bettyguo/harness-engineer-roadmap
An interactive roadmap for harness engineering — building the agent loop, tool layers, context engineering, memory, retrieval, eval harnesses, and the rest of the scaffolding around modern LLMs.
SUMMARY AI summary by gpt-5-mini
Harness Engineering Roadmap is an interactive, curated guide to the engineering around LLMs — the “harness”: agent loop, tool layers, context engineering, memory, retrieval, evals, observability, and production failure modes. It’s aimed at AI researchers and engineers building agents who need practical, production-ready scaffolding rather than model-centric theory. Key features: a live clickable diagram (12 areas, 84 nodes) with vetted resource panels; three pragmatic reading paths for common needs (debugging prod, scaling, learning foundations); durable vs. current tagging for links; nightly CI link checking and quarterly sweeps; static markdown fallback and contribution guidelines. Maintained by Betty Guo. Code is MIT-licensed; content CC-BY-4.0.
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Final-year PhD @ HKU CS. I prove the architectural limits of LLM reasoning, and build the systems that route around them.
Dates
| Created on GitHub | 2026-05-14 |
| Last push | 2026-05-14 |
| First seen here | 2026-05-14 |
| Last fetched | 2026-05-14 16:10 |
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