Subagent-driven development
Run a plan task-by-task: a fresh subagent implements each task, a reviewer checks it before the next. Fresh context per task = no pollution; review between = early catch. (Assimilated from obra/superpowers-skills; security-audited 2026-06-18 = clean; our wording.)
Status: probation — promote to active after a verified win where this skill was used and helped (see the skill-and-agent-probation-lifecycle methodology).
Process
- Load plan → a task list (one item per task).
- Per task: dispatch a fresh implementer subagent — "implement exactly task N, write/keep tests, verify, commit, report what changed + test results." It returns a summary, not a transcript.
- Review: dispatch the code-reviewer on that task's diff (base→head SHA). It returns Strengths / Issues (Critical·Important·Minor) / verdict.
- Apply feedback: fix Critical now, Important before the next task; dispatch a fix subagent if needed (don't hand-fix — context pollution).
- Next task; after all tasks, one final review of the whole change.
Red flags
Never skip the review between tasks, proceed with unfixed Critical issues, or dispatch multiple implementer subagents in parallel on the same worktree (they conflict — use separate worktrees if truly parallel).
Cost / when not to
Each subagent fan-out costs ~15× the tokens of a single pass — use this for genuinely independent tasks, not tightly-coupled ones (do those manually) and not when the plan still needs revision (brainstorm/spec first). See [[karpathy-loop-and-agent-discipline]]. For deterministic fan-out over many items, prefer the Workflow tool.