannot fight?

Like, there's something in the pre training. Is there something that you advise people to do or you just flag it and that's it? It's definitely less actionable.

Right? And I I think that the good thing for brands is like, generally speaking by the way, when I say brands, like, throughout this conversation, that's just like our term of art, but I just mean like businesses. Right?

Businesses that have products and services and, like, websites and want you to do stuff on the Internet to make money. I think it is less actionable. So most people, I think, are focused more squarely on on AI search.

So chat to me to you with the search box ticked. The good news is I think, like, most of the queries that will lead to action that are sort of of commercial interest are increasingly using search across these systems, like for a bunch of reasons. Right?

Timeliness and and avoiding hallucinations and so on. So I'd say, like, most people are focused on that. There are things you can do even in pre training mode.

And an example of that is just thinking about like what are you exposing to these models when they do come and crawl your website. Right? Everybody knows that GPT bot and CC bot and all these various AI training data collectors are hitting tons of websites on the Internet.

Some people are fine with that. Some people are are upset about it. But they're identifiable.

And you can think about the half life of the information you're presenting and whether or not that's something that really makes sense to give to a training data crawler. So for example, like, you know, if you're an ecommerce company and you're running a seasonal sale, like, should that go into the trained knowledge of a model? Like, I would argue that's probably counterproductive.

Right? So maybe you don't wanna expose information about that to those crawlers hitting your website. And that's something we advise our customers on.

Yeah. Right. I mean, it's really interesting.

I kind of agree with the sentiment, I think, behind it. Right? Like, I mean, obviously, it's tough to be it's tough to be a writer on the Internet.

It's tough to be like a content publisher on the Internet. And it it's getting tougher and tougher, I think, over time, whether it's Chat to Me Tea or it's it's Google AI mode. So the idea that where there's some sort of maybe like grand bargain we need to make as a society to, like, compensate content providers, which I think is kinda what, like, Matthew Prince is getting at with his blog post, does make some sense to me.

I think there's two things to think about there. And one is, like, technical mechanism, which is, like, how does this paywall work? And I would just say, like, the bridge doesn't connect on both sides yet.

Maybe we'll get there. So I don't think there's a lot of actual use of those systems. And there's like prior art.

Right? There's things like Tollbit, for example, that kind of has some similar ideas. I would say, like, there's some uptake in traditional media.

It's not like a huge piece of infrastructure on the Internet yet. And then the second thing I think is about power dynamics, which is like who wears the pants between website operators and CDNs and AI, in particular, AI search or search engines in general. Right?

Because websites obviously are sensitive to how their content's being used, but they also need traffic. And traffic, by and large, comes from Google. It's increasingly coming from JatGPT as we've seen.

You know, there's a fine line, I think, for The Walk where unless you've really got a strong native sort of like organic audience of people who like know you, love you, like have a relationship with you, which is still like one of the most important things you can do on the Internet, you need to be careful about how restrictive you are with your content. Because distributing your content through these systems is is how you're gonna get users.

very real. And I think one one thing I would just mention here is, like, they also have the AI browser announcements this week. You know, there's, like, Dia, there's Comet, there's there's the untitled OpenAI browser.

And I think that's a really interesting addition to this mix too. Right? Because what I what I kind think about is, like, you sort of just said it, but it's that nineties phrase of, like, information wants to be free, and people wanna connect models to the Internet.

And so, like, the way people are using these today is going through Chatuchiki or something, which feels like you know, Google is a is an input box in the middle of a pretty Spartan web page, and Chatuchiki is like an input box in the middle of a pretty Spartan web page. So they feel pretty similar. They're both sort of like these Internet platforms, Internet gatekeepers, and people think about them the same way.

But, like, there's no reason that has to be the way you consume Internet content and get it into these models. And I think the AI browser form factor is a really interesting evolution there. There's gonna be others.

Right? There could be local tools, local models. And what I would just say, right, is you can fight the battle, I think, of saying OpenAI shouldn't consume your content without paying for it or shouldn't consume it at all.

But I think it's gonna be really tough to fight the battle of saying, LLMs writ large shouldn't consume my content because it's just not that hard to hook these things up to to Internet content and set to some degree. And, like, once it's in somebody's browser, right, like, how are you going to to stop them? That's a whole different mechanism.

Some people, I think, are thinking about this change when it comes to AI search as one platform replacing another. So instead of Google, it's OpenAI. Or maybe it's Google disrupting itself.

