I'm Dominating SEO. If You're Struggling To Get Impressions, Watch This

The new way to do AEO and SEO is via API. And you know what's interesting? We had a call recently with a company that is literally, they do documentation for dev companies.

Okay.

So let's say they're doing, just call it $10 million a year.

Okay.

They raise a lot of money. Let's just say $24 million to do this documentation. Okay. And the interesting thing is they've gotten to that, that level by having like a powered by button at the very bottom of the documentation they do for everyone. Okay. So anyway, my point of saying this is that I think they use an API. So ClickFlow, we have an API as well that people use to generate content with. But I think the way you're going to do it is like people are just going to log into Cloud Code command line interface and just say, hey, can you just do this for me? Can you build this for me? They can plug it into their agents. The agents do the work. The agents could go out there and buy stuff. There's a ramp CLI now. So the agents marketing agents type of thing. So I think most SEO companies now, or AEO companies, whatever you want to call them, the way to do it is via API. And we have the documentation for ClickFlow and we use, we use that, actually use that documentation company for it. But I think it is using API because you need it to plug into your agents to get the work done faster. And if you aren't doing it that way, I feel like, you know, it's not required right now, but I do think it gets work done quicker for you.

Did you see that LinkedIn thread on how they know and how they mark that their content and the stuff that AI is creating, they know that it's AI generated?

You mean like Google? Yeah, I've seen that.

And I'm a big believer that they genuinely do know, you know, I was a believer even before I saw that. I was a believer that they do know that when content is AI generated. Because if you look at all the stats and the data, even though both Eric and I have our own AI content writing tools, it does not rank well. And you could get short-term traffic, but over time we see AI content just not do as well. And it doesn't mean you shouldn't use AI to write content. It means you should use it in different parts of the content writing process.

Yeah.

It's great for ideation, it's great for structure, it's great for research. A lot of the writing, I highly recommend doing it manual and I believe it's going to keep going that way because if AI doesn't care if the content's written by AI and then they crawl it and then use it to create more content and keep learning, it becomes this self-fulfilling prophecy and then it starts hallucinating and they don't want that.

So what we do for ClickFlow, so what I've heard the customers say, so what I've heard from our people working with the customers is that the content that they generate, sometimes they'll just YOLO and let it publish. But similar to how like, like Finn does it with customer service, right? For like, sometimes I have a hard time believing this and I've seen the content quality myself. I'm like, this is really good, right? But they say this is better than any other content generation tool that they've used and that we have a human in the loop, right? So that's what helps. So when they say like the content helps them get more citations and it ranks better, it does. But there's a lot of caveats. There's one, we have a human in the loop. Second, we spend a lot of time on iterating on it. And so that goes back to what you were just saying about Harvey. You can't just let it YOLO on its own. But I do think if we can get to a point where we have a lot of data around it and we can just release our own LLM down the road, like a vertical one, that's like down the road. But that's at least what we're seeing on the ClickFlow side.

Well, we've been seeing something interesting with content. So you know this, a lot of companies are publishing listicles on their own website. If you look at like ChatGPT and when they're doing the searches, I was with Sam from Writesonic. A lot of the prompts now have site: commands. So like ChatGPT will run a site: command on your own website to see the articles you have to see if it's relevant to what people are asking. And a lot of companies are creating articles like the 10 best web design shops, the 10 best— Yeah.

Really well, like a year and a half ago. Yeah.

Project management shops and whatever, CRMs, and they're creating their own pages for the services or products they offer. And what we're seeing is even though it can help you with GEO and helping you do better on ChatGPT, within 6 or so months of creating a lot of those listicles, assuming you do it in quantity, we see it hurt your organic search traffic.

Yeah, I believe it.

So it's just like, We think that's the wrong approach because you're trying to do better in one place at the cost of another channel. And we don't think in the long run, at least at my company NPD, that you should be publishing this content on your own website or even publishing the content because this kind of content is something where it'll help you with the algorithms now, but we don't think it'll help you with the algorithms in the long run because it's just easy to manipulate.

