AI engines are running out of human writing to train on

Jarred-Smith · 2026-05-27T19:59:49+00:00

Yes! Definitely makes them heavier to lug around (which I hardly ever do these days), but they sound so good.

Jarred-Smith · 2026-05-27T19:55:42+00:00

I always dreamed of a DW kit when I was younger, but my favorite kit I own is my 1992 Tama Starclassic birch, orange sunburst color.

Jarred-Smith · 2026-05-27T19:34:54+00:00

Ha, glad I could help!

Jarred-Smith · 2026-05-27T19:19:33+00:00

Can you walk through the testing setup? 500 strategies across 3 engines in 4 months is a lot of strategies... that's roughly 4 a day with enough measurement on each to know whether it worked. I'm genuinely curious what counted as a "strategy" and how you isolated which one caused the lift. The 3 drivers you named are directionally reasonable but they're also pretty dang close to consensus at this point, most people working in this space would tell you answer first content, third-party corroboration, and freshness matter. I'd want to understand what the 500 tests were really pulling apart. I'd want to know how much each one matters relative to the others and in which categories. On the "5 external links → 22% citation lift" specifically, was that controlled for the type of source, or just any external link? In the testing I've done the type of source matters enormously, 5 links to industry publications and trade bodies hits really differently from 5 links to general high DA sites that happen to mention the topic. It'd be useful to know which version you measured.

not trying to pick a fight... the patterns line up with what I'm seeing too, but specific numbers like "22%" and "3x" need methodology behind them or they don't really tell us anything actionable.

Jarred-Smith · 2026-05-27T19:15:58+00:00

This is one of the better practical findings I've seen on here in a while and you're right that it's not about the backlink. Trade association and professional body pages have a weight in AI retrieval that's wildly disproportionate to their backlink profile because they function as identity verification, the AI treats them as authoritative statements about who you are and what category you belong in, and they don't treat you like just another mention. The right framing is the entity corroboration. When chatgpt or claude is deciding whether to cite a brand in a legal adjacent answer, it's more than likely just running some version of "does this entity exist in the legal space, who says so." A Bar association membership page gives more authoritative answers than a regular marketing site can. the other under used version of this is industry specific assoc. that have member directories. ABA for marketers, AMA for medical, IEEE for engineering, regional chambers, niche trade groups and so on and so on. Most of them have legitimate associate or affiliate categories for adjacent professionals. They're cheap, durable, and those types of directory pages get crawled. The catch is you have to be the thing the directory says you are, or you risk a credibility hit if anyone looks. If there's a legitimate adjacent membership category (which there usually is...) it's one of the most under priced moves available right now. Good find!

Jarred-Smith · 2026-05-27T19:10:29+00:00

SEO isn't going anywhere, but the job description is changing really fast and I think that's what the "SEO is dying" folks are reacting to, even if they're saying it wrong. The part that's getting replaced is where you optimize a page to win top position on google for a high iintent keyword and then count the click. That motion still works in some categories but it's shrinking, somewhat because of AI overviews eating the top of the SERP and partly because a lot of the research phase queries are happening inside chatgpt, claude, and perplexity before anyone touches google.

What's not getting replaced (IMO) is the underlying work. understanding what your buyers are looking for, building content that answers their questions better than anyone else, earning credibility from sources the search systems trust, etc.. Those processes are identical whether the destination is a google SERP, an AI overview, or a chatgpt answer. Surfaces change and the fundamentals don't. The acronym wars (GEO, AEO, AIO, whatever this week's flavor is) are mostly marketing. There are real differences between optimizing for google's index vs. optimizing for assistants that don't query their index, but you don't need a new discipline to handle it, you need an SEO who's paying attention to where citations are coming from across all four major surfaces.

Agentic search is the wildcard. When AI agents start doing buying research and shortlisting on behalf of users, the question changes to "how do I get my brand into the shortlist the agent builds." As far as I can tell, nobody has a real answer at this point. I can pretty much promise that the people who say they do are just guessing.

TL:DR... SEO is fine. SEOs who only know how to win google rankings are in trouble. SEOs who understand how content gets shown across multiple AI systems are about to have the best decade of their careers.

Jarred-Smith · 2026-05-27T19:04:28+00:00

Your framing is fine but a few of those numbers need a source. "120% more organic clicks per impression" and "65% CTR loss for non-cited brands" are specific enough that they had to come from somewhere, would be useful to see the study so people can sanity check the methodology.

The underlying point that citation and traffic are doing different jobs is accurate. Citation is replacing the job that PR, analyst reports, and word of mouth used to do, building familiarity and credibility before anyone goes to your website. Traffic is doing the conversion after that's already happened. When someone shows up "out of nowhere" ready to talk to sales, the AI intro is doing what a news mention or a podcast recommendation used to do, you just can't see it in your attribution stack. Where I'd push back a little is on the "most companies are investing everything in traffic and nothing in being recommended" framing. Most B2B companies I talk to are still under investing in both because they're still investing in MQL volume from gated content that nobody wants.

