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AI.D - AI Development Methodology

You own it. We organize it.

Your API key. Your repos. Your data.

AI.D is an overlay for Claude Code that gives your whole team — PM, Dev, Tech Lead, QA — a repeatable process from idea to production.

Claude Code License Skills Agents

Created by Ilan Dahan


The Three Pillars

Humans Lead

AI accelerates, you decide.

You approve every phase gate. You own every decision. Claude suggests — you commit.

Structure First

Clarity before code.

No code until requirements are approved. No deployment until tests pass. Phase gates enforce discipline.

Nothing Lost

Context compounds.

Every session builds on the last. Context tracking means you never restart from zero.


Table of Contents


What is AI.D?

AI.D (AI Development Methodology) is a structured overlay for Claude Code that transforms how teams build software. It's not a framework you install into your code — it's a methodology that guides Claude to work with your team through every phase of development.

The Problem

Without AI.D With AI.D
AI generates code without context Phase gates enforce requirements before code
Losing track across sessions Context tracking remembers everything
Each team member works differently One process: PM → Dev → QA all aligned
Scope creep and endless revisions Approved PRDs lock scope
No learning from mistakes Feedback system improves over time

Roles

Role Focus
Product Manager Requirements, user stories, DDD (Document Driven Development)
Tech Lead Architecture, code review, technical direction
Developer Implementation, TDD (Test Driven Development)
QA Engineer Test strategy, BDD (Behavior Driven Development)

Phase Gate System

AI.D enforces 6 mandatory phases (0-5) with quality gates between each. No phase can be skipped.

Phase 0 ──► Gate ──► Phase 1 ──► Gate ──► Phase 2 ──► Gate ──► Phase 3 ──► Gate ──► Phase 4 ──► Gate ──► Phase 5
Discovery    ✓        PRD        ✓      Tech Spec     ✓      Impl Plan     ✓        Dev          ✓      QA & Ship

What Happens in Each Phase

Phase Name What You Do Output
0 Discovery Research, stakeholder mapping, Go/No-Go decision Research report
1 PRD Define requirements, user stories, acceptance criteria Product Requirements
2 Tech Spec Architecture, database design, APIs, security Technical Specification
3 Impl Plan Task breakdown, Jira population, sprint planning Implementation Plan
4 Development TDD implementation, code review, component building Production code
5 QA & Ship Validation, acceptance testing, deployment Release

Phase Permissions (Humans Lead)

Phase Allowed Blocked
0 Discovery Research, stakeholders, competitive analysis PRD, architecture, code
1 PRD + Requirements, scope, user stories Architecture, code, Jira
2 Tech Spec + Architecture, schemas, APIs Code, Jira issues
3 Impl Plan + Task decomposition, Jira creation Production code
4 Development + Code, tests, components Deployment
5 QA & Ship Everything -

You approve each gate. Claude cannot advance without your /phase-approve.


Sub-Agents

AI.D uses 4 specialized sub-agents — isolated AI processes that provide objective evaluation without bias from the main conversation.

Why Sub-Agents?

Main Agent Sub-Agent
Full conversation context Isolated — sees only what you pass
Knows its own reasoning Evaluates output objectively
Might agree with itself Catches issues the main agent missed

Available Agents

Agent Purpose Triggered By
reflection-agent Quality evaluation for all significant outputs Automatic (Quality Check)
phase-review-agent Phase gate validation before advancement /gate-check command
qa-validator-agent Task completion validation QA hooks (Phase 4)
memory-analysis-agent Analyzes feedback and suggests improvements /aid-improve command

Quality Check (Automatic)

Every significant output goes through the reflection-agent:

╭─────────────────────────────────────────────────────────────╮
│ 🔍 Quality Check                                            │
├─────────────────────────────────────────────────────────────┤
│  ✅ WHY Alignment     9/10   Addresses stated goal          │
│  ✅ Phase Compliance  10/10  Appropriate for Phase 2        │
│  ✅ Correctness       8/10   Verified against specs         │
│  ✅ Security          9/10   No vulnerabilities found       │
│  ⚠️  Completeness     7/10   Missing error handling         │
│  ══════════════════════════════════════════════════════     │
│  📊 Overall: 8.6/10                                         │
│  STATUS: ✅ PASSED                                          │
╰─────────────────────────────────────────────────────────────╯

Skills System

AI.D uses 23 specialized skills organized by role and phase.

Core Skills (Always Active)

Skill Purpose
why-driven-decision Foundational — understand WHY before any action
reflection Quality check system with sub-agent evaluation
phase-enforcement Enforce phase gates, refuse out-of-phase work
context-tracking Track tasks, steps, progress across sessions

Phase Skills

Skill Phase Purpose
pre-prd-research 0 Business analysis, competitive research, problem validation
aid-discovery 0 Stakeholder identification, Go/No-Go decision
aid-prd 1 User stories, acceptance criteria, scope definition
aid-tech-spec 2 Architecture, API contracts, security design
aid-impl-plan 3 Task breakdown, Jira population, sprint planning
aid-development 4 Implementation guidance, TDD practices
aid-qa-ship 5 Validation, release preparation, deployment

Role Skills

Skill Focus Areas
role-product-manager Requirements, user stories, scope, stakeholder alignment
role-developer Code quality, TDD, debugging, technical feasibility
role-qa-engineer Test strategy, BDD/Gherkin, acceptance testing
role-tech-lead Architecture review, code review, technical direction

