Answer product management's hardest questions in minutes, not days
Expert product management guidance powered by frameworks from Teresa Torres, Marty Cagan, April Dunford, and more - without hiring a product manager.
Right feature. Right users. Right time. Right reasons.
Not a project management tool. Not a generic AI assistant. A specialized copilot that combines:
- Speed of AI (answers in minutes)
- Depth of product management frameworks (Teresa Torres, Marty Cagan, April Dunford)
- Context-aware reasoning (remembers your product, personalizes outputs)
Built for solo developers and small teams who need enterprise product management capabilities without the complexity.
You're a solo founder building your first product. You can code, but product management decisions feel like guesswork:
- "Should I build feature X or Y first?"
- "How do I validate this idea without wasting weeks?"
- "Which users should I target?"
- "When is the right time to launch?"
Generic AI (ChatGPT, Claude): Fast answers, but no product management frameworks or strategic depth Enterprise PM tools (Jira, Aha!): Deep features, but slow, complex, and expensive Manual PM work (Notion, templates): Flexible, but requires expertise you don't have
AI PM Copilot: Expert product management frameworks + AI speed = rigorous answers delivered in minutes.
Built on 16 proven methodologies from product management thought leaders. Context-aware intelligence that remembers your product. Developer-native experience inside Claude Code.
AI PM Copilot isn't generic AI advice - it's built on expert frameworks from product management thought leaders:
Research & Discovery: Teresa Torres (Continuous Discovery), Erika Hall (Just Enough Research)
Strategy & Goals: Marty Cagan (Empowered), Sean Ellis (Product-Market Fit), April Dunford (Positioning)
Execution & Planning: Jeff Patton (Story Mapping), Basecamp (Shape Up), Google (HEART/Goals)
Prioritization: Intercom (RICE), Dan Olsen (Lean Product Playbook)
16 proven methodologies. 100+ templates and frameworks. Expert rigor at AI speed.
Just talk to Claude Code like you would a consultant:
You: "I'm building a SaaS analytics tool. Should I prioritize dashboards or API access first?"
→ product-manager routes to feature-prioritizer
→ Reads your product context from setup
→ Returns scored recommendations with rationale
Result: Expert RICE scoring in 2 minutes with explanation of why each feature ranks where it does.
Try it yourself:
- Install:
/plugin install ai-pm-copilot - Setup (optional, 5-10 min):
/ai-pm-copilot:pm-setup - Ask: "Should I prioritize feature X or Y?"
8 Expert Product Management Agents - Available 24/7 for research, strategy, execution, and launch (1 orchestrator + 7 specialists)
1 Utility Agent - Automated codebase context discovery (context-scanner)
3 Multi-Agent Team Presets - Validation sprints, PRD stress tests, competitive war rooms
16 Proven Frameworks - RICE, JTBD, Lean Startup, Story Mapping, and more
100+ Templates & Assets - PRD templates, roadmap frameworks, interview guides
Context-Aware Intelligence - One-time setup, personalized outputs across all agents
Built on frameworks from Teresa Torres, Marty Cagan, April Dunford, Sean Ellis, Jeff Patton, and more.
/plugin marketplace add https://github.com/slgoodrich/agents
/plugin install ai-pm-copilotSpend 5-10 minutes setting up context once, save 80% of questions across all future interactions:
/ai-pm-copilot:pm-setup"Should I prioritize feature X or Y?"
"Design a user interview study for churn"
"Score these 5 features with RICE"
Get expert product management guidance in minutes, not days. No signup. No API keys. Just install and ask.
Feature validation:
"I want to add real-time collaboration. Is this worth building?"
→ Coordinates research-ops for validation, feature-prioritizer for scoring
Planning:
"Plan next quarter focused on retention"
Documentation:
"Write a PRD for SSO integration"
Quarterly Goals:
"Create Q2 goals for a pre-PMF SaaS product"
Market analysis:
"Research the competitive landscape for project management tools"
Roadmap:
"Build a now-next-later roadmap for next 6 months"
User research:
"Design a study to understand user onboarding pain points"
Validation:
"Help me validate this feature hypothesis with 10 user interviews"
Synthesis:
"Analyze these interview transcripts and identify top 3 insights"
Go-to-market:
"Create a beta launch plan for our API product"
Positioning:
"Develop positioning for a new pricing tier"
Multi-agent team presets for high-stakes product decisions. Multiple agents work in parallel, challenge each other's conclusions, and synthesize competing perspectives.
Requires Claude Code's Agent Teams feature. Check https://docs.anthropic.com/en/docs/claude-code for setup instructions.
/agent-teams:validation-sprint "AI-powered code review tool for solo developers"
Three agents investigate in parallel (idea-researcher, market-researcher, idea-skeptic), cross-examine each other's findings, and deliver a BUILD / DON'T BUILD / NEEDS MORE EVIDENCE verdict.
