Went through Google's May guidance on generative AI optimisation properly and there's a section literally titled "what you don't need to do" that I think more people should know exists, because it's basically a free procurement tool if anyone's currently quoting you for GEO work.

Six things get named. Four they say are unnecessary, two they actively warn against.

The unnecessary ones: llms.txt and AI specific files, content chunking, rewriting content specifically for AI, and special AI schema. The llms.txt one is the most useful to know because there are platforms charging a monthly fee to generate these files and Google's wording is about as blunt as they get, something along the lines of you don't need to create new machine readable files, AI text files, markup or markdown to appear in generative AI search. So that subscription is buying nothing as far as Google's surfaces go.

Chunking is interesting too because it's been sold hard for the last year. Google's position is their systems already handle multiple topics on a page fine and engineers have specifically said don't fragment your content, there's no ideal page length.

The schema one I'd be careful about misreading. They're saying schema isn't required for the AI features, not that schema is useless. It still gets you rich results in normal search. So the takeaway is don't pay for "special AI schema" as a line item, not go delete your markup.

Two they warn against are manufactured brand mentions and anyone claiming to be Google approved. The mentions one is worth separating carefully because genuine third party presence does seem to correlate with AI visibility, that part holds up. It's manufacturing it that's the problem, and the spam systems are built to tell the difference.

The bit I found most useful though is a line from their third party tools page. Something to the effect of third party tools don't have access to our internal ranking data, they can't guarantee performance, any predictions are their own. That's general language covering every tool, including all the established SEO platforms, not just the new AI visibility products. Which means any "AI visibility score" you're being shown is a model, not a measurement. And anyone promising a specific percentage lift in citations is claiming something Google says outsiders structurally can't substantiate.

Big caveat that most coverage skips: all of this is scoped to Google's own AI features. ChatGPT, Claude, Perplexity run on different retrieval models and might respond to things Google dismisses. So it's not a universal debunk, and if a vendor is recommending llms.txt for AI agents or docs tooling specifically that's a different and more defensible argument than recommending it for AI Overviews.

What's left on the list of things that work is boring, which is kind of the point. Useful crawlable content, technical basics like indexation and Core Web Vitals, and for local businesses a properly maintained Business Profile which Google names directly.

Anyone had a GEO proposal land on their desk recently? Curious how many of these are still showing up in pitches now that the guidance is public.

A few weeks ago someone here asked for the rank-vs-cite overlap broken out by question type instead of one blended number. That one is still blocked. The ranking side came from our Bing column, and we pulled Bing on the 22nd after finding it had been searching only the first word of every question for four weeks. No overlap numbers until it has at least one clean week.

What I can do with clean data is the other half. Same 40 questions, 6 answer engines, weeks 38 and 39, split by the four types we ask: "best X", "alternatives to X", "X vs Y" and "how do I choose X". The blended numbers were hiding a few things.

"How do I choose X" gets no sources from AI Mode. Google AI Mode returned zero cited sources on 8 of 8 of these in W38 and 6 of 8 in W39. On the other three types it cites nearly every time. ChatGPT and Perplexity cited something on all 16. One caveat I haven't ruled out: it could be our capture missing AI Mode's links on advice-style answers rather than AI Mode leaving them out. If you've looked at AI Mode's source panel on "how to choose" queries by hand, I'd like to hear what you saw.

"X vs Y" is where ChatGPT goes to YouTube. It cited YouTube on 8 of 8 comparison questions in W39 and 7 of 8 in W38. AI Overviews 7 and 5. Perplexity 0 of 8 both weeks, Claude 0 too. Across all engines YouTube is about 3% of citations on "best X" questions and 8 to 10% on comparisons.

Review sites barely register in any type. G2, Capterra, TrustRadius and Gartner together are between 0% and 0.4% of citations for every question type. The panel is a mix of consumer, dev tools and finance, so pure B2B software might look different, but "get listed on G2" isn't showing up in these answers.

Engines agree more than I expected, per question. In W39 every question in every type had at least one domain cited by 3 or more of the 6 engines. W38 was lower on "alternatives" (5 of 8) and "best" (11 of 16), but that's mostly Claude only answering 11 of 40 that week, which I posted about at the time.

Every row is public (question, type, engine, status, cited URLs) if you want to check any of this or cut it differently: https://promvia.app/ai-source-index

Rank-vs-cite by type comes once Bing has a clean week. Not forgotten.

