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/
- ✅ 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.
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
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.)
Tasks compound into milestones; milestones grow the project.
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)
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 updateor
# Python / pip
pip install pilotspace-add && pilotspace-add init
pilotspace-add updateor, 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
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:
- 🧭 Orients from
add.py status(the resume point) — never re-reading your repo. - 📐 Sizes your request into a milestone (goal · scope · breadth-first tasks · exit criteria) — you confirm the shape.
- ✍️ Drafts each feature's one-approval front — Spec + Scenarios + Contract + Tests as one bundle — you give one approval at the frozen contract.
- ✅ 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.
/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:
- the 2-minute Getting Started
- the full hands-on walkthrough (one real feature, end to end)
- package source
CHANGELOG.
Releases:
@pilotspace/add(npm) - https://www.npmjs.com/package/@pilotspace/addpilotspace-add(PyPI) — https://pypi.org/project/pilotspace-add/