/agent-teams:prd-stress-test path/to/prd.md
Three reviewers (market-fit, feasibility, scope) score your PRD independently, flag conflicts between their reviews, and deliver a READY TO BUILD / NEEDS REVISION / MAJOR REWORK verdict.
/agent-teams:competitive-war-room "Notion, Coda, Slite"
One researcher per competitor runs a deep-dive in parallel. Results are synthesized into a positioning map, battle cards, and strategic recommendations.
The toolkit provides 1 orchestration agent, 7 specialist agents, and 1 utility agent that work together to cover the complete product lifecycle:
Your primary entry point - Intelligent agent that routes requests to specialized experts
Use for:
- General product management questions and guidance
- Multi-faceted problems requiring multiple perspectives
- When unsure which specialist to consult
Example:
"I need to validate a feature idea, prioritize it, and plan delivery"
→ Routes to research-ops, feature-prioritizer, and requirements-engineer
Market research, competitive analysis, and positioning
Use for:
- Competitive landscape analysis
- Market sizing and opportunity assessment
- Product positioning and differentiation
- TAM/SAM/SOM calculations
- Win/loss analysis
Example:
"Analyze our position against competitors in the project management space"
"Research competitive landscape for project management tools"
User research, interviews, and validation
Use for:
- User interview planning and synthesis
- Usability testing
- Problem/solution validation
- Customer feedback analysis
- Research program design
Example:
"Design a study to understand why 30% of users churn after first month"
"Synthesize these interview transcripts into themes and insights"
Vision, strategy, and goals
Use for:
- Product vision and strategy
- Quarterly and annual goals
- Strategic roadmaps
- North Star metric definition
- Strategic trade-offs
Example:
"Create Q2 goals focused on reaching product-market fit"
Roadmap planning and sequencing
Use for:
- Now-Next-Later roadmaps
- Theme-based roadmaps
- Quarterly planning
- Feature sequencing and phasing
- Milestone planning
Example:
"Build a 6-month roadmap for our mobile app launch"
RICE, ICE, and prioritization frameworks
Use for:
- RICE/ICE scoring
- Kano model analysis
- Value vs Effort matrices
- Trade-off decisions
- Backlog ranking
Example:
"Score these 10 features using RICE framework"
PRDs, specs, and user stories
Use for:
- Product requirements documents (PRDs)
- Technical specifications
- User story writing
- Acceptance criteria
- Feature documentation
Example:
"Write a comprehensive PRD for dark mode feature"
Go-to-market and launch execution
Use for:
- Launch planning and execution
- GTM strategy and distribution channel selection
- Beta programs
- Launch messaging and positioning
- Community launches (Product Hunt, Hacker News, Reddit)
Example:
"Create a launch plan for our new API product"
Automated strategic context discovery from codebase
Use for:
- Auto-discovering features, tech stack, and integrations during setup
- Refreshing stale context when product changes
- Getting accurate baseline for competitive analysis
- Fast onboarding on existing projects
What it discovers:
- Features (from routes, pages, API endpoints)
- Tech stack (from package.json, requirements.txt, etc.)
- Integrations (from 3rd party packages)
- Project scale (files, LOC, complexity)
What it doesn't do:
- Code quality or architecture analysis
- Performance or security assessment
- Engineering recommendations
Note: This is a utility agent (not a PM specialist) that uses Haiku model for efficient file operations. It's automatically invoked by pm-setup when you have an existing codebase, or can be invoked by PM agents when they need current product state.
Example (automatic invocation):
/ai-pm-copilot:pm-setup
→ Detects codebase
→ "Scan codebase to auto-discover context? (yes/no)"
→ If yes: context-scanner runs, presents findings for validation
→ Time saved: 10-15 minutes vs manual entry
The product-manager agent acts as an intelligent router that:
- Analyzes your request to understand the product management discipline(s) needed
- Routes to the appropriate specialist agent(s)
- Coordinates multi-agent workflows when needed
- Synthesizes outputs from multiple specialists
Simple routing:
"Help me prioritize features"
→ product-manager routes to feature-prioritizer
Multi-agent workflow:
"Validate this feature idea and create a launch plan"
→ product-manager routes to research-ops (validation)
→ Then to launch-planner (GTM strategy)
→ Synthesizes complete plan
Direct to specialist: If your question clearly fits one domain, Claude Code may route directly to the specialist without going through product-manager first.
Skills are knowledge frameworks that agents load progressively when needed, organized by the product development journey:
Is this idea worth my time? Who are my competitors?
- competitive-analysis-templates - SWOT, Porter's Five Forces, competitive positioning
- market-sizing-frameworks - TAM/SAM/SOM, market validation
- product-positioning - April Dunford framework, differentiation strategy
Who are my users? What problems am I solving?
- user-research-techniques - Interviews, surveys, usability testing, JTBD
- interview-frameworks - Interview design, questioning, synthesis
- synthesis-frameworks - Affinity mapping, insight generation
- usability-frameworks - Usability testing, Nielsen principles
- validation-frameworks - Problem/solution validation, MVP testing
What features do I build? How do I avoid scope creep?