Yeah. Real quick, if acquiring customers has been a struggle for you and you are trying to figure out how AEO works Answer Engine Optimization, or the new version of SEO, how paid works, how all this AI stuff is going to play into your customer acquisition strategy, then check out my ad agency, Single Grain. It's singlegrain.com. And if it looks like it's a good fit, we'll help you with a free marketing plan. So again, go to singlegrain.com and we'll see you on the other side. So businesses can sell directly via Meta and ChatGPT ads. I think we're going to see a lot more of this. That's— we're not saying, by the way, get rid of your website. I think the website's still important because the more information you can give agents to crawl, the better. So documentation around your software, very important in my mind. Whatever other information you have, get it all out there. Do more podcast interviews, get your YouTube channel out there. You know, keep doing what you're doing because that stuff, they need stuff to ground on. It's not going away.

This is a random note. This isn't marketing related, but you want to know what my wife does to try to make us all healthy every single week? What?

Make you wipe your butt with clean toilet paper and organic?

No, but I don't know.

I just bought a bunch of organic toilet paper.

I don't know what my toilet paper is.

Let me tell you what I bought. Go ahead.

Okay. So, what she does is she chops up different vegetables like in different colors because, you know, like radish is a different color than cabbage and all this kind of stuff. And she tries to get all the major vegetables in her body every single week, not every day because it's too hard to get all of them in.

Mm-hmm.

And then that way we have all the different colors and vegetables because she saw some report on how different vegetables have different things for you and the colors are all natural and she just Chops it up so tiny in food like lasagna that you can't see it. You just eat it. That's good.

That's smart. That's a lot of work. What does she use to chop it all?

Okay, her hand.

So let me tell you this. So by the way, we'll move on. Don't worry, guys. We'll bring this back to marketing in a second. So I bought this, okay? Real three-ply soft and strong bamboo toilet paper, and I just started using yesterday. Like 4.6 stars, 4,000 reviews. I saw this on Instagram and I bought it because someone was writing something about the toilet paper used. There's PFAS and all that. 'Cause I was using like the Amazon one, the Charmin one. And it's like, no, you gotta get, you gotta get this if you don't want PFAS in your butt.

What's PFAS?

Forever chemicals.

I didn't know that.

Yeah, so now you know, see? Better for your butt.

Well, typically when we're home, we don't have toilet paper. What, you use your hand? No, our toilets are bidets.

Dude, that's not enough.

And then we have wet wipes.

Okay, yes.

But I don't know what the wet wipes are in. It's toilet paper, but wet.

No, but the wet wipes are made from like bamboo too or something like that. So it's like, mine's plant-based, the Dude Wipes. They're expensive.

We don't use Dude Wipes, but we use another organic brand. I think it's organic for the wet wipes. I'm pretty sure everything in our house is organic, even though it doesn't mean much for food. Yeah, but we have bidets that clean you and then you have the wet wipes on top of that. Sometimes though, the bidets—

we'll just leave it at that. I'm just gonna send you this so you can buy. Okay, guys, let's bring this back to why A/B testing is dyke. So, back to marketing, guys.

Yeah, we're getting close to the end.

So yeah, we are. We still have 14 minutes left. So A/B testing was the gold standard for product decisions for 15 years. The best AI companies abandoned it. So this is from Akash Gupta. For a generation of PMs, experimentation meant designing a controlled test, allocating traffic, waiting 2 weeks for statistical significance, and hoping you had enough sample size to learn something. That loop trained an entire discipline to think in cycles of weeks. Evalves compress the loop to minutes. 3 components: a set of inputs your product needs to handle. Number 2, a task that generates outputs. 3, and a scoring function that produces a number between 0 and 1. You run it on your laptop, no production traffic, no 2-week wait, no data engineering pipeline. The math on what this changes is staggering. Teams running evals are doing 12.8 experiments per day. That's roughly 384 per month. A traditional A/B testing team runs maybe 3. Over a quarter, one team has explored 1,150 variations, the other has explored 9. That learning gap compounds every single week. So, The point of saying this, so he mentioned Ankur Goyal built the eval platform behind Vercel, Replit, Ramp, and Notion, $800 million valuation. He ran an eval from scratch on this episode, went from a score of 0 to 0.75 in under 20 minutes. That's a PM shipping a measurable quality bar before writing a single line of product code. So let me unpack this for people. So Andrej Karpathy, super AI researcher, he released Auto Research. I think these 2 kind of go hand in hand because Auto Research allows you to run compute experiments very quickly, right? AI experimentations. We're talking like every 5 minutes it's running one and he's just leaving his computer on and doing it. And he's found things that he couldn't— he's like, dude, over like 20 years of doing this, like he found a bunch of things that he didn't even know were possible.

