Qualixar film / 12:37

(Loop Engineering Vol. 1) The Inner Loop, the Outer Loop, and the Gate: What Nobody Explains.

Everyone says "stop prompting your agent, write a loop." Almost nobody explains what a loop actually is. This is the missing manual: the inner loop, the outer loop, the runner that connects them, and the gate that decides when to stop — built from the floor up, then proven with a real running example on screen. An agent is not a mind that decides to keep working. It's a model that returns text and falls silent — the loop is a piece of ordinary machinery built around it that decides whether to ask again. Peter Steinberger's line went to 8M+ views for a reason: "You shouldn't be prompting coding agents anymore. You should be designing loops that prompt your agents." Boris Cherny, who leads Claude Code at Anthropic, says the same thing from the inside: "I don't prompt Claude anymore. I have loops running that prompt Claude... my job is to write loops." This video is the part before both of those quotes make sense — the actual mechanics of the loop, the runner, and the gate. Building agents you can actually trust, one gate at a time, is what this channel calls AI Reliability Engineering. ⏱️ CHAPTERS 0:00 The cold open 0:37 What is an agent? (the word hiding inside it) 2:37 The two loops — inner and outer 5:12 The missing machine — the runner 9:19 Watch it run — a real loop, live 🔧 THE FIVE RUNNERS (every agent loop in the wild is one of these) • The shell loop — a bash while-loop piping a spec into a CLI agent, again and again • The exit-blocking hook — a stop-hook that catches the agent when it tries to quit and feeds the prompt back in • The built-in command — the runner the tool ships with (Claude Code's own /loop) • The scheduler — cron or CI, firing a fresh lap on a clock • The framework runtime — a graph engine following an edge back to an earlier node They differ only in where the re-summoning lives. What they do is identical: bind the model to the loop. The runnable code behind this series is now open-source → https://github.com/qualixar/bounded-loops bounded-loops: bounded, gated AI-agent loops where an independent check — not the agent — decides when the work is actually done. Nine enforced bounds, 67 runnable loops, keyless, Apache-2.0. "pip install bounded-loops" 📘 FREE — the full 57-page course (login-gated, free) This is Volume 1 of 3. Volume 2 picks up exactly here — what happens when the loop trusts the agent's word instead of a fact, and the gate + memory that make a loop safe to leave running. The complete written course — all 12 chapters, the runners, the gate, and the running example to build yourself — is free: → https://qualixar.com/learn/guides/loop-engineering-complete-guide 📚 SOURCES (verified, all primary) • Peter Steinberger, X: https://x.com/steipete/status/2063697162748260627 • Addy Osmani, "Loop Engineering": https://addyosmani.com/blog/loop-engineering/ • Anthropic, "Building Effective Agents": https://www.anthropic.com/research/building-effective-agents • Ralph Wiggum technique (Geoffrey Huntley): https://ralph-wiggum.ai/ 🔗 MORE Site + free guide: https://qualixar.com X: https://x.com/varunPbhardwaj Instagram: https://instagram.com/varunpratapbhardwaj LinkedIn: https://www.linkedin.com/in/varun-pratap-bhardwaj Until then — don't trust your agents. Verify them. #LoopEngineering #AIAgents #AgentLoops #ClaudeCode #StopPrompting #AIReliabilityEngineering #Qualixar #PromptEngineering