Strategic thinking partner for product decisions
Expert system for designing and architecting AI agent workflows based on proven Meta methodologies. Use when users need to build AI agents, create agent workflows, solve problems using agentic systems, integrate multiple tools into agent architectures, or need guidance on agent design patterns. Helps translate business problems into structured agent solutions with clear scope, tool integration, and multi-layer architecture planning.
[ARCHIVED] Full 4D Context Canvas reference. For new AI features, use /spec --ai. For debugging, use /ai-debug. For quality checks, use /context-check.
Full 5-stage PRD framework for complex features. Use for deep PRD work via /spec --deep full-prd. For quick feature specs, use /spec --feature instead.
Expert prompt optimization system for building production-ready AI features. Use when users request help improving prompts, want to create system prompts, need prompt review/critique, ask for prompt optimization strategies, want to analyze prompt effectiveness, mention prompt engineering best practices, request prompt templates, or need guidance on structuring AI instructions. Also use when users provide prompts and want suggestions for improvement.
Shape work using the Shape Up methodology (Ryan Singer, Basecamp). Walk through the 4-step shaping process to create pitches ready for betting. Distinguishes between established product mode (fixed time, variable scope) and new product mode (looser constraints). Use when planning cycle work, writing pitches, or coaching PMs on shaping.
Write specifications at the right depth for any project. Progressive disclosure from quick Linear issues to full AI feature specs. Embeds Linear Method philosophy (brevity, clarity, momentum) with context engineering for AI features. Use for any spec work - quick tasks, features, or AI products.