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LOOP ENGINEERING

Agent Loops v2 — Loop Engineering

Stop prompt your agents at every step. Design the loop that prompts them — a trigger, an action, and a stop condition that the AI itself checks.

A dense, practical course, from the fundamentals (reason → act → observe) to Loop Engineering, distilled from 45 verified sources + Nate Herk's video. Each concept has a diagram, and each technique has a ready-to-copy-and-run prompt.

A luminous ribbon folded into an infinite loop with three orbiting nodes — think, act, and observe — in amber and cyan on a dark background

The loop in one image: one goal at the center, and the three steps reason → act → observe repeating until verification says "done."

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The core idea in 30 seconds

A loop = 3 things

Trigger, action, and stop condition. Underneath every complicated design, it’s always reason → act → observe, repeating until "done".

Verification is everything

A loop is only as good as the way it checks "done." Without verification, it confidently delivers the wrong work — and calls it done.

You become the architect

Instead of typing the next step, you design the system that decides the next step. That’s the “v2” leap: Loop Engineering.

The 4 paths

How this course was made (and why it matters)

All the content originated from a verification loop: agents scanned 45 sources (Anthropic/OpenAI/Google docs, the ReAct paper, practitioner blogs, Nate Herk's video), a "maker" agent copied the exact phrase from each source, and a separate "checker" agent searched each URL again to confirm. It's the same maker→checker pattern you'll learn in Track 2 — the course itself is the output of a loop.

Sources independently confirmed · no hallucination presented as fact.