But I think there's a more fundamental change, which is people just have more powerful tools, have these AI tools, right, to consume web content. And I think what you're seeing with people who have access to the tools is like, they don't wanna browse websites the same way they used to in the past. Right?

So like, I actually think like, this is probably like a medium spicy take, but it's like, thinking about what's going on in AI that's really replacing search is the wrong take or maybe not that interesting. It's really more like AI is replacing web browsing. I think that's actually a more meaningful, more fundamental shift.

The reasons it's happening, think, is because people just like it better. It's not because of some top down platform mandate. People like using these tools to replace what they were doing before by the clicking around the Internet and consuming content.

Not for every single use case, but for a lot of things that people are using websites today for that they prefer to use an agent. Well, and deep research probably being the biggest example of that.

it suggests me? Or is the model simply just using the same ranking as the SEO that Google API, Bing API are using? So so, I mean, this gets this gets into the mechanism of it.

Right? And what I would say is AI search is still fundamentally search. Right?

So there is still a search ranking. And by the way, to the best of my knowledge, which I think is pretty good, most of the search that's in AI search is still traditional search. Right?

There's an AI model in front of it, but you're still using your sort of traditional, like, you know, text based, like, BM 25 or TF IDF or PageRank or what have you, search algorithms under the hood to locate pages in a search index. And that is kind of a fundamental component of all these AI search systems so far. I know people like Axle are doing something different, and I think that's really exciting.

But just like that's not what's powering most of the products that people are using today. So traditional search ranking does still matter, and traditional SEO techniques do still work. Now where it gets tricky after that, right, is like, you're not just getting links for discovery, you're also consuming the content behind the links.

How much of that are you giving away? Like, what does it say? How well is the system able to interpret it?

And so, like, the way we think about this for for most, you know, most models, most platforms, and the details vary a little bit between, like, know, ChatGPT versus Cloud Search or something like that. Right? It's like, you're generating queries.

Right? You can generate one query, you can generate multiple. If you're looking at like AI mode or some of the more recent like, you know, o three search integrations that ChatGPT has.

So you're generating keywords using an LLM. Right? You're running searches in parallel or potentially serially if you're using a reasoning model.

They're going out and retrieving results. And then there is sort of re ranking that happens once you've got those raw search results. So the raw search results are, again, predicial search.

But then what you're doing after that is it's re ranking them for relevance. And then it is only then starting to look at the actual content behind the pages. So this is where we see people, I think, get tripped up a lot in terms of small things that go wrong in terms of getting cited or getting mentioned inside ChatGPT.

Is people have these pages that rank really well for search. And then when you look at the title of the page, you don't look at the page content, you just sort of look at the metadata about the page. The metadata has been super optimized for human click through.

Right? So think about clickbait, think about things that are creating urgency, especially true in ecommerce, right, around sales and things like that. But they're not very informational about what actually is on the page.

And then what we see is, like, regardless of search ranking, often, a system like ChatGPT chooses not to use those. Right? So it will re rank them out of the consideration set, and then it'll just kinda go on to the next best result that has a more descriptive metadata saying, hey, this page actually has something that's relevant to your question on it.

That sort of re ranking step is critical. Since this is a technical podcast, they'll say like, I'm not saying re rank our model. I just mean there is a more intelligent step of sort of reordering what it looks at coming out of the traditional search index before you get to the part where it's actually consuming content and summarizing and generating.

That's, I think, an important technical mechanism to understand. In terms of the strategy of how much to expose, I think it varies based on what you wanna do. For shopping, I would say, typically, they're gonna buy the product from somewhere.

If you can get a link to your page and your page has a checkout on it, that's what you wanna achieve. Obviously, that's starting to change with like Chatchwiki Shopping and some of the more agentic shopping integrations we're seeing in terms of being able to buy right within the AI experience. But I would still on the side of disclosure.

Right? And I would especially on the side of in your content talking more about who the product is for and what it's good for, and being descriptive about it. A lot of shopping pages are really highly visual, for example.

So they're tuned for people who are looking visually at the web page and being like, I wanna buy that. And that's still worse because it's still super important. You're buying fashion, for example.

Right? That's just inherently a visual aesthetic experience. But even within apparel, we see that just being a little bit clearer about here's why here's who buys these type of leggings and for what can make a big difference in getting surfaced in Jatubu T.

And then not only getting surfaced, but actually getting people to click through and ultimately purchase the product from that source.

Yeah. I mean, people really want that to happen. It doesn't happen today.

Right? And I think there's a there's a bunch of reasons why that's the case. The reason I think it probably won't be the case in the future is for privacy reasons.