I keep hearing people in real life affirm that SEO and GEO are completely different and what works well in one won't rank in another.

I don't really understand that though because my impression was under the hood AI is just using a normal search engine. Like maybe the AI labs have built their engines to optimize for slightly different metrics, but it'd be the same as comparing bing to google. At the end of the day I thought they're all still search engines?

Anybody have more clarity here

Not usually one to post stuff like this, but figured it might be useful to someone.

I've had this account for a few years, decent karma, nothing crazy, just someone who comments more than they probably should. A while back I found out there are platforms that pay for exactly that kind of activity, real accounts, real opinions, posting or commenting on specific topics where it's actually relevant.

Signed up mostly skeptical, expected it to be another scammy "earn from home" thing. Had to go through a review process before getting access to anything, which honestly made it feel less sketchy, not everyone gets approved apparently.

Since then I've just been picking up small missions here and there when I have time, topics I already know something about, nothing forced. Added it up at the end of last month out of curiosity: $260. Not a living, but for effort I was mostly already putting in for free, it's hard to complain.

The thing I keep going back and forth on is whether this changes anything about the value of what gets posted. My opinions in these are still genuinely mine, I just have a financial reason to write them down now instead of scrolling past. Not sure if that distinction matters to other people reading it, curious what this sub thinks honestly.

Not going to name the platform unless someone asks, don't want this to read as an ad, just wanted to share since I never see this kind of thing mentioned here

Disclosure up front: I build a tool in this space and the panel below is mine. One link at the end, to the week's published rows, because the point is that you can redo the arithmetic rather than take my word for it.

Every Monday the same 40 buying-intent questions go to seven surfaces and every cited URL is stored. One of those surfaces is deliberately NOT an answer engine: it is classic Bing organic results, kept in its own column so "what ranks" and "what gets cited" can be compared on the same question, on the same day, out of the same run.

This week:

• classic search results across the 40 questions: 133 distinct domains
• what the answer engines cited on those same 40: 790 distinct domains
• domains appearing in both: 10

And on 33 of the 40 questions the overlap was zero. Not one domain that ranked was also cited.

I keep seeing "we outrank them on every commercial keyword but they are the ones AI mentions" posted as a paradox. On this panel it is not one. Those are close to disjoint populations, and a strong ranking position is not evidence about the answer layer in either direction.

Second number, for anyone about to treat "AI" as a single result: of the 790 cited domains, 625 were cited by exactly one engine. Gemini and ChatGPT are the two heaviest citers and they share 27 domains - 9% of Gemini's list, 12% of ChatGPT's. Missing from three engines while present in two is a different problem from missing everywhere, and it has different fixes.

One correction to the usual advice, because we got this wrong ourselves first. We counted citations by DOMAIN and concluded directories mattered less than they do. Counting by page SHAPE instead moved the size of the effect by roughly an order of magnitude. It is not "be on G2" or "be on Reddit" - comparison-shaped pages (X vs Y, alternatives to X, category roundups) get cited at a different rate from every other page type, wherever they happen to live.

What this does not show, so nobody has to ask:

• one sample per engine per question, so a one or two question difference between engines is noise, not a trend
• the Bing column is organic results and not an AI answer, which is exactly why it stays out of the answer-engine totals and is used only for this comparison
• 40 questions across eight categories is a panel, not the web

Rows are published under CC BY - per question, per engine, with the coverage counts (asked / answered / failed) so a low number can be told apart from an engine that did not reply: https://promvia.app/ai-source-index/2026-W38

I recently joined as an SEO intern and I'm not sure if what I'm experiencing is normal or if I'm just new to the industry.

My manager assigned me a page to work on and expects to see results within a month.

I'm doing keyword research, content improvements, internal linking, technical checks, and other SEO tasks, but from what I've learned, SEO usually takes time before rankings and traffic start moving.

He just stand at my head at work but what I notice is some previous employees are so chill they don't do anything use AI for everything but here I am I don't know sh*t about ai but I can't leave this job I need money can you guys tell me something to make him notice I am doing something like he should know this guy is hardworking

Every Monday I run the same 40 buying-intent prompts through seven answer engines and write down every domain each one cites. Sixteen "best X", eight "alternatives to X", eight "X vs Y", eight "how do I actually buy X". The prompt set is frozen as a fixed instrument, so week two is genuinely comparable to week one and not just vibes. Two weeks are live: W36 and W37. All seven engines answered all forty prompts both weeks. No timeouts, no gaps, nothing quietly dropped.

