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BMAD-METHOD/src/modules/bmm/README.md
Brian Madison 17f81a84f3 docs: comprehensive documentation accuracy overhaul and PM/UX evolution analysis 
This commit represents a major documentation quality improvement, fixing critical inaccuracies and adding forward-looking guidance on the evolving role of PMs/UX in AI-driven development.

## Documentation Accuracy Fixes (Agent YAML as Source of Truth)

### Critical Corrections in agents-guide.md
- **Game Developer workflows**: Fixed incorrect workflow names (dev-story → develop-story, added story-done, removed non-existent create-story and retro)
- **Technical Writer naming**: Added agent name "Paige" to match all other agent naming patterns
- **Agent reference tables**: Updated to reflect actual agent capabilities from YAML configs
- **epic-tech-context ownership**: Corrected across all docs - belongs to SM agent, not Architect

### Critical Corrections in workflows-implementation.md
- **Line 16 + 75**: Fixed epic-tech-context agent from "Architect" → "SM" (matches sm.agent.yaml)
- **Line 258**: Updated epic-tech-context section header to show correct agent ownership
- **Multi-agent workflow table**: Moved epic-tech-context to SM agent row where it belongs

### Principle Applied
**Agent YAML files are source of truth** - All documentation now accurately reflects what agents can actually do per their YAML configurations, not assumptions or outdated info.

## Brownfield Development: Phase 0 Documentation Reality Check

### Rewrote brownfield-guide.md Phase 0 Section
Replaced oversimplified 3-scenario model with **real-world guidance**:

**Before**: Assumed docs are either perfect or non-existent
**After**: Handles messy reality of brownfield projects

**New Scenarios (4 instead of 3)**:
- **Scenario A**: No documentation → document-project (was covered)
- **Scenario B**: Docs exist but massive/outdated/incomplete → **document-project** (NEW - very common)
- **Scenario C**: Good docs but no structure → **shard-doc → index-docs** (NEW - handles massive files)
- **Scenario D**: Confirmed AI-optimized docs → Skip Phase 0 (was "Scenario C", now correctly marked RARE)

**Key Additions**:
- Default recommendation: "Run document-project unless you have confirmed, trusted, AI-optimized docs"
- Quality assessment checklist (current, AI-optimized, comprehensive, trusted)
- Massive document handling with shard-doc tool (>500 lines, 10+ level 2 sections)
- Explicit guidance on why regenerate vs index (outdated docs cause hallucinations)
- Impact explanation: how bad docs break AI workflows (token limits, wrong assumptions, broken integrations)

**Principle**: "When in doubt, run document-project" - Better to spend 10-30 minutes generating fresh docs than waste hours debugging AI agents with bad documentation.

## PM/UX Evolution: Enterprise Agentic Development

### New Content: The Evolving Role of Product Managers & UX Designers

Added comprehensive section based on **November 2025 industry research**:

**Industry Data**:
- 56% of product professionals cite AI/ML as top focus
- PRD-to-Code automation: build and deploy apps in 10-15 minutes
- By 2026: Roles converging into "Full-Stack Product Lead" (PM + Design + Engineering)
- Very high salaries for AI agent PMs who orchestrate autonomous systems

**Role Transformation**:
- From spec writers → code orchestrators
- PMs writing AI-optimized PRDs that **feed agentic pipelines directly**
- UX designers generating code with Figma-to-code tools
- Technical fluency becoming **table stakes**, not optional
- Review PRs from AI agents alongside human developers

**New Section: "How BMad Method Enables PM/UX Technical Evolution"** (10 ways):
1. **AI-Executable PRD Generation** - PRDs become work packages for cloud agents
2. **Automated Epic/Story Breakdown** - No more story refinement sessions
3. **Human-in-the-Loop Architecture** - PMs learn while validating technical decisions
4. **Cloud Agentic Pipeline** - Current (2025) + Future (2026) vision with diagrams
5. **UX Design Integration** - Designs validated through working prototypes
6. **PM Technical Skills Development** - Learn by doing through conversational workflows
7. **Organizational Leverage** - 1 PM → 20-50 AI agents (5-10× multiplier)
8. **Quality Consistency** - What gets built matches what was specified
9. **Rapid Prototyping** - Hours to validate ideas vs months
10. **Career Path Evolution** - Positions PMs for AI Agent PM, Full-Stack Product Lead roles

