| name | ai-autopilot |
| description | Delivers large multi-concern specs and backlog runs autonomously: decomposes specs into sub-specs (or normalizes work items into a backlog DAG), deep-plans with parallel agents, builds a dependency DAG, implements in waves, runs a single final quality loop with one bounded quality-remediation pass (verify+guard+review on full changeset), delivers via PR. Trigger for 'implement spec-NNN end to end', 'autopilot this', 'autonomous delivery', 'decompose and ship', 'run the backlog', 'execute these GitHub issues', 'process the sprint backlog'. Invocation is the approval gate. Not for small or single-concern tasks; use /ai-build instead. Not for ambiguous requirements; use /ai-brainstorm first. |
| effort | high |
| argument-hint | 'implement spec-NNN'|--backlog --source <github|ado|local>|--resume|--no-watch |
| tags | ["orchestration","autonomous","multi-spec","backlog","pipeline","execution","dag","transparency"] |
Autopilot v2
Delivers large multi-concern specs and backlog runs autonomously — decomposing into sub-specs (or a backlog DAG), deep-planning with parallel agents, implementing in waves, and shipping via PR with one bounded quality-remediation pass. Use it for end-to-end delivery of specs with ≥3 concerns or ≥10 file changes; use /ai-build for smaller single-concern work.
Purpose
Autonomous execution of large approved specs via a 6-phase pipeline: decompose into N focused sub-specs, deep-plan each with parallel agents, orchestrate a dependency-aware DAG, implement in waves, run one final verify+guard+review pass (with one bounded quality-remediation pass on the full changeset), deliver via PR with a transparency report. One invocation, full disclosure. Done only when sub-spec work converges into a delivery PR against protected main.
Thin orchestrator: phases READ other skills' SKILL.md and EMBED instructions into subagent prompts (no inline implementation), so autopilot inherits their improvements.
When NOT to Use
Triggers (≥3 concerns / ≥10 files, post-/ai-brainstorm approval, --backlog) live in the description + Dispatch threshold. Do NOT use for:
- Need human review between phases — use
/ai-build with manual checkpoints.
- Cross-repo changes — coordinate manually.
- Data migrations with destructive DDL — require explicit user approval per step.
Process
Step 0 — Validate: confirm .ai-engineering/specs/spec.md is not a placeholder (else STOP → /ai-brainstorm). On --resume, read .ai-engineering/runtime/autopilot/manifest.md and re-enter at the Resume Protocol. Load stack contexts (manifest providers.stacks + .ai-engineering/overrides/<stack>/conventions.md); pass paths (not content) to subagents. plan.md is not required — Phase 2 agents generate their own. ai-eng host probe is diagnostic/advisory only; ok_to_dispatch is not a standard-flow execution gate and cannot block /ai-autopilot.
Step 1 — DECOMPOSE (handlers/phase-decompose.md): extract N independent concerns; abort if N<3 (recommend /ai-build); write sub-spec dirs + the execution manifest.
Step 2 — DEEP PLAN (handlers/phase-deep-plan.md): dispatch explore+plan agents in parallel; each enriches sub-NNN/spec.md (Exploration) + plan.md (checkbox tasks with exports/imports). Failed agents retry once → mark plan-failed.
Step 3 — ORCHESTRATE (handlers/phase-orchestrate.md): build the file-overlap matrix + import-chain graph from Phase-2 evidence (never from spec text alone); construct the wave-assigned DAG; merge unresolvable conflicts.
Step 4 — IMPLEMENT (handlers/phase-implement.md): per-wave kernel from .claude/skills/_shared/execution-kernel.md. Dispatch build agents per sub-spec in parallel within a wave; each task self-validates via TDD; wave-end guard advisory remains for governance. Collect Self-Reports + per-wave commits. Cascade-block dependents of failed sub-specs.
Step 5 — QUALITY LOOP (handlers/phase-quality.md): read ai-verify / ai-review / ai-governance SKILL.md once at loop entry; dispatch verify+guard+review in parallel on the full changeset; consolidate findings (unified severity). Clean → Phase 6. Blocker/critical/high findings enter Phase 5b only if the one bounded quality-remediation pass is unused and the fixes are finding-scoped. Remaining blocker/critical/high findings after final reassessment → STOP + escalate to user.
Phase 5b — BOUNDED REMEDIATION (handlers/phase-quality.md): persist quality_remediation.max_attempts: 1 in the autopilot manifest, map each finding to sub-NNN, integration, or shared, run cross-platform focal reproducers, return to Step 5 final reassessment. No re-decompose, no re-plan, no second remediation pass.
Step 6 — DELIVER (handlers/phase-deliver.md): build the Integrity Report; follow /ai-pr SKILL.md; cleanup runtime dir; clear spec.md + plan.md; verify cleanup. --resume handles mid-pipeline re-entry.
Flags
| Flag | Behavior |
|---|
--resume | Read .ai-engineering/runtime/autopilot/manifest.md, determine pipeline state, re-enter at the correct phase/wave. Never re-executes completed phases. |
--no-watch | Create PR without the watch-and-fix loop. For draft delivery or externally-managed CI. |
| `--backlog --source <github | ado |
Dispatch threshold
Dispatch the ai-autopilot agent when work has ≥3 independent concerns, touches ≥10 files, follows /ai-brainstorm approval (spec.md exists, not a placeholder), or runs any --backlog; smaller scope hands off to /ai-build. The agent handle is .claude/agents/ai-autopilot.md; the procedural contract lives in this SKILL.md.
Governance
DEC-023: invocation is the single approval gate; internal gates (sub-spec validation, DAG verification, quality convergence) are automatic and cannot be bypassed. The consolidation path is mandatory: sub-spec branch/worktree → wave or integration commits → final PR → protected main. State transitions live on disk in .ai-engineering/runtime/autopilot/manifest.md, never in agent memory.
Examples
See references/examples.md for the three canonical invocations (end-to-end delivery, --resume after interruption, --backlog --source github), the failure-recovery rows, the telemetry event taxonomy, and the common-mistakes checklist (never run on draft specs, never cross repos, never carry context across sub-specs, never hand-edit mirrors).
Integration
Called by: user directly post-/ai-brainstorm approval (or with --backlog for backlog runs). Reads: _shared/execution-kernel.md, ai-verify/SKILL.md, ai-review/SKILL.md, ai-governance/SKILL.md, ai-pr/SKILL.md, ai-commit/SKILL.md. Delegates to: ai-explore, ai-build, ai-verify, ai-advise, ai-review agents. Transitions to: /ai-branch-cleanup. See also: /ai-build (smaller scope), /ai-board sync (lifecycle transitions for backlog mode), references/examples.md.
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