- prioritization-methods - RICE, ICE, Kano, Value vs Effort
- product-market-fit - PMF indicators, Sean Ellis test, MVP scoping
Clear requirements, user stories, acceptance criteria
- specification-techniques - Requirements writing, clarity
- prd-templates - PRD formats and best practices
- user-story-templates - User story formats, INVEST criteria
Phase 1, 2, 3 and milestone planning
- roadmap-frameworks - Now-Next-Later, outcome-based roadmaps
Where do I launch? What's my messaging?
- go-to-market-playbooks - GTM strategies, distribution channels
- launch-planning-frameworks - Launch tiers, timelines, execution
- pm-setup - Interactive wizard for product context initialization
- codebase-scanning - Automated feature and tech stack discovery from code
One-time context setup that makes everything better.
Creates 8 core context files that all agents reference:
.claude/product-context/
├── product-info.md # Product description, users, value prop
├── business-metrics.md # ARR, users, growth, retention
├── strategic-goals.md # Goals, priorities, themes
├── current-roadmap.md # Now-Next-Later roadmap
├── tech-stack.md # Architecture, tech, constraints
├── customer-segments.md # Personas, segments, ICP
├── team-info.md # Team size, roles, constraints
└── competitive-landscape.md # Competitors, positioning
Benefits:
- Agents ask 80% fewer questions
- Outputs are product-specific, not generic
- Context reused across all agents and skills
Usage:
# First-time setup
/ai-pm-copilot:pm-setup
# Update context later
/ai-pm-copilot:pm-setup --update- Two plugins - core PM toolkit (ai-pm-copilot) + multi-agent team presets (agent-teams)
- Main orchestration agent + 7 specialist agents + 6 team agents with clear responsibilities
- Intelligent routing through main product-manager agent
- Progressive skills that load on-demand
- Solo developer focus - no enterprise complexity
- Natural conversation instead of memorizing commands
- Agents collaborate automatically
- Context flows between specialists
- Simpler mental model
- Install what you need: core plugin or full suite
- Expert-level strategic reasoning
- Nuanced decision-making
- Context-aware responses
- High-quality outputs
Use requirements-engineer to create Product Requirements Documents with automatic template selection:
"Write a PRD for [your feature]"
Intelligent Template Selection: requirements-engineer uses complexity assessment to automatically select the right template:
How it works:
- Assesses 3 dimensions: Technical Complexity, Risk/Impact, Scope Breadth (0-10 each)
- Reads repository context (
.claude/product-context/tech-stack.md, etc.) for informed scoring - Applies decision thresholds based on average complexity score
- Communicates reasoning transparently with complexity breakdown
Templates:
- Lean PRD (1-2 pages): Low complexity (avg < 4), < 1 week, simple features
- Comprehensive PRD (3-5 pages): Moderate complexity (avg 4-7), standard features [DEFAULT]
- Amazon PR/FAQ (3-6 pages): New products (detected by keywords)
- Google PRD (5-10 pages): High risk (security/payments) or scale-critical (high complexity)
Example reasoning: "OAuth authentication" → Google PRD (Risk: 9/10 security-critical, triggers high-detail template)
You can always request a different template if the automatic selection doesn't fit your needs.
Storage:
PRDs are automatically saved to prds/[feature-name].md using kebab-case naming:
prds/dark-mode.mdprds/csv-export.mdprds/user-notifications.md
Built for solo developers and small teams who need:
- Enterprise product management capabilities without complexity
- Conversational interface, not command memorization
- Intelligent routing to the right expertise
- Progressive learning and guidance
Perfect for:
- Solo founders building their first product
- Small teams without a dedicated product manager
- Developers transitioning to product roles
- Side projects and indie hackers
Not designed for:
- Enterprise organizations with product management teams
- Complex stakeholder management scenarios
- Large-scale portfolio management
- Multiple product lines with dependencies
- Architecture - Agent-first design and system overview
- Agents - Complete agent reference and capabilities
- Skills - Framework knowledge and progressive disclosure
- Usage - Patterns, workflows, and best practices
- Plugins - Plugin structure and organization
This plugin was inspired by wshobson/agents. If, like me, you're not a software developer by trade, I highly recommend checking out that repository to get better results from Claude Code.
Contributions welcome! This toolkit grows with the community.
Ways to contribute:
- Report bugs or issues
- Suggest new features or improvements
- Share usage examples and workflows
- Improve documentation
- Add new skills or assets
See CONTRIBUTING.md for detailed guidelines.
- Claude Code
- Basic familiarity with product management concepts
- Documentation - See docs/ directory
- Issues - GitHub Issues
- Discussions - GitHub Discussions
This project is licensed under the PolyForm Noncommercial License 1.0.0. See LICENSE for details.
Empowering solo developers and small teams with enterprise product management capabilities through conversational AI agents.