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Harness Engineering 101 builds an agent from a 300-line Python loop

github.com 3 min read Editor score 8/10

The series grows a roughly 300-line Python agent across 16 chapters, framing the harness as the program that builds, maintains, and protects the conversation sent to a stateless LLM. That grounding gives engineers a practical way to reason about agent behavior and failure modes.

What: • Harness Engineering 101 explains how to build an AI agent by growing a plain-Python harness around an LLM API.
How: • The harness builds and maintains a JSON conversation array, sends it to the stateless API, and processes the returned text.
Why it matters: • The failure-and-patch approach helps engineers reason about agent behavior, context limits, tools, retries and other system plumbing.

The harness sends a conversation array to the stateless LLM API and receives text in return. Sketched from the article's own text.

Read on github.com → Hacker News · 64 comments

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