So I don't think that you will see, at least in the context of the way search is working today inside like a system like Chat to Media, I don't think you'll see that it's gonna pass, like the prompt the user was using to the website, right, that it's getting content from. Because, like, if you think about how how people use Chat2D, people who get used to using Chat2D start putting, like, all sorts of, like, protected health information and, like, crazy personal stuff into it. And that's one of the reasons it works so well.

But obviously, you don't wanna be passing that to websites you're finding through search on the Internet. So right now, the answer is people really get almost no information about what led somebody from Chatfuel to their website. But I mean, that being said, I think if you look at where people are going to from Chatuchiki to your website, you can get a lot of signal there.

Right? People are coming to certain product categories. If they're coming to certain blog articles, you can get a sense of like, okay, what are people interested in who are using these tools?

And especially if you have a good feeling, if you're if you have a good feel for your audience, I think it can be really powerful. We have customers, for example, who have seen that people arrive on certain topics. Are developer infrastructure companies.

They see that people arrive from ChatGPT on certain blog posts about certain, you know, certain problems they're trying to solve. And they're like, clearly, are people trying to solve this problem on ChatGPT because this was surfaced and it came up. Let's write more content about that.

And it's been a really effective strategy. Right? They're just realizing that there is demand even though they're sort of indirectly detecting it because Chatzmiki is sending people their way, and then they're just creating additional supply for that demand.

a feature that they didn't have, then they were like, screw it. Let's build it because they Yeah. I I saw that.

I think I saw that one come through. Yeah. I mean, does that all the time.

Right? I mean, I think that if you're if you're like a cursor enthusiast, I think many of us have had the experience, for example, of being like, this thing keeps hallucinating methods in my code. I'd probably should just implement the methods so that I can stop having to try to prompt engineer the model not to do that.

And there's sort of a similar vibe there. Right? But I think that's also an example of my guess is without having looked a ton at the actual example of that particular company, that's a case where doing some sort of context engineering, doing some engineering of the actual content they had on their websites, on their pages, might have improved that problem.

Maybe it would have been a mistake to improve it because they might have lost this funnel of users who were like, yeah, we're really interested if you have this feature. But one thing I'll say about startups, and we've done a lot of reviews with Y Combinator startups, for example, is startups are really, really bad at describing what they do on their homepage. The number of homepages where you're like, there's a really cool parallax scroll animation, and you're like, what does this company actually do?

Is super high. And I think that's tricky if you're trying to make, like, the best use of these tools.

Yeah. I mean, I think that people are definitely doing people are paying very close attention to the specifics of what the different AI platforms are doing in terms of ranking and what kind of content they consume and testing all sorts of experiments for what works best. I'd say our role in terms of what we do at Scrunch is we do a couple of different things.

But one of the things we do is we give people a feedback loop to understand how what they're doing is changing their performance. And so we've had some great case studies of people doing things like that that are pretty in the weeds and getting good performance boosts out of it. In terms of some of the more gray area SEO tactics that Penguin was addressing with Google back in the day, I mean, I think the reality is a lot of those things do work today.

I can't tell you they don't work. But I would say as a company, I wouldn't encourage anybody to do them because I think it'll change eventually. And one thing you mentioned this, but like one thing that's definitely true about all the AI search companies is like everything's super early.

Twenty four months ago, ChatuchPutty was like basically, ChatuchPutty was the original ChatuchPutty wrapper. It was just a wrapper around like, g p d 3.5.

And obviously, it's gotten way more sophisticated over the past year or two. But none of these products have as much attention to detail or engineering put into them in terms of, like, moderation and abuse detection and, like, being defensive against the fact that the Internet's a wild place as Google does. Right?

And Google's been around for twenty five plus years, so no surprise there. A lot of things that work the way they work in AI search today, I would definitely say work that way sort of by accident. And so that's part of the the challenge, I think, of being in the space, whether you're us or one of our customers that's trying to figure out how to make this work, is like everything changes super quickly.

Of course, that's always true in AI. It's not just about like models getting better. It's really about, like, all of the underlying kinda glue that's connecting these models to search and to the Internet, just, like, being pretty rudimentary and, like, getting more sophisticated over time.

I don't know if that answers your question, but that's the way I think about it. What's the name of the category in your mind?

I would say people ask us like, are we a GEO company? And I say, yes. Right?

Because you can only fight so many battles. But again, I mean, I think if you think about people have different definitions of what SEO means. But I think most common understanding, right, is it's basically about showing up higher in search results.

