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(ADD) AI-Driven Development - LOOP SKILL AGENT

AI Workflow Methodology - AI Tool - MIT

1 LOOP skill ⟳ 5 Specs ⟳ 8 Growth-Steps

SKILL's assets in: .add

📖 Read the book online: https://pilotspace.github.io/ADD/


Highlight

  • Approve once, then let it run — one human sign-off at the frozen contract; the agent builds the rest.
  • 🔬 Proof, not promises — verify on observed behavior and pre-declared build-expectations, not code-reading.
  • 🔒 Security never gets waved through — any security finding is a HARD-STOP; Human in-loop
  • 🚀 Prototype to production — task → milestone → graduate (analytics-gated) → recorded release, one method.
  • 🚀 Smarter as you go — competency deltas fold into a living, compacting foundation carried across milestones.
  • 🚀 See it before you build it — a UDD wireframe + zero-dependency HTML mock, approved before any code.
  • 👥 Built for teams — support git-native multi-user, N parallel milestones, DAG-scheduled waves.
  • 🧩 One slice across many components — Support monorepo or multi-repo in teams
  • 🤝 Works with your AI — Claude, Copilot, Cursor, Codex, Gemini; install via npm, pip, or the Claude Code plugin.

Direction before speed. Trust comes from passing tests — not from reading code and finding it plausible.


Foundation Domain Documents

This is a complete guide to AIDD (AI-Driven Development) — a way of building software in which an AI agent writes most of the code and people do the two things AI cannot reliably do alone: decide what to build, and verify that what was built is correct.

Anyone who builds software with AI in the loop: engineers, architects, testers, designers, product owners, and the managers who lead them. No part assumes you have read the others; cross-references point you to what you need.

ADD Across the Org: AI-Driven Development Beyond Code


🚀 How the ADD work grows

One task · eight steps · one file. Every feature is a single TASK.md that fills in section by section as it moves around the loop — each step produces exactly one durable artifact. The contract freeze is the one human approval; the agent drives the rest. (The artifacts are what you keep — the code is disposable.)

How one TASK.md grows — eight steps circle a single TASK.md file; each step writes its own section, from §0 grounding map through §3 frozen contract (the one approval) to §7 deltas; a red⇄green engine runs between Tests and Build, and Observe loops back to the next Specify

Tasks compound into milestones; milestones grow the project.

MILESTONE.md and TASK.md lifecycle — a milestone decomposes breadth-first into a task DAG of TASK.md files run just-in-time; each task's Observe step feeds a spec delta into the next task; the milestone is goal-gated; at close, the ship-review folds lessons into PROJECT.md and CONVENTIONS.md, which loop back to ground the next milestone


🚀 Get Started

Three steps — 1. Install with npx @pilotspace/add init (also pip, or the Claude Code plugin); 2. Spawn a feature with /add 'your goal' and give one approval at the frozen contract; 3. Resume anytime with /add — state lives in .add/state.json, no context rot

Here is the whole path, from nothing to your first running feature.

  • 🧱 Prerequisites: Node ≥ 18 (npm path) or Python ≥ 3.10 (pip path)
  • 🤖 CLI Coding Agent: Claude Code, Codex, ...
  • Maximize performance with agent's skillset: https://github.com/ccsk-org/ccsk-cli (recommended — opt-in)

1 · Install into your project

From your project root (an empty folder or an existing repo), pick either ecosystem:

Example .add

# Node / npm
npx @pilotspace/add init

# Update
npx @pilotspace/add update

or

# Python / pip
pip install pilotspace-add && pilotspace-add init

pilotspace-add update

or, on Claude Code, install the skill straight from the marketplace — no npm or pip needed:

/plugin marketplace add pilotspace/ADD
/plugin install add@add-method

2 · Spawn your first feature — talk to the agent

In Claude Code, run /add and say what you want to build:

/add 'Describe your goal'

Example: /add simple JWT auth

From there the agent runs the on-ramp for you:

  1. 🧭 Orients from add.py status (the resume point) — never re-reading your repo.
  2. 📐 Sizes your request into a milestone (goal · scope · breadth-first tasks · exit criteria) — you confirm the shape.
  3. ✍️ Drafts each feature's one-approval front — Spec + Scenarios + Contract + Tests as one bundle — you give one approval at the frozen contract.
  4. ✅ Runs build → verify to green; a security finding always stops back to you.

So your first feature is: describe it → confirm the milestone → approve the contract → review the result. Everything in between is the agent.

3 · Resume anytime

/add status|continue

AI will report to you how are current status of this project?

State lives on disk, not in the chat — close your laptop, come back tomorrow, and this tells you exactly where you left off. No context rot.

Go deeper:

Releases:


📚 Deepdive into ADD Method - https://pilotspace.github.io/ADD/