Free Lesson
Developing Customer Sense as an AI-native Builder
Part of From customer sense to building solo with AI
45 min
Aug 27, 2026 11:00 AM
What you'll learn
Know what to build before you spend a token on it
Work backwards from real customer needs from every available source before going into AI generated/ synthetic user data
Build your own Customer Sense Evals
Apply the error-analysis method used on LLM pipelines to reviews, tickets, and interview notes.
Encode your findings into testable eval criteria
Walk out with pass/fail checks, grounded in real anecdotes, that your build must pass in session two.
Run a Customer Signal Audit on your current projects
Leave with a one-page audit that shows exactly where you have been trusting a proxy.
Catch a sycophantic AI before it shapes your roadmap
Divert the model from agreeing with you and point it towards what matters to your customers
Why this topic matters
One of the things AI can't replace is Customer Sense. Each layer, from customer research to production, launders the raw signal a little more. The expensive mistakes start there, when a confident model or a synthetic user gets treated as a real person. This session gives you ways to keep your customers at the center while building with AI, so your output is actually useful to them and not sloppy.