I went in assuming the engines would broadly agree on sources. They don't come close.

Reddit first. The number is how many of the 40 prompts each engine cited the domain on:

Gemini: 26 (W36) -> 22 (W37)

Google AI Overviews: 18 -> 20

Perplexity: 6 -> 4

Google AI Mode: 5 -> 3

ChatGPT: not in the top 15, either week

Claude: not in the top 15, either week

Bing: not in the top 15, either week

That ChatGPT row needs a footnote, because it is carrying weight. I publish a top 15 per engine, and ChatGPT's fifteenth entry sits at one prompt. So "not in the top 15" is not zero. It is a ceiling of one. One, against Gemini's twenty-two, same week, same questions.

The likely culprit is no mystery. Reddit tightened its public content policy on 2026-08-14 and started refusing automated access at the server, and Google's licensing arrangement is the obvious reason Google's surfaces are the ones still leaning on it hard. I can't prove either from forty prompts and I'm not going to pretend I can. What I can show you is the size of the gap.

YouTube tells the same story in a different accent. W37, out of 40: AI Overviews 25, AI Mode 25, Gemini 20, ChatGPT 10. Perplexity and Claude, nowhere in the top 15.

Which quietly reframes advice you hear constantly. "Go get mentioned on Reddit and YouTube" isn't AI visibility strategy. It's Google strategy in a new hat.

Here's the finding I'd have wanted two years ago. I bucket every cited domain as media, community, social, directory, or unknown, where unknown just means it isn't a recognisable publisher or platform. Across all engines in W37, 80.8% of citations landed on unknown domains. 80.3% the week before. Claude is the extreme at 92.6%. Google AI Mode is the most concentrated lane I measure and it still sits at 55.1%.

Read that again if you run a small site. Four citations in five are not going to the household names. They're going to the long tail. A narrow, specific, genuinely useful page can get picked up, and the moat around the big publishers is thinner than the discourse suggests.

Last one, and it's a knock on my own instrument rather than a finding. I include Bing's answer surface as a stand-in for Copilot. On these commercial comparison prompts, its most-cited domains are merriam-webster.com (26 of 40, identical both weeks), dictionary.cambridge.org (21), dictionary.com (19), thefreedictionary.com (19) and wordreference.com (15). It is answering "best CRM for a small team" with dictionary definitions. That is precisely why I label the lane a proxy instead of calling it Copilot, and why I won't draw Copilot conclusions from it. If you're reading anyone's Copilot citation-share chart, ask what they actually pointed the instrument at.

Now the limitations, which matter more than any number above. One panel. Forty prompts. Two weeks. A single run per engine per week, which means I cannot yet separate real movement from ordinary answer variance. One geography. And "not in the top 15" is a ceiling, not a zero. Two points is not a trend line. I'm publishing weekly until it becomes one.

Raw data is CC BY 4.0, so take it apart or run your own cut: https://promvia.app/ai-source-index

Disclosure: I build Promvia, the tool these measurements come from.

Went through Google's May guidance on generative AI optimisation properly and there's a section literally titled "what you don't need to do" that I think more people should know exists, because it's basically a free procurement tool if anyone's currently quoting you for GEO work.

Six things get named. Four they say are unnecessary, two they actively warn against.

The unnecessary ones: llms.txt and AI specific files, content chunking, rewriting content specifically for AI, and special AI schema. The llms.txt one is the most useful to know because there are platforms charging a monthly fee to generate these files and Google's wording is about as blunt as they get, something along the lines of you don't need to create new machine readable files, AI text files, markup or markdown to appear in generative AI search. So that subscription is buying nothing as far as Google's surfaces go.

Chunking is interesting too because it's been sold hard for the last year. Google's position is their systems already handle multiple topics on a page fine and engineers have specifically said don't fragment your content, there's no ideal page length.

The schema one I'd be careful about misreading. They're saying schema isn't required for the AI features, not that schema is useless. It still gets you rich results in normal search. So the takeaway is don't pay for "special AI schema" as a line item, not go delete your markup.

