Published: 2026-06-20
Analysis & perspective

Agent Loops Explained: Reason–Act–Observe Cycles Instead of One-Shot Prompting

Name: Agent Loops Explained: Reason–Act–Observe Cycles Instead of One-Shot Prompting
Uploaded: 2026-06-20

Chapters / key moments (click to jump — plays here on the page)

Nate Herk demystifies "loop engineering" — the idea that instead of prompting a coding agent yourself, you design a loop that prompts the agent. A loop is a trigger, an action, and a stop condition, built on two pillars: an objective goal and a verification method. He argues most tasks don’t need elaborate agent swarms — a single reason–act–observe loop with a good "definition of done" does most of the work.

Source video

"Finally. Agent Loops Clearly Explained." by Nate Herk — Watch on YouTube →

Key Takeaways

A loop is three things — a trigger, an action, and a stop condition — and "loop engineering" means replacing yourself as the one who prompts the agent.
The two pillars are the goal (as objective as possible) and verification (how the agent checks its own work and knows when to stop).
Quality climbs with attempts; outsourcing the feedback/iteration loop to the agent gets you to 90%+ far faster than one-shotting.
Most tasks need only a solo loop — one agent reasoning, acting, observing, repeating — not fleets of agents orchestrating each other 24/7.
The best stop conditions are measurable ("iterate until X metric equals Y"); vague ones like "until you’re satisfied" can run for 12+ hours with little payoff.
Examples used Claude Code’s /goal command and Matthew Berman’s open Loop Library (thumbnails scored vs. a rubric, a Three.js plane, an Abbey Road recreation) — each verified visually via screenshots.

Commands & Code Mentioned

/goal   # Claude Code slash command used to kick off a self-verifying loop

Agent Loops Explained: Reason–Act–Observe Cycles Instead of One-Shot Prompting

Key Takeaways

Commands & Code Mentioned

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