Okay.

I think when it comes to evals, evals are just, it's just a simple way of saying, hey, what is defined as a successful test versus a non-successful test? That's all it is. Okay.

Yes.

And then you're just running it over and over, but we're going to see a lot more of this. And depending on what you're doing, if you're sending cold emails or if you're running paid traffic or whatever, You do need a good enough sample size when it comes to marketing. And you can't just, you know, say you're going to do 384. So I think it depends on your data sample size. But now when you set these agentic platforms up or your agents up, you're just going to say, hey, I want you to run these tests and I want you to every week, I want you to run evals. And just so it can recursively improve over time. That's where this is all going. And that's where a lot of this stuff has already gone with AI, but not, it's kind of starting to encroach on marketing.

So this, what he's talking about, we've seen this happen for years. This is, it's new to a lot of people, but it's not new in the Bay Area or the startup world. There's one issue with this model. It only works if you have high volume. If you don't have high volume, you can't do it. I think for most companies who aren't heavily venture-funded startups or large enterprises, they can't leverage this because they don't have volume.

Yep.

A prime example of this is if you're a new entrepreneur, you set up a D2C e-com site, you're doing dropshipping, you're not even creating your own product, you're running Facebook ads and you're getting 5 sales a day and that's it. So 150 a month, you don't have enough conversion volume to run this playbook.

I think what's going to happen, so exactly what we're saying, but I think we're going to be using a lot more synthetic data. In the future?

Well, if you think about, you know, MMM, MMM has been out for ages and it's what people have—

What's MMM?

Median Mix Modeling. Okay, yeah, yeah, yeah.

Right?

So—

I thought you were talking about M&M's.

No, when you think about—

Yep.

And some of the solutions that Google offers and a few of the others, right? Meridian and the list goes on and on. When you think about it, you're taking data from what happened in the past to figure out what's most likely going to happen in the future. And it's saving a lot of time and money. And companies are also starting to look at not just, hey, where are we spending our money and where should we? They're also looking at incrementality in which—

Yeah.

Was this person actually buying because of the ad or were they already on the checkout and going to buy anyways and the ad just took credit? And that's another big problem in marketing as well. Because we spend a lot of money on advertising, but yet was the sale actually caused by, you know, marketing or was it not? And dude, we see this all the time. And the way you see this is not what I'm talking about, incrementality or, you know, causality. It's when you have the executive team just being like, what would happen if we turn off all our ads? Let's try that for a week. Right? That's their way of saying, did the ad actually cause, or does marketing actually cause more sales for us? Or is it just taking credit for sales that we would've already gotten? And it isn't that simple because if you just turn off your advertising and your marketing for a week, a lot of what you're closing in that current week came from people who saw your brand and from advertising and marketing that happened, you know, months ago or a year ago. So it of course isn't that simple, But, you know, when you think about incrementality testing and you think about MMM, because of AI, it's more easier for companies of all sizes to use this stuff while it wasn't possible for smaller organizations in the past.

Yeah, I think what people can learn from this, so what Neil's saying is true, this is not necessarily new on the marketing side, but I think on the PRD side, so a product requirements document, this guy's basically saying that evals are the new PRD. And so when you have a very specific spec-driven document and it shows like it defines what a win and what a loss is, I think this is going to be built in a lot more to whatever agents I'm building, for example, whatever workflows that I'm building. So it's just on top like, hey, I want you to have an eval here, right? That's just going to be built into whatever scaffolding that you have in the future. And that's going to allow us to do these things. Sometimes you might need synthetic data, sometimes you can't do it, right? But I think we are— I think me, for example, I've been required to, we were doing PRDs maybe like a year, year and a half ago and like me, PRD, right? Doesn't make sense. But now evals, when you just build it in, it reduces a lot of noise. That's what I think is going to, a lot more people are going to start doing it that way.

Yeah.

Yeah.

But yeah, with all these changes that's happening with data, you know, not just synthetic data, because I know a lot of corporations are using synthetic data too. And when I'm talking about synthetic data, let's say you're having, you're doing running Facebook ads. and they want you to pass in data on your customers. Well, a lot of corporations these days are passing in synthetic data. So then that way Facebook doesn't have their quote unquote customer data. Facebook hates it because when you don't pass in your real data, it makes their ecosystem not as strong and it doesn't help them for future, you know, companies who are running ads there. But because of technology, you're going to see 2 things. One, you're going to see it easier for startups to get up and running and have the power that a lot of these enterprises had because things like MMM are much more affordable and easier to do. The second thing that you're going to see is it's also easier for companies to leverage things like synthetic data and protect their own first-party data and not pass as much through. So then you're going to have these platforms like Meta and Google not be as effective from a targeting perspective because they're not getting passed in all the data from corporations that they would like.

