In short: In brief: Viral GEO tactics (FAQ schema, markdown, llms.txt) have marginal impact. LLMs recommend brands based on their overall positioning and third-party validation. Not based on your tags.
30 sof LinkedIn scrolling to find the next viral GEO hack
0public proof that a « key takeaways » block improves AI visibility
3reputation levers that beat 100 technical tactics
One GEO hack per day on LinkedIn
Scroll 30 seconds on LinkedIn.
You’ll land on the next viral GEO hack. « Create an AI info page so LLMs understand your brand. » « Generate markdown versions of your content to explode your AI visibility. » « Audit your robots.txt with Claude and auto-generate an llms.txt. »
I’ve been watching these posts pass by for six months. I’m also tracking the sites that apply them religiously.
Result?
Marginal.
According to Search Engine Land, most of these tactics don’t move the needle because they don’t address the real problem: how LLMs decide which brands to recommend.
LLMs don’t choose a brand because it has a nice llms.txt. They choose it because it is positioned consistently, categorized clearly, and validated by third parties across the web.
GEO isn’t a technical problem.
It’s a reputation problem.
Why Popular Tactics Fall Flat
The recommendations aren’t wrong. They’re just overvalued.
They become table stakes. The problem starts when brands misinterpret them and push them to extremes.
Useless FAQs inserted everywhere
Google recommends FAQs with schema. Great.
But the hype around FAQs for GEO drove brands to insert questions that nobody cares about. Just because they think « it helps with GEO. »
Result: fake questions at the bottom of the page that add nothing for users.
No real user searches for that answer. No LLM values it if it doesn’t exist anywhere else on the web.
« Key takeaways » blocks at the top of every article
Another glorified tactic.
A summary block at the top can improve human readability. But there is no strong public proof that a « key takeaways » block materially improves AI visibility on its own.
It’s a nice-to-have. Not a lever.
Over-formatting to « help the LLMs »
Force every page into a rigid Q&A pattern. Cram bullet points into every section. Inject HTML tables where they don’t belong.
Some assume LLMs need help extracting content. So they resort to copywriting tricks like « chunking » that complicate the editorial process with no measurable gain.
Spamming Reddit for GEO
Others are obsessed with Reddit as a GEO lever. This pushes brands to spam Reddit.
Eli Schwartz documented it: Reddit represents the voice of real people. Moderators hunt astroturfing and « SEO shaping » on software évaluation threads.
Again: GEO isn’t a technical problem. It’s a problem of reputation consensus.
GEO is a Strategic Issue, Not Operational
I’ll be direct.
GEO doesn’t get managed at the operational SEO level. It gets managed at the executive level.
Why?
Because LLMs aggregate signals that go way beyond your direct control on your site.
They scan:
How you’re categorized on third-party sites (directories, comparators, B2B platforms)
How you’re mentioned in editorial articles
How your users talk about you on Reddit, Quora, specialized forums
The consistency of your positioning across your site, product docs, LinkedIn pages, press releases
None of these dimensions are solved with an llms.txt.
They’re solved with a clear brand strategy deployed consistently across all channels.
If your positioning is fuzzy, or if you change catégories every six months, LLMs won’t know where to place you. They’ll recommend you less. Or not at all.
If you’re consistent, clearly categorized, and validated by third parties, LLMs cite you. Even without hacks.
Third-Party Signals Beat On-Site Optimizations
A B2B SaaS client calls me in January 2026.
They’d applied every GEO tactic on the market: llms.txt, FAQ schema, markdown, key takeaway blocks.
AI visibility? Flat.
I look at their external profile.
Zero presence on G2, Capterra, TrustRadius
Editorial mentions: two articles in three years
Reddit discussions: zero organic mention, only corporate posts flagged and removed
LinkedIn positioning inconsistent with the site (« all-in-one platform » on LinkedIn, « specialized CRM » on the site)
The problem wasn’t technical.
It was reputation.
We stopped tactical optimizations. We refocused effort on three axes:
Category coherence: align messaging site / LinkedIn / G2 / press releases on a single product category
Third-party validation: targeted PR campaign to land 8 editorial mentions in specialized publications in 90 days
Authentic user voice: customer ambassador program to generate organic discussions on Reddit and specialized forums (no spam, just real users sharing their expérience)
Result in 120 days: +340% citations in ChatGPT responses on their target queries.
Without touching the llms.txt.
LLMs started recommending the brand because it was validated by third parties, clearly categorized, and consistent everywhere.
Positioning Coherence > One-Off Optimizations
Here’s what I observe in 90% of brands struggling with GEO.
They have no clear positioning. Or worse: they have multiple positions that contradict each other.
On site: « Project management solution for agile teams. »
On LinkedIn: « All-in-one collaboration platform. »
On G2: category « Task Management. »
In press releases: « Next-generation productivity tool. »
LLMs scan all of this. They seek consensus. If there isn’t any, they don’t know where to place you. So they place you nowhere.
Or they place you in a generic category where you lose to better-positioned competitors.
Coherence beats optimization.
A brand with clear positioning repeated everywhere gets recommended before a brand with 10 GEO hacks but fuzzy messaging.
Immediate action: Audit your positioning across 5 channels (site, LinkedIn, G2/Capterra, press releases, founder interviews). If you find 3 different formulations of what you do, you have a coherence problem, not a GEO tactics problem.
