research-document
AI Engineering Handbook
AI Engineering Handbook
Part 2 --- Agent Architecture and Coordination
Version: Draft 0.1
1. Why Multiple Agents?
Different engineering activities benefit from different optimization goals. Separating planning, implementation, testing, review, and documentation reduces context pollution and improves accountability.
Recommended Agent Roles
Agent Primary Goal Outputs
Coordinator Orchestrate work Task assignments, progress Planner Decompose objectives Task graph Researcher Reduce uncertainty Evidence reports Implementer Write code Commits, patches Tester Validate behavior Test reports Reviewer Critique changes Review findings Documentarian Preserve knowledge ADRs, guides
2. Coordinator Responsibilities
The coordinator should:
- Define objectives
- Maintain task queue
- Enforce budgets
- Detect blockers
- Route work
- Collect artifacts
- Decide when human review is required
It should avoid becoming a bottleneck by delegating specialized work quickly.
3. Task Contracts
Every task should include:
- Objective
- Scope
- Inputs
- Required artifacts
- Constraints
- Acceptance criteria
- Budget
- Expected outputs
This prevents agents from making incompatible assumptions.
4. Communication Through Artifacts
Prefer durable files over conversational summaries.
Examples:
- ADRs
- Evidence registry
- Repository map
- Test report
- Review report
- Change log
Artifacts become the project's long-term memory.
5. Failure Recovery
When an agent fails:
- Capture partial work.
- Record assumptions.
- Record failed hypotheses.
- Preserve logs.
- Return unfinished work to the queue.
Never discard failed research without documenting why it failed.
6. Metrics
Useful operational metrics include:
- Tasks completed
- Acceptance rate
- Human review frequency
- Rework rate
- Tokens per accepted change
- Mean task duration
- Retrieval success rate
7. Anti-patterns
Avoid:
- General-purpose "do everything" agents
- Hidden assumptions
- Direct edits without task contracts
- Long conversational handoffs
- Missing acceptance criteria
Next Part
Part 3 explores engineering workflows for greenfield projects, legacy modernization, repository organization, CI/CD, and release engineering.