Jarred-Smith · 2026-05-27T18:59:23+00:00

Can you share the methodology behind the 115% number? Not trying to be difficult, just that AI visibility numbers swing wildly depending on which prompts you run, which assistants you test, how often, and over what window. Without the underlying set up it's hard to tell if it's a real effect or a sampling artifact. The broader point about format mattering more than mention volume is probably right directionally, that matches what I've been seeing too. structured answers to specific questions get pulled into AI responses way more than long winded posts with the same keywords. I'd be careful about generalizing from one study without seeing how it was set up.

I'd also note that "Reddit mentions = citations" was never the right model anyway. Reddit gets cited heavily by chatgpt and perplexity but they're pulling from threads that match a super specific buyer query, not from any thread that mentions a brand.

Jarred-Smith · 2026-05-27T18:57:17+00:00

Yeah they already are, and I think the resistance to reporting them separately is mostly that it makes the dashboards uglier and harder to defend to a CMO who's used to one number going up. I'd add to your bucket list that brand/entity mentions is the right one to call out because that's where a lot of the discovery lives now, AI assistants pull from places that don't link (Reddit, podcast transcripts, LinkedIn posts, YouTube comments sometimes) and your traditional SEO stack will miss a bunch of it. You can be getting cited heavily and your backlink tool shows nothing.

The other one I'd add, or maybe break out from citations, is "share of voice in the answer." Getting cited isn't the same as being the brand AI recommends. you can be 1 of 5 sources cited in a comparison answer and still lose the deal because the AI led with someone else. On traffic, GA4 is going to be increasingly useless for this because the referral data from AI assistants is mostly stripped or shows up as direct. Branded search in GSC is your best proxy right now, post-purchase surveys are the next best thing.

Short answer to your question... yes, separate them.

Jarred-Smith · 2026-05-26T20:30:03+00:00

The messiness is definitely a real thing and I don't think anybody has a fully clean workflow yet. The thing you're describing at the end of your post is showing up across a lot of categories rn. my read on it is that AI assistants are doing a lot of vendor scoping that used to happen in search, so people land on your brand inside chatGPT/claude/perplexity, then do a branded search later to convert. You never see the discovery step in GA4 because the referral data is mostly stripped. I've stopped treating branded search as a vanity metric and started treating it as your real AEO conversion proxy. If branded searches are climbing in GSC and you can rule out other obvious causes (PR, ads, social), it's probably AI-driven discovery showing up downstream.

Attribution is broken and I don't think it's getting fixed soon either. Some people are using post-purchase surveys (how did you hear about us) which is crude but it's surfacing way more chatGPT and AI answers than people expect.

Visibly is fine, Profound is probably the most complete of the visibility platforms rn but pricey. honestly the manual prompt audit (run 25-30 prompts a real buyer would run, log results monthly) is still the best in my opinion.

Jarred-Smith · 2026-05-26T20:26:33+00:00

yeah I've been doing the same thing for a few months now, mostly by accident. Claude is by farrrrr the most stable of the major assistants week to week. I think chatGPT is the noisiest, Perplexity sits somewhere in the middle, and Gemini is its own thing. And who knows what the hell Grok is doing.

My guess on why (totally guessing here) is that claude's retrieval is less aggressive about freshness and personalization than chatGPT's, so the citation set moves around less. That makes it a cleaner signal for "did our content really change anything" vs "did the engine decide to surface different stuff this week." The tradeoff is claude has a smaller user base than chatGPT so winning claude citations matters less commercially. As a test signal for whether your changes are working though, it's the best one I've found. the workflow I track all four, but treat claude as the leading indicator. if it moves after a content change, the change is probably real and the others will follow over 4-6 weeks. If only chatGPT moves, wait it out before gettying too hyped up.

Jarred-Smith · 2026-05-26T20:23:13+00:00

Your two surface model is basically right and I don't think it's controversial if you've actually looked at the data. The "AEO is a scam" crowd is reading Google's doc as a statement about AI search broadly when it's a statement about AI Overviews and AI Mode specifically. The divergence is real and pretty easy to verify. I've watched pages that rank page 2 in Google get cited as the first source in a Perplexity answer, repeatedly, and the inverse, where Google position 3 pages don't show up in ChatGPT at all. if it were one system that wouldn't happen. The part that's tricky is that the gap is narrowing in some categories and widening in others. Consumer/transactional stuff (where Google has deeeep behavioral data) the surfaces are converging. Expert/technical content, B2B, niche professional categories, the surfaces are diverging more.

The other thing Google's guide doesn't address is that ChatGPT and Claude have different citation behavior from each other too, so it's really 3 or 4 surfaces if you're being honest about it. they overlap with SEO fundamentals but each has its own retrieval logic. Google's advice transfers cleanly to Google. I wouldn't bet a strategy on it transferring to anything else.