It's about showing up more frequently. And that is an important part of optimizing how your business, your products, and services perform in these tools like ChatchBT. But again, I I I think that's only like the tip of the spear.

Because it's not just replacing discovery, it's actually replacing how people actually consume content about your business, and increasingly how they like interact with your business. It's not just like the entry point, it's more of the full journey of how somebody like engages with you or engages with your website. And so I think SEO, AEO, GEO, that's generally been more focused on that entry point.

And the real prize is, again, I think more and more traditional web browsing is going away. Like, how do you optimize the complete customer experience for a world where, like, most people are doing most things in a tool like ChatGamingTee instead of browsing around your website. So I don't I don't know what a good category name for that is, but I think that's the one we're in.

The way we think about it is agent experience. Right? So by analogy to the customer experience, there's tons and tons of technology around making sure that customers have a good experience when they do come to your website, and like go down funnels, and like have a high NPS score, and ultimately convert, and and are happy with the service they get.

You know, I think it's gonna be really important to be that data driven about how these, like, AI systems are interacting with your content, with your website, with your infrastructure. Because ultimately, they are serving your ultimate customer, serving the user, and you have to do a good job with the AI systems if you wanna do a good job for the user. So maybe agent experience is is what I would call it.

Let's go forward to a feature where, like Sam Altman says, JWPD is kinda like the all encompassing personal assistant.

It definitely is. Right? Like, ChatSpicy personalization, memories, just explicit preferences, if you set them up, do definitely affect the results you get.

Now, again, obviously, they're they're still using traditional search. So the search index itself is not necessarily personalized. But you can definitely tell ChatBody, right, like, I don't wanna read anything from these sources, and it will try to obey.

That can affect both, like, it's searching for, and also which sources it prefers and ultimately how it presents information from those sources to you. Right? I mean, I have the classic set of chat meeting instructions in my chat meeting config, which is like, I'm a senior engineer, be concise, don't over explain things, and don't blaze me too much.

And I certainly get different results using AI search with that profile that I do if I'm in an incognito window with the default consumer experience of Chatuchiki. So I think, again, understanding your audience matters a lot. Ultimately, maybe where this ends up is no single Chat to BT.

Every single person kind of has their own, right, their own fully personalized experience. And I think if you're a marketer who's like, how do I measure this stuff? That's kind of a nightmare.

But I just think that's the reality you may be living in. So again, understanding your audience, understanding your personas, your ideal customer persona, thinking about how they wanna use these tools, what they're trying to accomplish, and modeling that out and measuring it is like a really important thing you should start doing. And that's something, again, that we we try to help with in terms of what we're doing with monitoring at Scrunch.

Not just like monitoring prompts, but trying to group them into customer personas and actually monitoring the complete experience for somebody who is a senior engineer, is a product manager, is whatever ICP kinda makes sense for your business.

like, there's there's clusters of how people use LLMs that are definitely a little little bit less commercially relevant. So for example, there's there are a lot of people who are very high volume users of ChatGPT who are doing role playing, for example. And then there's some other systems that have been more of that.

And if you're us, that's maybe a little bit less interesting. The biggest thing I would say is, if you expand from coding a little bit, what I would really say is it's about problem solving. I don't know if you guys have seen this, but there was a study that's gone around.

There's been a couple versions of it around what is basically the prompt intent of what people type into ChatHPT. Are they using it to find information? Is it navigational, which doesn't really make sense?

Is it generative? They're trying to create some text or create an artifact. Are they doing research?

They mined all this data from like panel data, the clickstream data of like a bunch of consumers who had opted into having their data collected, which is like the classic way this stuff happens in marketing research. One of the takeaways that the study had was like people use ChatuchPut a lot for these sort of generative tasks. Right?

They're trying to accomplish something. They're not necessarily trying they're not necessarily trying to do a search in the sense that somebody's, you know, trying to go to Google and search for a topic. And their takeaway was like, maybe Google's safe.

People are not necessarily using ChatGPut that much for these search tasks. So Google is still the king for search. You don't have to worry.

Like Google nobody is moving your cheese too much. But actually, what I would say is when you look deeper and and study how people use the tools, we've done some qualitative studies and things like that, and then we have we have the same data everybody else has as well. People go to ChatGPT, especially in a business context, to solve problems.

They're like, I need help with something. I need to accomplish something. I need to write this proposal.

I need to come up with this financial model. Like, for coders, it's real like, it's really, really potent. If you if you've used AI coding tools, like, they write the code for you.

