[Upcoming webinar] Catch 7 AI Analysis Mistakes Before They Drive Decisions

One thing I keep seeing: AI is pretty good at producing analysis that looks done.

That’s also the problem.

You get a clean summary, a number that sounds precise, and a recommendation that feels reasonable. Then someone asks, “Wait, what definition of conversion did it use?” and the whole thing gets shaky.

I’m teaching a free Maven Lightning Lesson on the 7 mistakes that make AI analysis untrustworthy before it drives a decision.

Very practical. Metric definitions, denominators, source paths, caveats, and the quick review check I wish more teams used before forwarding AI output.

Friday, July 10 at 12 PM PT. If you can’t make it live, sign up anyway so you get the recording/transcript after.

Signup Link: https://maven.com/p/399386/catch-7-ai-analysis-mistakes-before-they-drive-decisions