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MAID - Managed AI Development

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


The Three Pillars

Humans Lead

AI accelerates, you decide.

You approve every phase gate. You own every decision. github 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 MAID?

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

The Problem

Without MAID With MAID
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

MAID enforces 7 mandatory phases (0-6) 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 ──► Phase 6
Discovery    ✓        PRD        ✓      Tech Spec     ✓      Impl Plan     ✓        Dev          ✓      QA & Ship    User Feedback

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
6 User Feedback Collect feedback, triage issues, implement fixes Resolved feedback log

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 -
6 User Feedback + Receive, triage, fix user issues -

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


Sub-Agents

MAID 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 /maid-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

MAID uses 30 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
maid-discovery 0 Stakeholder identification, Go/No-Go decision
maid-prd 1 User stories, acceptance criteria, scope definition
maid-tech-spec 2 Architecture, API contracts, security design
maid-impl-plan 3 Task breakdown, Jira population, sprint planning
maid-development 4 Implementation guidance, TDD practices
maid-qa-ship 5 Validation, release preparation, deployment
maid-user-feedback 6 Collect user feedback, triage issues, fix loop

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

MAID 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)

┌─────────────────────────────────────────────────────────────┐
│  /maid-start  →  Work  →  /maid-end  →  /maid-improve          │
│     ↑                                       │               │
│     └───────────── Next Session ────────────┘               │
└─────────────────────────────────────────────────────────────┘
Step Command What Happens
1 /maid-start Select role (PM/Dev/QA/Lead) + phase → Skills loaded
2 Work github applies relevant skills, enforces phase gates
3 /maid-end Rate session (1-5), describe what worked/didn't
4 /maid-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
/maid-start Start session — select role & phase
/maid-end End session and provide feedback
/maid-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
/maid-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
/maid-start             # Select role + phase
[work]                 # github applies skills
/maid-end               # Rate session

Project Structure

MAID/
├── .github/                    # ALL github 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/                       # MAID methodology docs
├── integrations/               # MCP setup guides
├── github.md                   # Main instructions
├── INSTALLATION.md             # Setup guide
└── README.md                   # This file

Your Project (After Setup)

your-project/
├── .maid/                      # Runtime state
│   ├── state.json              # Current phase
│   └── context.json            # Work context
└── .github/                    # Linked from MAID
    ├── skills/
    ├── agents/
    └── commands/

Documentation

Document Description
INSTALLATION.md Complete setup guide
github.md Critical instructions for github
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. /maid-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. /maid-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. /maid-end                  # Collect feedback
22. /maid-improve              # Learn from session

License

AMID 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

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MAID — Managed AI Development setup for github-copilot in VS Code

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