You get a solution. You can run the solution. Like, problem solved.

You're done. Right? So that's very tactile for most of us.

But even outside of coding, I think people do a lot of that. And so what I would say, right, is like, you think about search, again, a commercial context, it's usually like somebody being like, how should I start to think about solving a problem? Like, how should I go find options I can consider to solve this problem I have?

Right? How can I use Excel to build my financial model? How can I write a proposal that'll look good to my boss?

These are search intent informational queries. In chatting with people, people don't really do that. People just say, solve the problem for me.

What I think is really interesting about that is it's actually the highest intent. Like, it's the most valuable thing you could be doing. Because you're going from being like, I think I need to solve this problem and maybe I will, to being like, I'm actually in the middle of trying to solve it inside Chat Smoothie or Cursor or what have you, right, depending on what you're doing.

So I'd say that's kind of the biggest cluster if you wanna get a little bit more abstract. One specific example that takes people a little bit by surprise is there are a huge number of people doing, like, b to b software bake offs in ChatuchPad. You know, if you're at a big company and your boss is like, hey, we need to buy something to solve this problem, but, like, procurement makes us get three examples.

Like, we can't just go buy something. We have to, like, you know, like, run a bake off. People are outsourcing a lot of that paperwork to Chatuchiki and particularly to deep research, but even just with regular search.

And it's really good at it, to be honest. Right? Like, it's it's really good at being like, here's your comparison table of, like, different CRM systems or something like that.

Yeah. Make the check boxes focus on what I'm looking for, not what they're selling, you know? Right.

Right. And so for for b to b software companies Yeah. You can imagine.

As a quick note, how do you know? Because you don't directly see the traffic, but like, how how do you know? Yeah.

So there's two parts to it. Right? So there is looking at panel data, which I think is what everybody who's publishing these studies, basically, is doing.

And I, in previous lives, worked in the ad tech. So to the extent the web is maybe less pleasing of a place to be, like, we're all looking for the guy who did this. It was it was me.

You know? And we used just a ton of panel data in that pursuit to do, like, consumer modeling and stuff like that. So, I mean, that's sort of the the secret of all of these studies of, like, what people are doing in the Internet is they generally come from, like, clickstream panel data, which is valuable.

But it also can be misleading because the type of people who are in panels isn't necessarily representative of the whole population. And specifically, it's not necessarily representative of people who are doing high value things like being staff software engineers at Stripe or something like that. So the other thing we've done is we've just done qualitative research.

We've just followed people home, watched them use products. Wow. Ask them, you know, ask the, like, post survey follow ups where somebody's been like, I found you through ChatGPT.

We've been like, what were you doing when you found us? Things of that nature. And so that's where a lot of those b to b software examples come from.

Just to double click on the b to b software thing. I'm sure people ask you this, but I don't think you've covered it yet. What if I try a prompt injection inside of my, you know, feature list page?

Yeah. I mean, it it often works right now. Right?

Like, I don't I I don't think this is a secret. Yeah. So everyone should do it.

I think it it works until it stops working. Right? And I would say, like, there's not a lot of stories of people getting banned for, like, chat speedy search so far, but it's coming.

Right?

I I think, you know, again, like, talking my own book, what I would say is as things get more sophisticated, like black hat stuff tends to get kind of pushed out and penalized, and there's negative consequences to doing it. And then there's some gray hat stuff, which like typically people do and don't talk about. Really, what I would say though about most AI search things in terms of just optimizing how you show up in these answers if you're a business, is I think we're actually in one of these rare windows of time where it's positive sum all the way around.

And what I mean by that is when you look at improving how you show up in chat community answers, most of the time, the problem is not that you were insufficiently glazing yourself in your product description page. A lot of the time, the problem is you're just not being very descriptive about your product in general on your product description page. And so if you provide more information, more context, it helps the model do a better job.

It's gonna have a more accurate comparison table. It's gonna guide the user to a better solution. And so assuming you do a good job providing that context, like, you're gonna be happy, the user's gonna be happy, and ultimately, the platform provider's gonna be happy.

I think at Google and SEO, things often feel sort of, like, pretty zero sum. Everything's competitive and everybody's looking for a trick. There's so much low hanging fruit in this space that I would just say, before you go to that, I would focus on how do you actually serve focus on serving the user.

Right? Serving the user through the AI platform they're using. And just like clear writing, good structured content, adding lots of helpful examples and facts and FAQs makes a huge difference.

