Episode 16 - AI Loops...This is the way
Published Jul 6, 2026 · 27 min
Listen to this episode
Summary
AI loops are changing how people get real work done with agents.
Chapters
- 00:00 — What are AI loops?
- 00:27 — Why loops are not exactly new
- 01:10 — From prompt-by-prompt work back to real requirements
- 02:58 — OpenClaw, cron jobs, and early agent loops
- 03:35 — GPT-5.5 and goal-oriented prompting
- 04:55 — A four-hour builder/reviewer agent loop
- 06:03 — Chunking work versus letting loops run
- 06:44 — Good AI workflows look like good human workflows
- 08:34 — Why nuance and hidden requirements still matter
- 09:53 — The review agent is the critical piece
- 10:40 — Win conditions tell the loop when to stop
- 12:29 — The value shifts from typing to thinking
- 14:01 — Solving the wrong architecture before code exists
- 14:54 — Why knowledge work is undervalued
- 15:59 — The boiler repairman and the value of experience
- 17:13 — Value-based billing and technology leverage
- 19:18 — The dopamine trap of instant AI iteration
- 19:43 — Prototyping first, then turning reactions into requirements
- 20:11 — AI can help write specs, but you still have to read them
- 21:50 — Applying loops to creative and social content
- 23:34 — Getting to 90% before humans review
- 24:35 — Using transcripts as requirements for content loops
- 25:28 — Stop staring at the harness and start defining the contract
- 26:26 — Start with small loops, not a 50-agent circus
- 27:21 — Simple workflow loops like standups, notes, and PR rebases
- 27:53 — Wrap-up