AI Visibility Logs
Tested on Reforge, which describes itself as a professional education platform teaching product and growth to experienced tech operators, across Claude, ChatGPT, Gemini, and Perplexity.
Bottom line: two AI engines read the same page about Reforge on the same day. One reported the company had been acquired. The other didn’t mention it. Publishing the fact clearly is not the same as the fact getting through.
The query
Asked verbatim, unchanged, in a fresh session on each engine: What is Reforge, and what are they best known for?
No URL. No context. No follow-up. The way a prospect would type it.
Sources cited
| Engine | Citations | Pages | Mix | Sources |
|---|---|---|---|---|
| Claude | 6 | 6 | 1 owned / 5 databases | reforge.com · Crunchbase · Tracxn · PitchBook · CB Insights · ZoomInfo |
| ChatGPT | 5 | 2 | 2 owned | reforge.com (×4) · Brian Balfour’s profile page |
| Gemini | 4 | 4 | 2 owned / 2 secondary | reforge.com · Brian Balfour’s profile page · MOGE product overview · a personal blog post on Balfour’s ideas |
| Perplexity | 5 | 5 | 1 owned / 4 third-party | reforge.com · PitchBook · LinkedIn · VentureCapitalTracker · a 2022 Series B press release |
Every URL above is what the engine itself displayed. Nothing was added.
I assumed owned sources would beat third-party ones, but Claude’s mix was more database-heavy than Perplexity’s, and its answer was far better, with the acquisition, founding year and headquarters all correct. And ChatGPT produced the most detailed answer of the four off just two distinct pages.
What the source class actually determines is which part of the question an engine can answer. Investor databases carry firmographics: founded, based, funded, and acquired. Crunchbase and CB Insights track ownership changes as a matter of course, which is the likeliest reason Claude had the Miro deal, while carrying nothing about what a company teaches, which is why Claude was thin on frameworks and dropped a co-founder. Owned pages carry the opposite.
Perplexity’s weakness wasn’t third-party sourcing. It was a weak set within that class: a stale funding press release and a low-authority tracker doing work a maintained database would have done properly.
Source class shapes the blind spots. Source quality shapes the accuracy. Neither is about which model you asked, or how many pages it read.
The finding I didn't expect
Gemini cited Brian Balfour’s profile page on reforge.com. So did ChatGPT. It’s where ChatGPT found the Miro acquisition. Gemini read the same page and didn’t report it.
That’s the most useful thing in this test. Retrieval is not comprehension. An engine can fetch the page carrying your most important fact and still not surface it. Which means the gap between what you have published and what gets said about you isn’t only a publishing problem; you can put the fact on the page, watch an engine cite that exact page, and still get an answer that omits it.
There is no lever that fixes this from your side. Publishing well is necessary. It is not sufficient.
Where all four agreed
- Category. Education and career development. Four for four.
- Audience. Experienced, mid-to-senior technology professionals. Four for four.
- No single flagship framework. Not one engine named one, even unprompted.
Where they diverged
- The Miro acquisition: two of four. Claude and ChatGPT have it. Gemini and Perplexity don’t.
- Andrew Chen as co-founder: one of four. Only ChatGPT.
- Founding year: three of four. Perplexity omitted it.
- Detail depth: wide. ChatGPT named a dozen frameworks; Gemini named several and listed instructor companies. Perplexity gave four sentences with no founder, no year and no frameworks.
- Category wording varied. “Career development and education company” (Claude), “professional learning platform” (ChatGPT), “elite career accelerator and executive education platform” (Gemini), “professional education and career development company” (Perplexity).
One fabrication
Gemini referred to Reforge’s frameworks as the “Reforge Playbooks” in quotation marks, as though it were the company’s own term.
It isn’t. Reforge uses “playbook” freely as a common noun and has a Growth Playbooks collection on its blog, but the branded name for its member assets is Artifacts. Gemini named Artifacts correctly two paragraphs later.
So it invented a brand term while simultaneously knowing the real one. No reader would catch it. That’s what makes it worth logging.
Possibly relevant: two of Gemini’s four sources were an AI-generated product summary and a personal blog paraphrasing Balfour’s ideas. Neither is the company. Loose paraphrase upstream is a plausible route to an invented label downstream, though with one run, I can’t establish that, only note it.