But if you want to prompt inject Chat to be in through search, it's it's definitely achievable. And again, I think, like, these systems are, like, one hundredth of the sophistication they'll eventually be. Again, not even talking about the LLMs, just talking about sort of, like, the glue code, right, between, like, the search and web pages and and AI.

And when you say tweaking the content, do you still mean doing that in the traditional formats? Or what about things like, you know, LLMs. Txt?

Are these, like, AI native ways to alternatively serve content? Chat d today, right, is using your existing web pages. So it's using HTML you're serving off your web server.

I know that there's debate about this, but I'd say the evidence is like, Chatrapate is not indexing and it's not retrieving content from LMS. Txt by default. And I think a lot of people who are are a little bit further removed from the odd like, the original audience, like the fast AI guys for LMTSD sort of have mistaken what it's for.

It's great for documentation. It's great if you've actually already written a ton of prose and you're like, how do I load this into my context window more efficiently? As a discoverability tool, I would say it's not moving the needle for most people yet.

But these things can always change. Right? Like Yeah.

Everything's changing day by day. Anything else that you think people think it's good, but it actually doesn't make a difference? What what else would you put in that list?

Oh, man. Embeddings. You know, I think a lot of people are very focused on especially in some of like the SEO optimization community, there's a lot of focus on like understanding embeddings and similarity search and things like that.

With the idea that again, like maybe the search technology is changing. And I think, obviously, embeddings are are very, very useful in general. But I think as a tool to understand how these AI platforms are consuming your content, embeddings aren't that relevant.

You're better off focusing on just, again, having a good structured set of content that makes sense, like, to a human with, like, clean HTML and things like that. Trying to, like, super optimize, like, you know, topic similarity and things like that, I don't think makes much of a difference and may harm things in some cases. I just wanna open up the space to any other practices you see that may be super effective or super ineffective that Okay.

People have got into their heads that, oh, we gotta do this for for a GEO, but, like, it doesn't matter. I mean, I feel like we've covered quite a bit of it. I would just you know, again, I would say, like, clear writing matters a ton.

And then this is I guess we haven't said this on the on the pod yet. So this is one thing definitely people should take away, which is, like, ChatSuite doesn't execute JavaScript. Most of the AI search indexers and retrievers don't execute JavaScript.

So if your content is not rendered on the server side, it's typically not gonna be available. Right? And we see that it trips people up all the time.

And I would just say, I'm perhaps an old fashioned SSG enthusiast. Right? But even if you're using Next.

Js and things like that, we've seen lots of examples with customers where, you know, they've got like a use effect in some page somewhere, and it breaks server side rendering.

Right. The infinite chain.

I don't know. I I think there's good bad versions like everything. Right?

So what I would say is, first off, like, it's just a fact of life that a lot of content, especially on marketing websites, is being produced using AI. Like, that's just like, it's already so prevalent. When you get to scaled programmatic SEO, which is a little bit more controversial, I think that it can be super helpful in some cases if it's done well.

And really when I say done well, what I mean is if it's bringing some kind of insight that actually is particular to you and your company and what you do, and making it easier to consume for AI, right, or for search in general. So if you're just taking content off the public web that's there already, that's already super well represented in AI, and you're remixing it, maybe hey, they'll cite my page instead of this other page. I mean, it works sometimes, but I wouldn't say it's a durable strategy.

We have customers who are doing things where they take, for example, support tickets that are coming they're looking at their support tickets, and they're doing programmatic SEO generation of how to's from the support tickets and putting that on their website. And number one, it's super helpful for users. It's helpful for the support team because they get fewer support questions.

And that content is the almost the exact ideal content you could give to an LLM. Right? Because people are going to chat to and be like, how do I solve this problem?

And it's like, here you go. I think it can be done well, and it can be really helpful in those cases. I think there's a lot of things that work right now in terms of just using AI to remix content and get more scale.

But like everybody has access to these tools. Right?

Yeah. I mean, the ingestion pipeline is is similar. Right?

So, you know, all the practices I mentioned, like, Deep Research also doesn't read JavaScript. Right? It's just quantity.

Right? It's doing more searches, and it follows up the thing that makes deep research really powerful so, like, maybe there's it's good to a taxonomy. There's, regular search, which is like, it does one search.

It gives you the results. It ranks them. It summarizes them.

You get an answer. There's multi search, which we're starting to see more in, like, regular ChatGPT four, and also in AI mode where it just does a bunch of searches simultaneously. And then deep research, what's different about it is that it's sequentially following up with a reasoning model to be like, these sources didn't answer the question.

