10xchengtu/harness-engineering/harness-engineering

Harness Engineering

Harness = the operating system for AI agents working on your project. Model is CPU, context window is RAM, harness is OS.

Core Principle

Start simple, add complexity only when needed. Every harness component encodes an assumption about what the model can't do alone. Pressure-test these assumptions — they expire as models improve. Build for deletion.

When This Skill Activates

Workflow

For New Projects

1. Assess — What's the project? Tech stack? Team size? How will agents be used?
2. Setup — Create foundational harness files → read references/01-project-setup.md
3. Context — Design information architecture → read references/02-context-engineering.md
4. Constraints — Add guardrails and linters → read references/03-constraints.md
5. Evaluate — Set up feedback loops → read references/05-eval-feedback.md
6. If project involves multi-agent or long tasks → read references/04-multi-agent.md, references/06-long-running.md
7. If agents will run unattended (scheduled tasks, CI loops) → read references/08-loops.md; if agents should learn across sessions → read references/09-memory.md

For Diagnosis (Agent Not Performing Well)

1. Read references/07-diagnosis.md immediately
2. Identify which harness layer is failing
3. Apply targeted fix from the relevant reference

For Incremental Improvement

Assess current harness maturity, identify weakest layer, improve one layer at a time.

Harness Layers (Quick Reference)

Self-Update Protocol

When you discover a new reusable harness pattern during a project:

1. Identify which reference file it belongs to (or if it needs a new one)
2. Add the pattern with: what it solves, when to use it, how to implement it
3. Keep it concise — no fluff, just the pattern