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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.

TypeScript OTHER GitHub ↗ site ↗
★ 1
stars
70
AI relevance
65
solo dev
0
tool sigs

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.

DETECTED Detected AI stack

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🤝 Agent frameworks (1)
AgentOps

GitHub Topics

#agent-frameworks #agent-harness #agent-infrastructure #agentops #context-engineering #harness-engineering #llm-agents #roadmap

Language breakdown (by bytes)

CSS
2.3%
HTML
2%
Python
39.4%
JavaScript
0.1%
PowerShell
5.3%
TypeScript
50.9%

Owner

Account
bettyguo
Type
User
Followers
8
Company
The University of Hong Kong

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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