Let me try something else. And that's really the game changer about how deep deep search works. I think from an optimization perspective, there's not necessarily a ton of fundamental differences.

But what I would say is, like, sometimes more content isn't better. And that's true for me as a user using deep search. Like, I definitely have experiences where I'm like, deep research gives me results that are inferior to just just using regular chat to do research.

Because it's adjusting more content, but the content isn't necessarily, like, contributing to the understanding I'm looking for. And then as a business who is publishing content that's being consumed by this thing, it's like, how consistent is your content? Right?

Do you have outdated things? Is it getting information that contributes to the user being helped and having a helpful understanding of what you do? Or is there outdated and conflicting stuff?

Classic example in that would be pricing. We see cases all the time where people have tons of pages on their site that mention pricing, and some of them are out of date. And the more content Chatbitee is consuming off of your website, the more likely it is to get conflicting answers.

And sometimes people end up with the wrong prices. So I'd say that's something to be mindful of, but I don't think it changes the game a ton in terms of your strategy in the business.

because it's serialized, it's influenced by the previous results. But what I would also say in that situation is like, why not just include the content in the first place? Right?

Rather than having it do a follow-up. Well, you you just can't include everything. Right?

Like, maybe there's a there's there's different branches you could take, so the branching factor is high. Sure. There's limits on context window and things like that.

So, I mean, I think it is I think it is reasonable. But what I would also say is, actually, that's a perfect case for something like programmatic SEO, where you might also benefit from saying, like, let's have more focused pages that describe, like, a complete solution rather than or the complete piece of information for some particular version of a query or version of a persona, rather than sort of it being choose your own adventure. And I think that's where having more technical sophistication on how you manage content and what you show maybe to AI versus versus, like, to to Google Google or or to to regular people can be interesting.

Yeah. I mean and, like, there's tons of, like, LMs dot full TXT's that are, you know, well over the context window of common models. So you're like, is this helping?

I don't know. Again, to me, I'm like, for some of these things, search works pretty well. Like, search over your regular website works pretty well and naturally sort of solves that chunk size problem.

But you do need to have content on your website that's like, that's helpful and targeted to the questions people are trying to ask. Awesome. Any case studies on companies that are doing this amazingly well that people should learn from, or are people still keeping it under wraps?

We definitely have case studies. And I think the ones that are most interesting to me personally, again, are the ones where we're seeing people who are not just getting more traffic. Right?

Like traffic is kind of like the first approximation everybody uses in SEO and and then also in this AI search phase. But people who are actually getting more conversions, more actual business. And so two that I would mention, two really great customers who are both in kind of the dev infrastructure space.

One is Clerk, the user authentication company. And they have they have great docs in general. They're well set up to succeed in AI because of that.

But they've seen a huge lift in AI traffic from sort of like targeted optimizations and like looking at the type of content that AI wants to use and generating more of it. But they've actually seen an even bigger uplift in conversions coming from ChatBudie. So I think the stat is like, they've seen like a six x growth in ChatBudgy traffic, more traffic from ChatBudgy perplexity, but the common set.

But they've seen a nine x lift in conversions. And again, I think that goes back to like, when people are looking like, people are asking like, you know, how do I implement enterprise s o in my app, for example. Right?

It's because they actually have that problem. Like, they're looking for a solution and they're ready to implement. Right?

So the the closer you can get them to actually being able to, like, solve a problem, the higher propensity they have to convert.

I think where we're at right now is, like, we're the we're the feedback and experimentation system. So we know, I can't take credit, basically, is what I'm saying. The team at is great and has been really thoughtful about, like, the types of content they need to create.

They know their audience really well. Right? They're developers.

They have a Discord. They're super engaged with with the people who actually use Clerk every day. So we're providing, I I think, the supporting role of helping them understand what's working and double down on it.

We're not like a content generation company. Right? We don't know their business as well as they do.

They can do a better job generating content. We are, I think, working on helping them put that process more on rails. So creating more structure, being able to run multiple experiments at a time, and ultimately helping them try to figure out how to deliver more technically of that value to the AI platforms.

And that's where maybe some of these other things, we didn't get into it. But obviously, MCTs, NL Web, everybody is wondering what the technical mechanism is gonna be for getting this content into these AI platforms, if it's not just traditional AI search in the future is. So starting to do more work there, which I'd also put under that sort of like agent experience bucket.

But they're the star of the show. And I'd say that's true for all of our customers. So we are a solution people can use to solve this problem.