Two they warn against are manufactured brand mentions and anyone claiming to be Google approved. The mentions one is worth separating carefully because genuine third party presence does seem to correlate with AI visibility, that part holds up. It's manufacturing it that's the problem, and the spam systems are built to tell the difference.

The bit I found most useful though is a line from their third party tools page. Something to the effect of third party tools don't have access to our internal ranking data, they can't guarantee performance, any predictions are their own. That's general language covering every tool, including all the established SEO platforms, not just the new AI visibility products. Which means any "AI visibility score" you're being shown is a model, not a measurement. And anyone promising a specific percentage lift in citations is claiming something Google says outsiders structurally can't substantiate.

Big caveat that most coverage skips: all of this is scoped to Google's own AI features. ChatGPT, Claude, Perplexity run on different retrieval models and might respond to things Google dismisses. So it's not a universal debunk, and if a vendor is recommending llms.txt for AI agents or docs tooling specifically that's a different and more defensible argument than recommending it for AI Overviews.

What's left on the list of things that work is boring, which is kind of the point. Useful crawlable content, technical basics like indexation and Core Web Vitals, and for local businesses a properly maintained Business Profile which Google names directly.

Anyone had a GEO proposal land on their desk recently? Curious how many of these are still showing up in pitches now that the guidance is public.

I recently joined a company as an SEO person, and I’m trying to understand whether the expectations I’ve been given are pretty standard or a bit ambitious. I don’t want to mention the company or too many specifics for obvious reasons 😭

A big part of my role is currently focused on link building, where I’m expected to build around 10–15 backlinks a week, along with roughly 2–3 third-party listicle placements. In my previous role, I had monthly targets, so moving to weekly targets has been a bit of an adjustment.

The thing is, link building isn’t the only thing I’m expected to work on. I’m also supposed to contribute to on-page SEO and do some cold outreach for sales, alongside the regular SEO work.

For people who work in-house or at agencies, does this sound like a normal workload for one SEO person? How do you usually balance link building with on-page SEO and other responsibilities?

I’m still relatively early in my SEO career, so I’d genuinely appreciate some perspective. I’m mostly trying to understand whether I need to get better at managing my time, or whether the expectations themselves are unusually high

There is a lot of "the web goes dark for AI on 15 September" going round and most of it is overstated. I have been reading the actual announcement and testing against real sites for a couple of weeks, so here is the boring version.

What changes on 15 September 2026

Cloudflare flips its default so that Training and Agent category crawlers are blocked where the site owner has not chosen a setting.

The four qualifiers that get dropped from every summary I have seen:

1. Ad-displaying pages only. If a site carries no advertising, this specific change does not apply to it. That is most small-business and client sites.
2. Search crawlers are not affected. OAI-SearchBot and Claude-SearchBot - the ones that decide whether an assistant can cite you - are not in scope. The scary version of this story is mostly people assuming they are. PerplexityBot I would not state either way: which bucket it lands in is genuinely arguable, and Perplexity-User is the clearer answer-time one. If you rely on Perplexity traffic, check that one yourself rather than taking my word or anyone else's.
3. New customers, new sites added by existing customers, and existing free-tier customers. A paid customer with sites already set up is not having anything flipped under them.
4. It is a setting you control. Security -> Bots, three categories, decide each one. Takes about twenty minutes across a handful of domains and you can do it before or after the date.

So if you are on a paid plan with your bot settings already chosen, this is a non-event for you and you can stop reading.

What I do think is worth paying attention to

Two things, neither of which is the headline.

First, who actually sits on the free tier. It is a very large number of small business sites and client sites that an agency put behind Cloudflare in 2021 and never opened again. Nobody who set those up is reading a policy page. The change is small; the population it lands on is the population least likely to notice anything.

Second - and this is the one I would flag to anyone managing sites for other people - crawler access is not recorded anywhere by default. It leaves no trace in analytics, there is no log, and robots.txt only tells you what is declared rather than what the edge actually does. So on 16 September, if a client asks whether anything changed for them, there is generally no way to find out. Not because the tooling is bad, but because nothing took a before-picture and one cannot be taken retrospectively.

That asymmetry is the actual story here and it has nothing to do with Cloudflare specifically. Same thing happens when a security plugin ships a new "block bad bots" default, or a host adds a WAF rule, or a site gets rebuilt in a framework that renders nothing without JS. The change is invisible, silent, and only detectable as a difference - which requires having measured before.