Fact-check
I verified the contested claims rather than trusting any engine.
- The Miro acquisition is real. Announced 24 March 2026. Balfour joined Miro as Chief Growth Officer.
- Reforge Learning does continue as a standalone brand, ChatGPT’s version was the precise one.
- Andrew Chen co-created the first Growth Series. The engines that credited Balfour alone were incomplete.
- 2016, San Francisco: correct.
No engine flagged that its picture of the company might be out of date.
What this means if you are the brand being asked about
Two source classes describe you, and you need both to be maintained. Your own pages supply what you do and who for. Company databases supply the facts of the entity, founded, based, funded, and owned. Engines draw on whichever they reach, and an engine reading only one class inherits that class’s blind spots.
Your database listings are marketing assets. Three engines cited Crunchbase, PitchBook, ZoomInfo, CB Insights, or Tracxn. Almost nobody maintains those. They are describing you as they last knew you, and they get quoted back to your prospects.
Nothing propagates evenly. Half the engines missed the single biggest development in the company’s history, four months on. If you’ve rebranded, been acquired, or changed what you sell, assume some engines still have the old version.
There is no single answer about you. The earlier attempt at this test, run on a personalized account, returned an answer about Reforge that was partly shaped by who was asking. Your prospects all have their own history, instructions, and saved context. “How do we show up in ChatGPT?” doesn’t have one answer; it has as many as there are people asking.
What that adds up to. Go and look at your own database listings: Crunchbase, PitchBook, ZoomInfo, CB Insights, Tracxn. Most are claimable and editable, and most companies have never touched theirs. Then check that the facts you would want quoted are written plainly on your own pages, team bios included. That’s the part you control.
The part you don’t: an engine can cite the right page and still not surface what’s on it. Publishing well is necessary. It isn’t sufficient.
Limitations
- One run per engine. Non-determinism is real. I cannot distinguish “Gemini doesn’t know about the acquisition” from “Gemini didn’t mention it this time.” Two engines already showed me the same query returning different answers on different runs.
- Model tiers aren’t matched by design. Pinning a specific model on ChatGPT or Perplexity requires a paid plan, so both were left on automatic selection, which is what an unsubscribed user gets. Gemini ran on Flash for the same reason. The tradeoff: Gemini was also the engine that fabricated a brand term and missed the acquisition, so some of what reads as “Gemini” here may be “Flash.” And because auto selection can route differently per query, the model itself may vary between runs without appearing in the interface. These tests describe what a default user sees, not what each engine is capable of at its best.
- All four engines retrieved. Every engine cited sources, so nothing here measures unaided recall. This is a retrieval test throughout.
- Retrieval measures the web on a date. These runs describe 30 July 2026. Reforge publishes; the answers will move.
- One subject. A company with a strong owned content library. A business with a thin site would likely produce a different pattern entirely.
- Publishing this is itself a variable. This page is now a source about how engines describe Reforge.
What I got wrong the first time
I ran this test once before and didn’t publish it. The question was leading; it asked which single framework Reforge specialises in, which forced each engine to pick one and made the picks look like disagreement. And the session was contaminated: it ran in ChatGPT’s Temporary Chat, which still applies custom instructions, so an answer about Reforge came back partly addressed to my own positioning (more on why).
Fix both, and most of the disagreement evaporates. A less dramatic finding than the one I started with, and the one the evidence supports.
What's next for this log
More runs, added to this page. One run per engine can’t separate a genuine engine difference from ordinary variance. Three runs each, and the results above become counts rather than single observations. Changes will be dated in the revision history below.
Log 002 — Give four AI engines your website. Does it change what they say about you? Every engine here found reforge.com without being told where to look. The open question is whether naming the URL explicitly shifts the source mix, whether Claude drops the investor databases, whether Perplexity stops citing a funding release from years ago. If it does, then how a prospect phrases the question determines which version of a company they get.
Revision history
30 July 2026 — Published. One run per engine, brand name only.
Part of the AI Visibility Logs, an open record of how AI systems find, interpret, and describe brands. Method notes: How these tests are run.