Development Skills

Skill Purpose
atomic-design Figma-to-code component system (atoms → pages)
atomic-page-builder Compose pages from existing components only
system-architect Security-first architecture (ISO 27001, OWASP)
test-driven TDD methodology, test patterns, coverage
code-review Quality review, security audit, production readiness

Support Skills

Skill Purpose
memory-system Session feedback, learning, improvement cycles
learning-mode Decision transparency, debate invitations
figma-design-review Design system compliance scoring

MCP Integrations

AI.D integrates with Model Context Protocol (MCP) servers for seamless tool connectivity:

MCP Purpose
Filesystem File operations, directory management
Chrome DevTools E2E testing, visual testing, performance
Jira Epics, stories, tasks, sprint management
Confluence Documentation, knowledge base
Figma Design tokens, component specs, assets
GitHub Repos, PRs, issues, code review

Setup: See INSTALLATION.md for MCP configuration and environment variables.


Commands Reference

Setup commands: See INSTALLATION.md

Session Flow (Daily)

┌─────────────────────────────────────────────────────────────┐
│  /aid-start  →  Work  →  /aid-end  →  /aid-improve          │
│     ↑                                       │               │
│     └───────────── Next Session ────────────┘               │
└─────────────────────────────────────────────────────────────┘
Step Command What Happens
1 /aid-start Select role (PM/Dev/QA/Lead) + phase → Skills loaded
2 Work Claude applies relevant skills, enforces phase gates
3 /aid-end Rate session (1-5), describe what worked/didn't
4 /aid-improve System learns and updates skills (optional, weekly)

Daily Workflow

Command Description
/good-morning Morning startup — check systems, load context
/context Show current work context
/aid-start Start session — select role & phase
/aid-end End session and provide feedback
/aid-status Show current state

Phase Management

Command Description
/phase Show current phase status
/gate-check Check if ready to advance (spawns sub-agent)
/phase-approve Human sign-off for current phase
/phase-advance Move to next phase

Development

Command Description
/discovery Start Phase 0 research
/prd Create Product Requirements Document
/tech-spec Create Technical Specification
/jira-breakdown Break spec into Jira issues
/design-system Build design system from Figma
/build-page Compose pages from components
/write-tests Write tests (TDD methodology)
/code-review Review code quality
/qa-ship QA validation and release

Improvement

Command Description
/aid-improve Run learning cycle (spawns sub-agent)
/reflect Show detailed quality check breakdown

Quick Start

See INSTALLATION.md for complete setup instructions.

Once installed, your daily workflow:

/good-morning          # Start your day
/aid-start             # Select role + phase
[work]                 # Claude applies skills
/aid-end               # Rate session

Project Structure

AI.D/
├── .claude/                    # ALL Claude Code content
│   ├── agents/                 # 4 sub-agents
│   ├── skills/                 # 23 specialized skills
│   ├── commands/               # Slash commands
│   ├── hooks/                  # QA gate hooks
│   ├── references/             # Reference documentation
│   ├── rules/                  # Behavioral rules
│   └── templates/              # State file templates
├── docs/                       # AI.D methodology docs
├── integrations/               # MCP setup guides
├── CLAUDE.md                   # Main instructions
├── INSTALLATION.md             # Setup guide
└── README.md                   # This file

Your Project (After Setup)

your-project/
├── .aid/                       # Runtime state
│   ├── state.json              # Current phase
│   └── context.json            # Work context
└── .claude/                    # Linked from AI.D
    ├── skills/
    ├── agents/
    └── commands/

Documentation

Document Description
INSTALLATION.md Complete setup guide
CLAUDE.md Critical instructions for Claude
docs/PHASE-GATES.md Phase system details
docs/MORNING-STARTUP.md Daily workflow guide

Example Workflow

Creating a New Feature (Full Cycle)

1. /good-morning              # Load context, check systems
2. /aid-start                 # Select PM role, Phase 0
3. /discovery                 # Research and Go/No-Go
4. /phase-approve             # Human approval
5. /phase-advance             # → Phase 1

6. /prd                       # Create requirements
7. /phase-approve             # Human approval
8. /phase-advance             # → Phase 2

9. /tech-spec                 # Create architecture
10. /design-system            # Extract Figma tokens
11. /phase-approve            # Human approval
12. /phase-advance            # → Phase 3

13. /jira-breakdown           # Create Jira tasks
14. /phase-advance            # → Phase 4

15. /aid-start                # Select Developer role
16. /write-tests              # TDD - tests first
17. [implement code]
18. /code-review              # Quality check
19. /phase-advance            # → Phase 5

20. /qa-ship                  # Final validation & deploy
21. /aid-end                  # Collect feedback
22. /aid-improve              # Learn from session

Author

Created by Ilan Dahan

Built with Claude Code by Anthropic.


License

AI.D Community License v1.0 — Free to use, adapt, and share. Cannot be sold.

See LICENSE for full details.

Allowed Not Allowed
Use in any project Sell the methodology
Customize for your needs Remove attribution
Share and teach
Commercial use

Credit: Ilan Dahan / theaid.ai

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AID - AI Development process - Complete methodology for AI-assisted full-stack software development. E2E process from raw ideas to deploy.

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