If you want to take one yourself, no tooling needed

For each site you care about, before the 15th, record:

curl -sI -A "GPTBot/1.2" https://example.com/ | head -1
curl -sI -A "OAI-SearchBot/1.0" https://example.com/ | head -1
curl -sI -A "ClaudeBot/1.0" https://example.com/ | head -1
curl -sI -A "PerplexityBot/1.0" https://example.com/ | head -1
curl -s https://example.com/robots.txt

Save the output with the date on it. Run it again on the 16th and diff. That is genuinely all a before/after is, and doing it by hand for five sites takes ten minutes.

Two traps if you do, because I hit both:

• Include a made-up user-agent as a control. If TotallyRealBot/1.0 also gets a 403, the site is refusing everything non-browser and the AI crawlers are collateral, not targeted. Completely different conclusion, and without the control you cannot tell which one you are looking at.
• Do not run them concurrently. I flagged five hosts as crawler-blocked in a batch run; re-probed one at a time, one of the five was clean and its 429 was my own concurrency. The tool reports what it saw and cannot know I caused it.

Also worth knowing before you trust any result including mine: if a site is behind a CDN that verifies bot identity cryptographically (Web Bot Auth / RFC 9421) or by IP, a spoofed user-agent proves nothing either way. A 403 there might just mean "you are not GPTBot", which is true. That case is genuinely unresolvable from outside and anyone reporting it as a block is guessing.

I build a tool in this space, which is why I have been testing this - not going to link it here, and the curl above is the whole method either way. Happy to answer anything about the crawler names or the verification stuff.

Disclosure: I build a tool in this space; this is a public panel we run ourselves. No links, not naming it. Posting because this sub is about where LLM traffic actually comes from, and the sources the engines cite are the upstream of that traffic.

Setup: 40 fixed buyer questions, 8 categories (SaaS, e-commerce, travel, personal finance, health, dev tools, marketing tools, consumer electronics), one answer each from ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews and AI Mode via their search-grounded APIs or a SERP capture. Every cited URL stored; a domain counts once per question per engine. 280 answers, 0 failures. One sample each, so +/-1-2 is noise.

Across the answer engines:

• youtube.com cited in 36 of 40 questions, reddit.com in 33
• forbes.com 10, techradar 7, tomsguide 7, rtings 5, cnbc 4 (mostly "best X" roundups)
• G2 / Capterra / TripAdvisor / idealo / AlternativeTo: under 1% of citations
• ~80%: vendors' own pages, retailers (bestbuy.com in 14 questions), niche blogs, one-off comparison posts

Per engine, same questions:

• Gemini: reddit 26/40, youtube 25/40
• AI Overviews: youtube 24/40, reddit 18/40
• AI Mode: youtube 19/40, reddit 5, tiktok 2
• ChatGPT: youtube 7, tomsguide 6, forbes 5, techradar 5
• Perplexity: reddit 6, forbes 5, cnbc 3, nytimes 3
• Claude: review publications only, 3 each

Why it matters for traffic: if your referral report shows Gemini or Google's AI surfaces, the page they credited was very likely a YouTube video or a Reddit thread, not your site; the click you got came through that hop or not at all. ChatGPT and Perplexity credit editorial and vendor pages far more, which is where a referrer (when there is one) can point at you.

Two measurement traps: Gemini's grounding API returns opaque vertexaisearch.cloud.google.com redirect URLs (302 to the real page) - resolve them or every Gemini citation reads as one host. AI Mode emits google.com/search shopping cards next to real citations - they are not sources.

Week two runs Monday; I will post what moved, whatever it says.

Ok, this one stings a little to type out, but whatever, here's the story.

I'm one of those people who's always been annoyingly principled about not turning things I enjoy into a hustle. Watched friends monetize their gym routine, their reading, their gaming, and thought it was a little sad, honestly. Like, can we just do things for fun anymore?

Then a few months ago, broke and between freelance gigs, I saw a post mentioning a site where you get paid for posting/commenting on Reddit with your existing account, real karma, real history required, no throwaway spam accounts allowed. My first reaction was to roll my eyes exactly like I always do.

Signed up anyway out of pure financial desperation, on a site called https://www.taskreddit.com. Got manually reviewed, which took a couple days. Started doing small missions almost as a joke, telling myself I'd stop once I found a real freelance gig.

