Loop Engineering: Build Agents That Run Themselves

Loop Engineering — From Simple Runners to Autonomous Agents

A single intensive day covering the full loop engineering stack: anatomy of a loop, tool calls and branching, human-in-the-loop design, failure handling, and when to go fully autonomous. Every section ends with a working loop you built yourself.

1. Session 1: Loop Anatomy — Structure, State, and Termination

   Dissect what a loop actually is in an agent context: the trigger, the task queue, state management between iterations, and the termination condition. Understand the difference between a loop that runs once and one that keeps going until the job is done. Build your first simple task-runner loop in Claude Code end-to-end.

2. Session 2: Tool Calls, Branching, and Multi-Step Workflows

   Wire real tools into your loop — file reads, API calls, code execution. Add conditional branching so the loop can change course based on intermediate results. Build a multi-step research-and-write loop that fetches data, processes it, and produces a structured output without manual intervention.

3. Session 3: Human-in-the-Loop — Checkpoints and Approval Gates

   Not every step should run autonomously. Learn the two checkpoint patterns: blocking approvals (loop pauses and waits) and async approvals (loop queues work and resumes). Design approval gates for the moments that matter — destructive writes, external sends, budget thresholds — and keep autonomous everything that doesn't need a human.

4. Session 4: Failure Handling, Retries, and Production Patterns

   Loops fail. Learn structured failure handling — per-step error capture, exponential backoff retries, and hard-stop conditions. Understand loop observability basics: what to log, when to alert, and how to replay a failed run without duplicating side effects. Close with a review of the loop patterns that cover 90% of real production use cases.