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  • Home
  • About
  • Work
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    • Video Translator
    • Text Moderator
    • Second Brain
    • Content Resonance Engine
    • Custom Chatbot
  • Small Biz Services
    • AI Foundation Diagnostic
    • AI Search Optimization

AI SEARCH OPTIMIZATION

Your boss asked if you show up in ChatGPT. You don't have a real answer yet.

Neither does anyone selling you one.


You typed your own questions into ChatGPT to check. Sometimes your company came up. Sometimes a competitor did. Sometimes it invented something about you that isn't quite right. You closed the tab knowing a little more and feeling no more certain.


Here's the part nobody leads with: you don't have a visibility problem you can fix by rewriting everything. You have pages AI can read and pages it can't, pages worth being found for and pages that don't matter, and no way yet to tell which is which. That's diagnosable.

The advice you're about to get is "rewrite everything for AI"

It'll arrive as a checklist, a retainer, or a tool that scores your whole site red and offers to fix it. You've heard this pitch before in a different costume. It was "clean all your data first."


Your content isn't the problem. Your content is the symptom. Most of what's "wrong" with a site in AI search isn't writing. It's structure:

  • Content that renders fine to you and comes back empty to a crawler
  • A date field the CMS has been filling in wrong for a year
  • Your company's name written one way in the headline, another in the body, so nothing reading the page can be sure they're the same org


You don't rewrite those. You find them. And you only fix the ones sitting between you and a page worth being found for.

What actually gets looked at

Every page in scope gets pulled, read the way an AI crawler reads it, and checked against four things:


  • Legibility: Can a bot even see this page, or does it load in a way crawlers skip, sit behind a blocking robots rule, or lack a clean map for agents to follow?
  • Extractability: Does the page answer a question in a clean, liftable chunk, or bury the point under three paragraphs of throat-clearing?
  • Substance: Is there anything behind the claims: specific facts, real numbers, a named source, an actual expert quote?
  • Audience fit: Is the page doing the job its reader needs? This layer gets built for you, because the job differs by industry. 


Then findings join to your real traffic, so what comes back isn't a pile of problems. It's a sequence: this page carries weight and it's broken, fix it first. This one scored badly and nobody visits it, leave it alone.

The part that matters most: it tells you what it couldn't tell

Every finding carries a confidence level.


  • Confirmed: The evidence is right there on the page.
  • Inferred: The signal is strong but not explicit, with a note on why.
  • Undetermined: It couldn't be established, with a written reason. Not a guess dressed up as a number. 


Most scanners return a confident score for every field, because a dashboard full of green numbers demos beautifully. It also lies to you in exactly the places you can least afford it. You've sat across from four vendors who answered your data-quality question with something that sounded technical and meant nothing. You wrote "vague on data quality" in your notes every time.


An audit that says "I don't know, and here's why" is worth more than one that's confidently wrong. You knew that already. This is a system that agrees with you.

Nobody actually knows what makes AI cite a page. Including me.

I'd rather say that directly than pretend otherwise.


Some things we can verify. Some we can't yet.


Verifiable and fixable:

  • A page has to be reachable, legible, structured, and consistent
  • Schema that matches the visible text
  • Answer-first openings, consistent naming

Still an informed guess:

  • Exactly how a model chunks a page
  • Why it picks one source over another
  • How much any single signal actually moves a citation 


The fixable fundamentals are most of the work. The deeper mechanics are guesses right now, and the honest version of this labels them as guesses. My rubric is versioned, because it's going to change as the ground does.


If someone's selling you certainty about how ChatGPT decides what to quote, that's the tell. They're guessing too. They're just not telling you.

What you walk away with

Which of your pages are load-bearing for AI search, and which you can stop worrying about.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

Which of your pages are load-bearing for AI search, and which you can stop worrying about.

The difference, page by page, between structurally broken and just old.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

Which of your pages are load-bearing for AI search, and which you can stop worrying about.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

An honest map of what the diagnostic couldn't determine.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

Findings with the evidence attached, so when your boss asks where this came from, you point at the page instead of defending a number.

If you're the one who has to answer for this

You don't need someone to tell you AI search matters. You need someone to tell you which of your pages are worth the effort, and to be honest about the parts nobody can prove yet. That's the whole job. Let's find out what your content can actually support.

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