"Stop prompting the agent — design the system that prompts it." Three people independently reached the same phrase within one week of June 2026. A new layer in the stack 🔁 Title: Loop Engineering: The Anthropic Playbook for Designing Systems That Prompt Your Agents URL: A field note defining loop engineering as the 4th layer above prompt→context→harness, decomposed into five moves, six parts, and four costs. Three highlights. 🔁 Move yourself OUTSIDE the loop Earlier terms assumed a human at the keyboard prompting line by line. Loop engineering deletes that assumption, shifting you from being the engine to designing it. It wakes on a timer, spawns sub-agents, and feeds its own output back as the next input — that cross-conversation memory is what makes it a loop, not a one-off rerun. 🛑 The hard part is verification that can say "no" Ask an agent to grade its own output and it praises it. So rather than making the generator self-critical, you tune an independent skeptical evaluator on a different model — one that doesn't just read but acts (e.g. via Playwright) to verify. Claude Code's /goal lets a fresh small model judge the stop condition (the bank maker-checker principle). 💎 Generation is nearly free; judgment is the scarce resource Code, PRs, and fixes become abundant; value concentrates in deciding which one is actually right. Stripe merges 1,300+ machine-written PRs a week, yet reliability comes from constraint quality, not model size — and humans still review every PR. The closing line lands: the same loop, built by two people, can yield opposite outcomes. #AIAgents# #LoopEngineering#