As AI-powered search tools like ChatGPT and Perplexity become primary discovery channels, many websites are realizing that traditional SEO is no longer enough. This article explores why fast-shipped AI apps often fail to appear in AI-generated answers, and what actually influences AI search visibility.
Why SEO doesn’t guarantee visibility in AI-generated answers?
Shipping apps with AI has never been easier.
Discoverability, though, is a different story.
I’ve been building small AI-powered apps using a very vibe coding workflow: fast iterations, minimal landing pages, focus on shipping, not marketing.
Everything worked… except one thing:
my apps were basically invisible to AI search engines like ChatGPT, Perplexity, or Gemini.
Not a traffic problem.
A structure problem.
AI doesn’t read your site like humans do
Most indie apps rely on:
- a hero section
- a short feature list
- maybe a pricing block
That works for humans.
LLMs don’t care.
What AI seems to look for instead:
- explicit questions & answers
- clear use cases
- well-defined entities (what the product is, who it’s for, what problem it solves)
- content it can reuse verbatim in answers
If your site doesn’t answer questions, AI has nothing to cite.
SEO patterns don’t map cleanly to AI search
Classic SEO assumes:
- keywords
- backlinks
- rankings
AI search behaves differently:
- it synthesizes answers
- it cites sources selectively
- it prefers clarity over persuasion
I realized most of my pages were optimized to convince users, not to inform machines.
That’s where AEO (Answer Engine Optimization) starts to make sense.
Doing AEO manually doesn’t scale (especially for indie devs)
I tried doing it by hand:
- rewriting pages as FAQs
- adding structured explanations
- clarifying entities manually
It worked… but it was slow and annoying.
For vibe-coded projects, this friction kills momentum.
What I ended up building
I eventually built a small internal tool to automate this for my own projects:
- analyze how “readable” a site is for LLMs
- detect missing questions, answers, and entities
- output concrete, copy-pastable fixes (not marketing advice)
That tool became x102.tech.
It’s opinionated, dev-first, and focused on:
- fast audits
- actionable output
- zero SEO jargon
Not trying to replace SEO tools.
Just solving AI visibility for people who want to ship fast.
Why this matters now
Google still treats “AEO” as a weird edge case.
AI search already doesn’t.
If your product isn’t understandable by LLMs, it won’t be cited — no matter how good it is.
For indie hackers and vibe coders, this is becoming part of shipping, not marketing.
Final thought
If you’re building AI apps:
- don’t overthink SEO
- but don’t ignore AI discoverability either
Make your product answerable, not just attractive.
If you’re curious, you can check out what I’m building at https://x102.tech.
Feedback from indie devs is more than welcome.
Top comments (0)