The Idea

Use dependency-aware “waves” to parallelize multi-task implementations, where each wave contains tasks that can run concurrently.

Context

During git workflow plugin enhancement, the plan agent created a 4-wave execution strategy:

Wave 1 (Start Immediately):
└── Task 1: Extend State & Config (foundation)

Wave 2 (After Wave 1):
├── Task 2: Add event hook [depends: 1]
├── Task 3: Add PR review checking [depends: 1]
└── Task 4: Add commit limit enforcement [depends: 1]

Wave 3 (After Wave 2):
├── Task 5: Enhance issue tool [depends: 2]
└── Task 6: Add PR tool [depends: 2,3,4]

Wave 4 (After Wave 3):
└── Task 7: Update documentation [depends: 5,6]

Critical Path: Task 1 → Task 2 → Task 6 → Task 7
Parallel Speedup: ~35% faster than sequential

Raw Exchange

Plan Agent Output: “7 Tasks organized into 4 parallel waves… Critical Path: Task 1 → Task 2 → Task 6 → Task 7”

Execution Reality: Wave 2 tasks (2,3,4) all modified same file, so done sequentially to avoid conflicts. Wave 3 and 4 executed as planned.

Key Insight

Theoretical parallelism ≠ practical parallelism

Even when tasks are logically independent (different features), they may have:

• File conflicts: Multiple tasks editing same file
• State conflicts: Shared runtime state
• Test conflicts: Overlapping test coverage

The plan agent identified Wave 2 as parallelizable, but execution correctly serialized them because they all modified git-workflow-enforcer.ts.

Expansion Potential

1. Blog post: “Wave-Based Task Orchestration for AI Agents”
2. Template: Reusable wave planning structure for complex implementations
3. Tool improvement: Auto-detect file conflicts in parallel waves