We're not an agency that comes in and solves it directly. But we do have I'll I'll give a plug here. We do have tons of really great agency customers.

So if you're looking for an agency to do it for you, we can definitely steer you in the right direction. And can you give a a range of, like, just literally okay. Like, you know, I'm a company.

I wanna improve my rankings or optimization.

just to give an idea of what's on the table for for these, like, you know? I mean, I I think it varies a little bit by vertical. Like, DevTools is is is a very good fit for AI.

So I'm not gonna promise that everybody's gonna see a six x uplift in traffic. But there's a lot of low hanging fruit. So I would say we typically see people get double digits improvements in traffic within a month or two if they, you know, if they are actively working to improve.

Right? Updating their website, publishing content.

I would say, by far, in a way, is the thing that people think about as being an AI platform that has the strongest consumer presence and the most durable relationship with consumers. Right? So everything else is kind of a distant second.

Now AI overviews and AI mode, which is brand new, so I don't have great stats on that, obviously are like they're putting being put right So in front of your huge huge traffic. And then Meta AI. Right?

Like Sleeper has published stats on, you know, having 700,000,000, I'm sure more than that now, active users because they're you know, if you do an Instagram search, you end up in Meta AI. You haven't mentioned perplexity, which I think it should I think I think is interesting. Yeah.

Yeah. Perplexity is pretty big. So I would actually say that, like, perplexity is the second biggest AI native search platform after ChatVee.

Wow. And it's got I think more importantly, it's got, like, people who are really passionate about using it. You know what I mean?

I would say that, like, people who are really into Probac City are probably more into it than many of the other options. But it is it is smaller, right, in terms of raw volume. I think what's actually really interesting, and I didn't pull you guys can pull this up the same as I can.

But if you go look app store rankings, for example, I think what's actually more interesting than just looking at how is Chat to Pikachu the number one app in the app store in the category, which mostly has been. Right? What's actually interesting is look at the volatility of it.

And if you look, like, go look back at DeepSeek, look at when Grok first launched a mobile app, things like that. And you can look at similar you can look at similar data from like SimilarWeb, for example. ChatSuite has pretty consistently been very high traffic.

Obviously, the growth has been insane. But in terms of like relative market share, it's been consistently one of the best. And in contrast, we've seen more peaks and troughs with things like Gemini and DeepSea and and Rock and things like that.

So they may well become firmly established, but nobody has this sort of durable relationship with tons of people like ChatSpity does in the space so far. And perplexity though, if you look at it again, in absolute terms, it's lower. But if you look at the consistency of people using it over time, it's really, really strong.

So I would say, like, especially if you are in a category that has an affinity for perplexity, if you're in tech, if you're in maybe subsegments of finance, things like that. Early adopters. Yeah.

You need to pay attention to it. And same thing for Claude. Right?

Like Claude famously, like, way fewer users, like revenue, actually different story in terms of being compared to OpenAI. But people who use Claude are very, very passionate about it for the most part. That's an interesting thing to think about from a strategy perspective.

And I will say I don't think it's Chat strategy is durable, but not infinitely so. Like, if you look at the reaction to Blaze Gate, the reason people, I think, stick with it is because they actually just really like the product. Right?

Which is sometimes under appreciated, I think, in tech. Right? We always talk about platform wars and politics and stuff like that.

But people just really like it. But when people feel maybe a little bit betrayed, like the product's going in the wrong direction, there's a lot of pushback. And so it's gonna be an interesting time to be alive over the next couple years, as it has been so far.

But I I think it's here to stay. Awesome, Robert. This was great.

Anything else we missed or any call to action for people? Are you hiring?

Yeah. I mean, I I would say, I think this is the future, like, of the web. Right?

Like, the future of the web is like you need to be sort of AI compatible and understand how the things you're publishing shows up in these systems. And so just as somebody who's been a web enthusiast for thirty years, because I'm old, don't get caught up in snake oil and investigate what works and do things that make sense. And don't ignore it either.

I would also just say for especially for the latent space audiences, we are definitely hiring. And I think a lot of what we're doing, right, is we're doing research into exactly what I just said, which is understanding how AI and the web kind of interoperate in the future. And like what the future of the web should look like if you're a business who's trying to be in front of customers.

And so if you're a type of person who's interested in helping us figure that out, like, we are definitely hiring. We have a lot of open roles, and we would love to love to talk to you. Awesome.

Thank you, Robert. Thank you so much. Nice to meet guys.