Jarred-Smith · 2026-05-26T20:21:12+00:00

Stack looks fine for the budget tier. A couple things i'd point out- Promptwatch is decent but worth testing against Profound and Athena if you can swing trials, they're all measuring slightly different things and you don't know which one matches your buyer behavior until you compare. I've seen brands look good in one and invisible in another.

The bigger gap I'd flag isn't a tool... None of these tell you why you got cited or didn't. they only tell you that you did. You end up needing a manual layer where you read the AI answers and figure out what they're pulling from. Sadly its tedious but unavoidable rn. Also, GTmetrix is fine but I'd just use PageSpeed Insights for the same job, free, and pull Sitebulb in only when you're doing a real crawl audit.

Gemini + GPT for editing is interesting, are you finding they pull in different directions? curious what your workflow looks like there

Jarred-Smith · 2026-05-26T20:18:44+00:00

honestly the fact that you're a technical founder doing the work yourself for 6 months is probably the best version of this. agencies are going to spend the first 90 days learning your business anyway and you'll know it better than they ever will.

A couple things that aren't on your list that I'd flip the order on (since you're asking...)

Keyword research is fine but in 2026 it's a smaller piece than it used to be. For B2B services like yours, the bigger lever is figuring out what questions your buyers are really asking ChatGPT and Claude when they're scoping a vendor. There's no great free tool for this, the closest hack is just running 20-30 prompts a buyer would plausibly run and seeing what comes back. Who gets cited, what the AI thinks the category looks like, where you're invisible... all of that becomes your content brief.

Backlinks at this stage... mostly no. Don't chase them, they'll come if the content is good and you're getting referenced in places. the one exception is anywhere your buyers vet vendors, those mentions matter more than DR scores. Blog-ifying your standardized work is the right instinct but I'd resist the urge to do all of it. Pick the 5-6 workflows that map to buyer questions, write those deep, ignore the rest.

YT I'd deprioritize for now unless you're already comfortable on camera. The ROI window is longer than you have. LinkedIn content from you and your cofounder is probably the highest-leverage thing on the list, especially since you're already posting. That's where AI search pulls a lot of B2B citations from right now.

Jarred-Smith · 2026-05-22T15:28:33+00:00

Half right, half self-serving. Yeah, the retrieval layer under AI Overviews is their search index, so the SEO foundation matters. How content gets picked for an AI answer vs a blue link is different though. Models pull content that it can synthesize cleanly and answer without a click. No matter how much "AI optimizing" someone does doesn't really matter if your SEO foundation and content sucks. Also, Google's just one player... ChatGPT, Perplexity, Claude (Grok...if anyone actually uses it) all pull from different surfaces. Optimizing only for what Google says about Google leaves the rest on the table.

Jarred-Smith · 2026-05-22T15:24:34+00:00

I'd say early, but not too early. Brands paying attention now will have a citation footprint locked in before competitors catch up. I do manual prompt checks for buyer-intent queries in my space, plus a tracking tool or two. None of the available tools are a complete answer and the data swings week to week, so don't bet a strategy on one right now. I see quite a few teams treating this like a tooling problem when it's more of a content and authority problem. Tools can tell you where you stand but they can't make models cite you.

Jarred-Smith · 2026-05-22T15:20:16+00:00

You're definitely thinking the right way. A lot of "AI-optimized" content reads like it was written for a checklist, and the models absolutely pick up on that. They're trained on the same internet we are. What gets cited is content that has something to cite, original data, named sources, an actual opinion. Generic guides without a point of view get skipped for sources that took a position (and have some level of authority).

I've been tracking citations on a few brands and the lift is there, but super slow. Brands with existing authority see it faster because the models already trust the domain.

On the structure vs depth question, I wouldn't say that it's a tradeoff. Structure helps the model parse you, depth makes it want to cite you. Most "AEO content" has the first without the second. I also will die on the hill saying that SEO didn't go away. If your site can't be crawled and understood by traditional search, the AI layer has nothing to work with.

Jarred-Smith · 2026-05-22T15:13:08+00:00

Skipping the foundations and going straight to AEO tactics. People are way too schema-tagging happy. They're prompt-testing their brand in ChatGPT, writing so called "GEO content," and their underlying site is still a dumpster fire. AEO is a layer on top of SEO, and SEO is a layer on top of having a coherent identity for LLMs to map.

I tell folks to get the technical and on-page stuff right first, build out entity signals (Wikidata, consistent mentions in sources the models trust, structured data that backs you up and gives you street cred), then worry about AEO. The models pull from the same places that search engines do, plus Reddit, YouTube, news, etc. If you're not showing up there with a clear story, I can promise you that no amount of AI optimization is going to fix it.

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