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All documentation now accurately reflects what agents can actually do per their YAML configurations, not assumptions or outdated info.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of 3)**: - **Scenario A**: No documentation → document-project (was covered) - **Scenario B**: Docs exist but massive/outdated/incomplete → **document-project** (NEW - very common) - **Scenario C**: Good docs but no structure → **shard-doc → index-docs** (NEW - handles massive files) -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500 lines, 10+ level 2 sections) - Explicit guidance on why regenerate vs index (outdated docs cause hallucinations) - Impact explanation: how bad docs break AI workflows (token limits, wrong assumptions, broken integrations) **Principle**: "When in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. |
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README.md
BMM Workflows - Complete v6 Guide
Master guide for BMM's four-phase methodology that adapts to project scale (Level 0-4) and context (greenfield/brownfield).
Table of Contents
- Core Innovations
- Universal Entry Point
- Four Phases Overview
- Phase Details
- Scale Levels
- Greenfield vs Brownfield
- Critical Rules
Core Innovations
- Scale-Adaptive Planning - Automatic routing based on complexity (Level 0-4)
- Just-In-Time Design - Tech specs created per epic during implementation
- Dynamic Expertise Injection - Story-specific technical guidance
- Continuous Learning Loop - Retrospectives improve each cycle
- Document Sharding Support - All workflows handle whole or sharded documents for efficiency
Universal Entry Point
Always start with workflow-status or workflow-init
workflow-status
- Checks for existing workflow status file
- Displays current phase and progress
- Routes to appropriate next workflow
- Shows Phase 4 implementation state
workflow-init
- Creates initial bmm-workflow-status.md
- Detects greenfield vs brownfield
- Routes undocumented brownfield to document-project
- Sets up workflow tracking
Four Phases Overview
PREREQUISITE: document-project (brownfield without docs)
↓
PHASE 1: Analysis (optional)
brainstorm → research → brief
↓
PHASE 2: Planning (required, scale-adaptive)
Level 0-1: tech-spec only
Level 2-4: PRD + epics
↓
PHASE 3: Solutioning (Level 2-4 only)
architecture → validation → gate-check
↓
PHASE 4: Implementation (iterative)
sprint-planning → epic-context → story cycle
Phase Details
Documentation Prerequisite
When: Brownfield projects without documentation OR post-completion cleanup
| Workflow | Purpose | Output |
|---|---|---|
| document-project | Analyze and document codebase | Comprehensive docs |
Use Cases:
- Pre-Phase 1: Understand existing brownfield code
- Post-Phase 4: Create clean documentation replacing scattered artifacts
Phase 1: Analysis
Optional workflows for discovery and requirements gathering
| Workflow | Agent | Purpose | Output |
|---|---|---|---|
| brainstorm-project | Analyst | Software ideation | Architecture proposals |
| brainstorm-game | Game Designer | Game concept ideation | Concept proposals |
| research | Analyst | Multi-mode research | Research artifacts |
| product-brief | Analyst | Strategic planning | Product brief |
| game-brief | Game Designer | Game foundation | Game brief |
Phase 2: Planning
Required phase with scale-adaptive routing
| Workflow | Agent | Output | Levels |
|---|---|---|---|
| prd | PM | PRD.md + epics | 2-4 |
| tech-spec | PM | tech-spec.md | 0-1 |
| gdd | Game Designer | GDD.md | Games |
| create-ux-design | UX | ux-design.md | Conditional |
Phase 3: Solutioning
Architecture phase for Level 2-4 projects
| Workflow | Agent | Purpose | Output |
|---|---|---|---|
| create-architecture | Architect | System design | architecture.md + ADRs |
| validate-architecture | Architect | Design validation | Validation report |
| solutioning-gate-check | Architect | PRD/UX/arch check | Gate report |
Phase 4: Implementation
Sprint-based development cycle
Sprint Status System
Epic Flow: backlog → contexted
Story Flow: backlog → drafted → ready-for-dev → in-progress → review → done
Implementation Workflows
| Workflow | Agent | Purpose | Status Updates |
|---|---|---|---|
| sprint-planning | SM | Initialize tracking | Creates sprint-status.yaml |
| epic-tech-context | SM | Epic technical context | Epic: backlog → contexted |
| create-story | SM | Draft story files | Story: backlog → drafted |
| story-context | SM | Implementation guidance | Story: drafted → ready-for-dev |
| dev-story | DEV | Implement | Story: ready-for-dev → in-progress → review |
| code-review | DEV | Quality validation | No auto update |
| retrospective | SM | Capture learnings | Retrospective: optional → completed |
| correct-course | SM | Handle issues | Adaptive |
Implementation Loop
sprint-planning (creates sprint-status.yaml)
↓
For each epic:
epic-tech-context
↓
For each story:
create-story → story-context → dev-story → code-review
↓
Mark done in sprint-status.yaml
↓
retrospective (epic complete)
Scale Levels
| Level | Scope | Documentation | Path |
|---|---|---|---|
| 0 | Single change | tech-spec only | Phase 2 → 4 |
| 1 | 1-10 stories | tech-spec only | Phase 2 → 4 |
| 2 | 5-15 stories | PRD + architecture | Phase 2 → 3 → 4 |
| 3 | 12-40 stories | PRD + full arch | Phase 2 → 3 → 4 |
| 4 | 40+ stories | PRD + enterprise arch | Phase 2 → 3 → 4 |
Greenfield vs Brownfield
Greenfield (New Projects)
Phase 1 (optional) → Phase 2 → Phase 3 (L2-4) → Phase 4
- Clean slate for design
- No existing constraints
- Direct to planning
Brownfield (Existing Code)
document-project (if needed) → Phase 1 (optional) → Phase 2 → Phase 3 (L2-4) → Phase 4
- Must understand existing patterns
- Documentation prerequisite if undocumented
- Consider technical debt in planning
Critical Rules
Phase Transitions
- Check workflow-status before any Phase 1-3 workflow
- Document brownfield before planning if undocumented
- Complete planning before solutioning
- Complete architecture (L2-4) before implementation
Implementation Rules
- Epic context first - Must context epic before drafting stories
- Sequential by default - Work stories in order within epic
- Learning transfer - Draft next story after previous done
- Manual status updates - Update sprint-status.yaml as needed
Story Management
- Single source of truth - sprint-status.yaml tracks everything
- No story search - Agents read exact story from status file
- Context injection - Each story gets specific technical guidance
- Retrospective learning - Capture improvements per epic
Best Practices
- Trust the process - Let workflows guide you
- Respect scale - Don't over-document small projects
- Use status tracking - Always know where you are
- Iterate and learn - Each epic improves the next
- Consider sharding - Split large documents (PRD, epics, architecture) for efficiency
Document Sharding
For large multi-epic projects, consider sharding planning documents to improve workflow efficiency.
What is Sharding?
Splits large markdown files into smaller section-based files:
- PRD with 15 epics →
prd/epic-1.md,prd/epic-2.md, etc. - Large epics file → Individual epic files
- Architecture layers → Separate layer files
Benefits
Phase 1-3 Workflows:
- Workflows load entire sharded documents (transparent to user)
- Better organization for large projects
Phase 4 Workflows:
- Selective loading - Only load the epic/section needed
- Massive efficiency - 90%+ token reduction for 10+ epic projects
- Examples:
epic-tech-context,create-story,story-context,code-review
Usage
Load bmad-master or analyst agent:
/shard-doc
Source: docs/PRD.md
Destination: docs/prd/
All BMM workflows automatically support both whole and sharded documents.
For specific workflow details, see individual workflow READMEs in their respective directories.