Harness Engineering: diagnose the environment around an agent

When a long task fails, inspect its tools, state, tests and instructions alongside model capability. The course introduces ways to locate the missing boundary and choose a check before changing the setup.

The course is an interactive player: eight modules, quizzes, no sign-up. Related practice: the AI agent audit and the management-methods course.

For whom

• Developers and leads who already give agents multi-step work in a real repo
• Operators whose agents report done while tests are red or files are missing
• Readers ready to inspect repository state, runtime evidence and multi-step failures

Modules

1. Why agents fail
2. 5 harness subsystems
3. Repository = system of record
4. Against giant instructions
5. Session lifecycle
6. Overreach and WIP=1
7. Features and validation
8. E2E · observability · exit

After the course

• Use five diagnostic layers to investigate failures; allow contributing causes and model capability limits
• Distinguish instructions, tools, environment, state and feedback; choose a repair from the observed failure
• Keep authoritative project state in the repository and test whether a new session can recover it
• Split a bloated instruction file into a router plus topical docs
• Keep context between sessions: init, continuity artifacts, handoff
• Introduce WIP=1 and executable proof of completion
• Build feature lists as data and multi-level validation
• Require E2E, make the runtime observable, leave clean session state