Category Alignment Determines AI Visibility
LLMs function by catégories.
When a user asks « best CRM for startups, » the LLM looks for brands that:
Are consistently categorized as « CRM »
Are associated with the « startups » segment across multiple sources
Are validated by third parties (reviews, articles, forums)
If you’re categorized « all-in-one platform » on half the web and « specialized CRM » on the other half, you appear in no answers. Because there’s no consensus.
A B2B e-commerce client in March 2026.
They sold a product catalog management solution. But their messaging varied:
Site: « Next-generation PIM »
LinkedIn: « Product data platform »
G2: category « Product Information Management »
Press articles: « Content management solution for e-commerce »
Result: invisible in AI responses on « best PIM » because half the web didn’t categorize them as PIM.
We re-categorized everywhere in 60 days. Site, LinkedIn, G2, press releases, founder profiles.
Single category: « Product Information Management (PIM) for B2B e-commerce. »
Result in 90 days: +280% ChatGPT citations on PIM queries.
Without changing a line of code.
Category alignment is a strategic lever. Not a technical optimization.
Third-Party Validation Forges AI Recommendation
LLMs don’t trust what you say about yourself.
They trust what others say about you.
That’s why editorial mentions, G2/Capterra reviews, organic Reddit discussions, citations in buying guides beat any on-site optimization.
If you appear in a TechCrunch article that says « X is a leader in category Y, » that signal outweighs 100 markdown pages on your site.
If you have 200 G2 reviews positioning you as « best for Z, » that signal counts more than a perfect llms.txt.
If real users recommend your solution on Reddit in évaluation threads, that signal beats all the FAQ schema in the world.
A B2B HR SaaS client in February 2026.
They’d optimized their site for GEO for six months. Markdown, schema, llms.txt, summary blocks. AI visibility: +12%.
We pivoted to third-party validation:
Targeted PR campaign: 6 editorial mentions in specialized HR publications in 90 days
Review program: incentivize satisfied customers to post on G2 and Capterra (no review buying, just a legitimate ambassador program)
Organic Reddit: customer ambassador program to share expérience on r/humanresources when relevant questions appear (no spam, just real answers from real users)
Result in 120 days: +410% ChatGPT citations on their target HR queries.
Third-party validation beats on-site optimizations 10 times out of 10.
Neurology of recommendation: LLMs are trained on web consensus. They reproduce what humans do: they trust third parties more than self-promotion. To get recommended, get yourself validated by others. Not by yourself.
Where to Start if You Want to Move AI Visibility Needle
Stop the hacks.
Start with a reputation audit.
Here are the three levers that actually move AI visibility:
1. Positioning coherence
Audit your messaging across 5 channels minimum: site, LinkedIn, G2/Capterra, press releases, founder interviews.
If you find 3 different formulations of what you do, you have a coherence problem. Solve it before any technical optimization.
Align everyone on a single sentence: « We are [category] for [segment]. »
Not « all-in-one platform. » Not « innovative solution. » One recognized market category: CRM, PIM, Marketing Automation, Project Management, etc.
Verify you’re categorized the same way on G2, Capterra, your site, LinkedIn, press releases.
If you’re categorized differently on two channels, LLMs won’t know where to place you.
3. Third-party validation
Get editorial mentions in specialized publications in your sector. Not SEO backlinks, real mentions that position you in your category.
Generate authentic reviews on G2, Capterra, TrustRadius. Not review buying. Legitimate customer ambassador programs that incentivize satisfied users to share their expérience.
Encourage organic discussions on Reddit, Quora, specialized forums. No spam. Ambassador programs where real users share expérience when relevant questions appear.
These three levers beat 100 technical tactics.
They take more time. They require cross-department coordination (marketing, PR, product, customer success).
But they move the needle.
GEO hacks don’t.
GEO Reputation Audit: Where You’re Losing AI Citations
First call = live audit of your external positioning. I scan your third-party signals, category alignment, cross-channel coherence. You leave with the 3 priority levers to move your AI visibility.
Do GEO tactics like llms.txt or markdown do nothing?
They’re not useless, but impact is marginal. They become table stakes. What actually moves AI visibility: positioning coherence, category alignment, third-party validation.
How do I know if my positioning is coherent?
Audit your messaging across 5 channels (site, LinkedIn, G2, press releases, interviews). If you find 3 different formulations of what you do, you have a coherence problem, not a technical problem.
Why do third-party signals count more than on-site optimizations?
LLMs are trained on web consensus. They trust what others say about you, not what you say about yourself. Editorial mentions, reviews, organic discussions outweigh any tag.
How long until you see results with reputation-based GEO?
90 to 120 days based on my client deployments. Time to align positioning, generate third-party mentions, and for LLMs to reindex these signals. Longer than hacks, but gains stick.
What’s the first concrete action to take for GEO?
Audit positioning across 5 channels. If you don’t have one coherent sentence repeated everywhere (« We are [category] for [segment] »), start there. Before any technical optimization.
Stéphane Jambu
SEO & AI Engineer
I build growth systems / AI / Neuroscience | 650+ clients · 80 LinkedIn testimonials · 30 years of expertise · 15 years of systems running without me.
