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/implement-wave

Runs all ready issues in parallel. Each issue gets a sub-agent. Results batched into single commit.

Usage

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/implement-wave

What's Different from L3

At L4, parallelization speeds execution: - Multiple issues run simultaneously - Sub-agents handle each issue independently - Single commit captures all wave changes - Dramatically faster for independent work

How It Works

  1. Claude runs bd ready to find unblocked issues
  2. Spawns sub-agent for each issue (max 3 per wave)
  3. Sub-agents work in parallel via Task tool
  4. Results merged and validated
  5. Single commit closes all wave issues

Why max 3? Each subagent returns results that accumulate in context. Capping at 3 prevents context overflow on complex issues while still providing meaningful parallelism.

Output

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Wave 1: 3 issues ready

Launching sub-agents:
  → agentops-abc: Add login form
  → agentops-def: Add logout button
  → agentops-ghi: Add session display

[Sub-agents complete...]

All 3 issues completed successfully.

$ git commit -m "feat: add auth UI components

- Login form (agentops-abc)
- Logout button (agentops-def)
- Session display (agentops-ghi)

Closes: agentops-abc, agentops-def, agentops-ghi"

$ bd close agentops-abc agentops-def agentops-ghi

Wave 1 complete. Run `bd ready` for Wave 2.

Example

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You: /implement-wave

Claude: Checking ready issues...

$ bd ready
1. [P1] agentops-xyz: Create user model
2. [P1] agentops-abc: Create order model
3. [P2] agentops-def: Add database migrations

Launching 3 sub-agents...

[3 parallel agents work...]

✓ All complete. Tests passing.

$ git commit -m "feat: add data models and migrations"
$ bd close agentops-xyz agentops-abc agentops-def

Done. Next wave has 2 issues ready.

When to Use

  • Multiple independent issues ready
  • Issues don't share file dependencies
  • Want maximum velocity

Next

  • bd ready - See next wave
  • /implement-wave - Run next wave
  • /retro - Extract learnings after completing plan