Nobody teaches this AI agent building method. I call it prompt extraction.

I start slow. Build a tool, a feature, whatever it is, through a bunch of trial and error using Claude or ChatGPT. Lots of back and forth, dead ends, fixes.

Once it actually works and I have something reusable, I say one thing to the AI:

"We now have a reusable product after all this trial and error. Turn everything you learned building this into a clean, reusable prompt. Then zip the code, include a README, and package it so it can be reused directly."

That single instruction does two things. It captures the knowledge from the whole messy process into something reusable next time, and it packages the actual output so I'm not pasting code back and forth burning tokens on something already solved.

The first build teaches the AI, and you, what actually works. The prompt and the zip are what make that learning reusable instead of one-off.

Most people rebuild from scratch every time. Prompt extraction turns every hard-won build into a permanent asset.

Anyone else doing something similar, capturing the process after the fact instead of planning it upfront?