All right, so this can be a nice final topic for us. So this is also from Akash. So every CEO will be running an OpenCLAW within 12 months. So Mark Zuckerberg, Meta CEO, is building his own in-house. So a couple days ago, right, Jensen Huang stood in front of 30,000 people at GTC and said every company needs an OpenCLAW strategy. So now you have Zuckerberg building a personal CEO agent, And it's a Fortune 5 company, right? And so, you know, a CEO at MetaScale sees maybe 1% of information that determines whether a decision is right or wrong. The other 99% gets filtered through VPs, chiefs of staff, dashboards, and whatever made it into the pre-read. The agent replaces the filter. Think about what a CEO agent actually does. It ingests every product metric, every internal thread, every customer escalation, every competitive intelligence report across every team simultaneously. Then it surfaces the 3 things that actually matter this morning. Before every one-to-one, one-on-one, it pulls that person's team metrics, open headcount, recent launches, and the 2 things they said they'd deliver last quarter. When the CEO asks, what happens to our glasses timeline if we move 200 engineers to AI infra? The agent gives a first-pass answer in minutes instead of a 2-week strategy team exercise. And it never forgets. The person who remembered why the company killed that project in 2019 left 2 years ago. The agent didn't. So Meta employees are already running their own versions, tools called MyClaw and Second Brain. Engineering output is up to Up 30%, power users up 80% year over year. Zuckerberg is doing what his employees are doing, applying it to the highest leverage seat in the company. So this is exactly what I'm doing internally right now. I have everything connected and it's proactive with telling me. It does forget. Don't, guys, don't think this is perfect. Memory is an issue with AI right now. But I do think that if you're applying it at the highest level like this, for example, or even like the way I'm doing it right now, it cuts the noise very quickly. And I can execute a lot faster. And I think we all like to move faster.

I agree with you this. I still have, I don't understand the concept why AI can't figure out the memory issue. It doesn't seem like a big deal. You tell it something once and for some reason it doesn't always follow.

Do you remember everything? You have really good memory.

No, but this is a computer. It should be able to hardcode and not forget unless you tell it otherwise.

You know what a computer's made out of, right?

Yeah.

Sad. Like we conjured it and then we put electricity through. I think it's gonna get better over time and I think the memory problem should be solved, I don't know, maybe in the next year or 2. But I do think just the decisions, like man, it's so crisp now and I can move a lot faster. For example, last week I made that CFO agent and it's like, oh, you have $700,000 in cuts over here. I was like, wait, what?

Yeah.

Found money, man.

Right?

It's great. It's great. I love it. So when I make a copy for you, you can use it for yourself. You can just duplicate it and use it for yourself. You can use your own skills. scaffolding on it. That's my gift to you.

I was at an event a month ago and I met someone who's working Anthropic and they're in charge of coding up a lot of this stuff. And I asked him the memory question and he gave me an explanation on why AI isn't perfect on recalling everything. And it was too complex. I didn't understand it. And I was like, when will it get solved? And because that's what I was really looking for, right? I'm like, I don't really care how you solve it. I don't care about the technical details. Yeah, yeah, yeah. And he's just like, he's like, it's not going to be easy. We don't see it happening in the short run, but it'll get better over the next few years. That was his words, not necessarily being solved in a few years. It'll get better and make the errors less often.

That's what I'm really saying. Like, we expect this to compound over time. And as we talk about this too, like, this is the worst it'll ever be. So I don't know, my eyes continue to burn to the ground every night. And I don't know about you.

My eyes don't burn to the ground every night.

But they do if you use them too much, right?

No.

They don't? No, I never had that issue. You have LASIK, right?

Yeah, I never had that issue.

Yours do.

Yours do. Okay, great.

Noah's does. All right. So Neil's preserving his eyes.

Noah and I are being stupid. But yeah.

Anyway, guys, that is it for today. Please don't forget to rate, review, subscribe, and we'll see you tomorrow.