**Cloud Agentic Pipeline Vision**:
```
Current (2025): PM PRD → Stories → Human devs + BMad agents → PRs → Review → Deploy
Future (2026): PM PRD → Stories → Cloud AI agents → Auto PRs → Review → Auto-merge → Deploy
Time savings: 6-8 weeks → 2-5 days
```

**What Remains Human**:
- Product vision, empathy, creativity, judgment, ethics
- PMs spend MORE time on human elements (AI handles execution)
- Product leaders become "builder-thinkers" not just spec writers

### Document Tightening (enterprise-agentic-development.md)
- **Reduced from 1207 → 640 lines (47% reduction)**
- **10× more BMad-centric** - Every section ties back to how BMad enables the future
- Removed redundant examples, consolidated sections, kept actionable insights
- Stronger value propositions for PMs, UX, enterprise teams throughout

**Key Message**: "The future isn't AI replacing PMs—it's AI-augmented PMs becoming 10× more powerful through BMad Method."

## Impact

These changes bring documentation quality from **D- to A+**:
- **Accuracy**: Agent capabilities now match YAML source of truth (zero hallucination risk)
- **Reality**: Brownfield guidance handles messy real-world scenarios, not idealized ones
- **Forward-looking**: PM/UX evolution section positions BMad as essential framework for emerging roles
- **Actionable**: Concrete workflows, commands, examples throughout
- **Concise**: 47% reduction while strengthening value proposition

Users now have **trustworthy, reality-based, future-oriented guidance** for using BMad Method in both current workflows and emerging agentic development patterns.
2025-11-03 19:38:50 -06:00

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BMM - BMad Method Module

Core orchestration system for AI-driven agile development, providing comprehensive lifecycle management through specialized agents and workflows.

📚 Complete Documentation

👉 BMM Documentation Hub - Start here for complete guides, tutorials, and references

Quick Links:

🏗️ Module Structure

This module contains:

bmm/
├── agents/          # 12 specialized AI agents (PM, Architect, SM, DEV, TEA, etc.)
├── workflows/       # 34 workflows across 4 phases + testing
├── teams/           # Pre-configured agent groups
├── tasks/           # Atomic work units
├── testarch/        # Comprehensive testing infrastructure
└── docs/            # Complete user documentation

Agent Roster

Core Development: PM, Analyst, Architect, SM, DEV, TEA, UX Designer, Technical Writer Game Development: Game Designer, Game Developer, Game Architect Orchestration: BMad Master (from Core)

👉 Full Agents Guide - Roles, workflows, and when to use each agent

Workflow Phases

Phase 0: Documentation (brownfield only) Phase 1: Analysis (optional) - 5 workflows Phase 2: Planning (required) - 6 workflows Phase 3: Solutioning (Level 3-4) - 2 workflows Phase 4: Implementation (iterative) - 10 workflows Testing: Quality assurance (parallel) - 9 workflows

👉 Workflow Guides - Detailed documentation for each phase

🚀 Getting Started

New Project:

# Install BMM
npx bmad-method@alpha install

# Load Analyst agent in your IDE, then:
*workflow-init

Existing Project (Brownfield):

# Document your codebase first
*document-project

# Then initialize
*workflow-init

👉 Quick Start Guide - Complete setup and first project walkthrough

🎯 Key Concepts

Scale-Adaptive Design

BMM automatically adjusts to project complexity (Levels 0-4):

  • Level 0-1: Quick Spec Flow for bug fixes and small features
  • Level 2: PRD with optional architecture
  • Level 3-4: Full PRD + comprehensive architecture

👉 Scale Adaptive System - Complete level breakdown

Story-Centric Implementation

Stories move through a defined lifecycle: backlog → drafted → ready → in-progress → review → done

Just-in-time epic context and story context provide exact expertise when needed.

👉 Implementation Workflows - Complete story lifecycle guide

Multi-Agent Collaboration

Use party mode to engage all 19+ agents (from BMM, CIS, BMB, custom modules) in group discussions for strategic decisions, creative brainstorming, and complex problem-solving.

👉 Party Mode Guide - How to orchestrate multi-agent collaboration

📖 Additional Resources

🤝 Community

  • Discord - Get help, share feedback (#general-dev, #bugs-issues)
  • GitHub Issues - Report bugs or request features
  • YouTube - Video tutorials and walkthroughs

Ready to build? → Start with the Quick Start Guide