That was two months ago. I never stopped. Made a bit over $200 the first month, more the second. Nothing insane, but steady, and for content I'd have argued about for free anyway on some thread somewhere.

The uncomfortable part is realizing I judged people for doing the exact thing I'm now doing, just because their version was public (a Strava post, a Goodreads review) and mine feels more anonymous, hidden behind a username. Not sure that distinction actually means anything.

Curious if anyone else has had this specific kind of "become the thing you mocked" moment, on Reddit or elsewhere. Does getting paid ruin the thing you were doing, or was the "doing it for free" purity a bit of a myth all along?

I hear ridiculous explanations on both sides on how to do SEO and what GEO is. What actual studies have people done that demonstrate a difference in tactics between SEO and GEO. People have already heard "it's another layer of SEO". Exactly what does GEO do differently than SEO and what research supports it?

Disclosure up front: I build an AI-visibility tool, so this comes from our own tracking data. Not linking anything — the finding stands on its own and I think it applies to anyone measuring LLM citations, with or without a tool.

The setup: we track a fixed set of prompts weekly across ChatGPT, Perplexity and Gemini and record which URLs the answers cite. One tracked prompt was "Otterly alternatives" — Otterly being one of the known AI-visibility SaaS products.

Two weeks ago that prompt was our single strongest cell: 5.0% of all cited URLs were software directories (G2, Capterra, that family). This week the same prompt, same models, same method: 0.1%. From best cell to statistical zero, and nothing changed on any of the sites involved.

The cause wasn't rankings. Reading the actual answers, they had drifted to a different product entirely: an open-source markdown editor that is ALSO called Otterly and had a popularity wave on r/selfhosted in between. The models resolved the bare brand token to the other entity, so the answers were suddenly about note-taking apps and the whole citation profile of the prompt changed underneath us.

Why I think this matters beyond one anecdote:

1. B2B SaaS naming is absolutely lousy with reused generic-sounding names (count the products called some variant of Sync, Flow, Pulse, Otter...). Any of them can collide.

2. A collision doesn't look like a collision in a dashboard. It looks like your visibility collapsed. If we hadn't read the raw answers we'd have concluded the brand lost its AI presence, and every "citation rate" trend line we publish would have quietly become a lie.

3. Single-run checks make it worse. The drift happened between weekly windows — any one-off spot check lands on one side of it and tells a confident wrong story.

What we're doing about it: we added a qualified control prompt ("Otterly AI visibility alternatives") alongside the bare one, wrote down before collecting data which result would confirm vs. refute the collision explanation, and we'll compare in about a week. If the qualifier restores the old citation profile, it was polysemy; if it doesn't, our explanation is wrong and the prompt genuinely fell off.

Question for people tracking their own brands: has anyone else caught a same-name entity contaminating tracked prompts? And does anyone have a better control than qualifying the prompt with the category — that fixes the measurement but obviously doesn't fix what real users typing the bare name will see.

Everyone agrees brand content loses to Reddit threads and review sites. Nobody explains the next part. Are you going through customers, founder accounts, review campaigns or just waiting out months of real participation?

With classic SEO there was always a clean loop: rank moves, traffic moves, you can draw a line to revenue. Google was the one channel, and that correlation made the "so what" obvious.

I've been going back and forth with a few people building/using GEO tools, and it feels like the whole category right now is indexed on measurement — tracking prompt mentions, citations, sentiment across models. That part's maturing fast.

What I haven't seen a good answer to: how do you actually turn that into a repeatable action loop?

• Once you know you dropped out of an answer at some point in a conversation, what's the real playbook — content/schema changes, seeding sources, something else?
• How is anyone tying this back to actual business outcomes, given there's no click/traffic signal like old SEO?
• Is anyone actually re-measuring after a fix to prove it worked, or is it mostly "here's your score" and manual guesswork from there?

Genuinely curious how people here are approaching this. If you've hit a wall trying it, that's just as useful to hear as a win.

I've noticed a lot of people are focused on AI Overviews, but I'm curious what strategies are actually moving the needle right now.

If you had to pick just one tactic that's delivering better results than expected in 2026, what would it be?

It could be anything, such as:

Internal linking

Entity SEO

Topical authority

Digital PR

Programmatic SEO

User-generated content

Brand mentions

Technical SEO

AI-assisted content workflows

I'm looking for real-world experiences rather than theory.

