OA9 OppAlerts from Ben Wills
How AI Search Works: From Prompt to Response A guide for SEOs, AI search marketers, and marketing teams
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Work in progress Work in progress. Released about a week early, on purpose.

ChatGPT disclosed things in this session that I did not expect it to disclose, and there is no guarantee it stays available. I would rather people had time to use it than had a tidier version of it later.

So: every word of every ChatGPT response here is verbatim, and that part is checked automatically on every build. What is not finished is the presentation. The color coding on the code blocks is incomplete and some of it is imprecise, and there are notes to myself still sitting in the page.

Parts 1 and 2 are close to empty and are getting a lot of detail over the next week or so, along with a cleanup pass on everything else. Worth checking back.

Read the announcement →

Prompt sensitivity

How One Word in a Prompt Changes AI Recommendations

1,363 answers across six models, with search turned off and one irrelevant word varying between runs.

Placeholder

This section is not written yet. The research behind it is finished and the numbers below are verified, but the writing and the exhibits are still to come.

This part covers what happens when there is no search at all. The question goes to the model, the model answers from what it already knows, and nothing is fetched.

The test

One prompt asks for hotel recommendations in Los Angeles. It mentions, in passing, what car the traveler is flying in to pick up. The car has nothing to do with hotels.

Six wordings for the car, from "a used Honda Civic" through "a brand new Ferrari", plus one-word versions so that some pairs of prompts differ by a single word. Six models, three runs each, with temperature and reasoning level swept where the model supports them.

What it shows

Full write-up to come.