PRD to merge-ready PR
An AI engineering team that turns a plain-English feature request into committed, tested, reviewed code — without changing how product or leadership work.
The team
Four specialized agents orchestrated by /eng-team. Each reads from a shared scratchpad — no agent talks directly to another.
Tech Lead
Reads the PRD and codebase, produces a precise Technical Spec — file paths, acceptance criteria, approach. Never writes code.
Spec onlyEngineer
Implements the spec, writes tests inline, runs the linter, and commits to a feature branch.
Build + testReviewer
Diffs against main for correctness, security, and performance. Approves with a PR description — or rejects with actionable fixes.
Diff reviewDevOps
Deploys locally via Docker Compose. Separate /devops command after merge.
How it works
Human provides the PRD. The autonomous pipeline runs spec → implementation → review, with bounded iteration loops when needed.
PRD in
Human merges
Bounded loops: Human ⇄ Tech Lead (PRD clarification) · Engineer ⇄ Tech Lead (spec gaps) · Engineer ⇄ Reviewer (reject/fix) · All state in .eng_team/task_*.json
Get started in four steps
Copy .claude/ into your project, bootstrap context, and run your first PRD.
Add eng-team to your repo
Copy the .claude/ directory to your project root. Requires Claude Code.
Generate CLAUDE.md
Run /eng-team-context ./ to analyze your repo and generate agent-optimized context automatically.
Run a PRD
/eng-team Add rate limiting to the cart API — max 100 req/min per user, Redis-backed, fail-open
Push & merge
Push the branch, open a PR, paste PR_DESCRIPTION.md. Deploy locally with /devops deploy local.
Interactive guides
Architecture deep-dives, quality gates, and executive presentations — built for teams adopting autonomous engineering.
Executive presentation
19-slide deck: current workflow, quality gates, multi-repo architecture, and roadmap. Keyboard-navigable.
Open presentation →Quality gates guide
Five-stage framework for single-repo and multi-repo environments. Failure modes, agent workflow, sequencing rules.
Explore guide →Code as agent harness
How eng-team maps to harness engineering research. Scratchpad evolution, verification stack, prioritized backlog.
Read analysis →Repository README
Full setup instructions, PRD examples, tips, and workflow summary. Start here for hands-on usage.
View on GitHub →Philosophy
Why eng-team starts at the verifiable bottom, replaces one role at a time, and keeps the human intent gate.
Read philosophy →Executive summary
One-page overview for leadership: trust earned incrementally, not declared. Not about replacing engineers.
Read summary →Built on a simple conviction
AI enters the engineering hierarchy from the bottom — where output is verifiable — and earns trust upward.
Verifiable first
Tests pass or they don't. Diffs make sense or they don't. Product judgment has no equivalent check — yet.
Narrow insertion
One slice: requirement → PR. Product, design, and deployment stay exactly as your team already owns them.
Trust compounds
Teams that watch AI ship reliable code earn the right to automate the next layer. Track record, not promises.