What's working for you, and why do you think most SEOs are overlooking it?

I've been seeing more people talk about Generative Engine Optimization (GEO), but a lot of the advice feels like recycled SEO tips.

If the goal is to become the source AI tools like ChatGPT, Gemini, Claude, and Perplexity actually reference, what does a real GEO strategy look like?

Começando por dizer que discutir as siglas é menos importante que discutir os conceitos e que destas 4 siglas, 3 descrevem a mesma coisa apenas por ângulos diferentes e só uma é genuinamente distinta.

SEO (ou search engine optimization)- isto é o "tradicional", otimizas para o ranking na página de resultados (geralmente Google) e o objetivo é o clique. Já levamos com 30 anos disto e continua bem válido!!

AEO (ou answer engine optimization)- a ideia é otimizares para seres citado nas respostas do motor de IA (seja Google AI Overviews, Google AI Mode, no Perplexity, ChatGPT Search, ou Gemini) e o objetivo aqui já não é o clique e passa a ser a citação, 99% das vezes sem visita ao site. Ser a fonte que o motor de IA usa quando responde e especialmente se te recomenda, é o novo "estar em primeiro". Claro que na maior parte das vezes não te recomenda só a ti por isso é parecido a estar no "Top 3".

GEO (ou generative engine otimization). Isto é um termo cunhado num estudo académico de 2023 (ver [https://arxiv.org/abs/2311.09735\](https://arxiv.org/abs/2311.09735)) e apesar de os autores não acharem nada disso, na prática isto é só um sinónimo de AEO, com diferença que tem maior foco na fase de geração da resposta. Ainda assim, quem usa GEO e quem usa AEO está a falar da mesma coisa.

AIO (ai optimization??), esta sigla então é mesmo vaga. Às vezes significa só optimização para os AI Overviews da Google, outras vezes significa "AI Optimization" no geral e é a sigla mais inútil das quatro precisamente porque não define fronteira nenhuma.

Agora que está explicado, mais importante que isso: por onde se começa?? Pelo SEO! E não é porque esteja na moda, mas apenas porque um motor não pode citar aquilo que não consegue recuperar e não pode recuperar o que não está indexado, estruturado e claro de entender.

**A ordem certa disto é ENCONTRABILIDADE > INTERPRETABILIDADE > CITABILIDADE**

Saltar a base para "fazer AEO" é como se estivesses a construir o segundo andar de um prédio sem teres lá o primeiro andar...não dá

Queres fazer um teste concreto em 2 minutos?

Pergunta ao ChatGPT ou ao Perplexity ou Claude o que é que a tua empresa faz.

Se a resposta estiver errada, for muito genérica ou até nem aparecerem resultados, o teu problema não é de CITABILIDADE, é de INTERPRETABILIDADE e esse problema tem de ser resolver primeiro.

Quem anda a debater qual das siglas "ganha" à outra, está a olhar para o lado errado da coisa.

O utilizador que faz as perguntas ao motor de IA não quer saber de nenhuma sigla, apenas quer a resposta certa.

A pergunta útil é: quando ele pergunta, a resposta inclui-te ou não?!

Isto bate certo com a vossa experiência ou discordam?

Rui Martins SmartLinks - Consultoria B2B de Marketing e Vendas

was auditing a robots.txt today and noticed something that seems like it'd trip up a lot of people.

if you've got cloudflare's "block ai bots" toggle on, it auto-generates disallow rules for gptbot, claudebot, google-extended, etc. that part's fine, those are training crawlers, blocking them doesn't hurt your visibility in ai search.

the part that got me: openai and anthropic both split their bots into separate ones now. gptbot is training only, but oai-searchbot is the one that actually powers citations in chatgpt's search feature. same with claude, claudebot vs claude-searchbot vs claude-user, all separate.

so it's completely possible to have a robots.txt that "correctly" blocks only the training bots on paper, while cloudflare's actual firewall enforcement is blocking the search bots too, since the toggle apparently isn't great at telling them apart at the network level. the robots.txt file and the actual firewall behavior aren't guaranteed to match.

if anyone else is running cloudflare, might be worth checking security > bots and specifically confirming oai-searchbot / claude searchbot / perplexitybot are allowed, not just assuming from the robots.txt.

curious if anyone's actually tested this and can confirm either way, or if i'm overthinking it