Skill: danielfoojunwei/ai-product-manager-playbook (version 1.0.0)

--- name: ai-pm-playbook description: "A comprehensive operating system for AI Product Management. Use this skill when planning, prototyping, evaluating, or launching AI-native products. It provides agentic workflows for roadmap planning under uncertainty, rapid prototyping, AI evaluations, cross-functional collaboration, go-to-market strategy, and responsible AI deployment." --- # AI PM Playbook ## Overview The **`ai-pm-playbook`** skill operationalizes the best practices of AI Product Management into executable, agentic workflows. It is designed to help product managers transition from traditional, process-heavy roles to the "builder mentality" required in the AI era. This skill provides a structured approach to the entire AI product lifecycle, ensuring that products are built rapidly, evaluated rigorously, and deployed responsibly. **Use this skill when:** - Prototyping a new AI feature or product. - Planning a product roadmap in a rapidly changing AI landscape. - Designing and running evaluations (Evals) for an AI model. - Structuring a cross-functional AI product team. - Developing a Go-To-Market (GTM) strategy for an AI product. - Implementing ethical guardrails and red teaming for responsible AI. ## The AI PM Operating System This skill is built on the premise that AI automates low-value PM tasks (like writing detailed PRDs) and elevates the need for strategic vision, judgment, and technical fluency. The workflows below are designed to augment these higher-order skills. ## Core Workflows Choose the appropriate workflow based on your current product development phase: ### 1. Prototyping and Rapid Experimentation Move from static PRDs to interactive, "production-ready" prototypes. - **Action:** Decompose features, plan with AI, and build interactive prototypes. - **Reference:** See `references/prototyping_workflow.md` for the step-by-step guide. ### 2. Roadmap Planning Under Uncertainty Shift from feature-based roadmaps to outcome-oriented planning. - **Action:** Define desired behaviors, use the Now/Next/Later framework, and apply the U.S.I.D.O. model. - **Reference:** See `references/roadmap_uncertainty.md` for the planning framework. - **Template:** Use `templates/outcome_roadmap.md` to structure your plan. ### 3. AI Evaluation and Metrics (Evals) Move beyond basic accuracy to measure user experience, safety, and reliability. - **Action:** Define evaluator roles, supply context, set goals, and establish scoring rubrics. - **Reference:** See `references/evaluation_metrics.md` for the evaluation framework. - **Template:** Use `templates/ai_eval_rubric.md` to design your evals. ### 4. Cross-Functional Collaboration Structure your team for success in the complex world of AI development. - **Action:** Implement a hybrid team structure, prioritize data readiness, and foster psychological safety. - **Reference:** See `references/cross_functional.md` for organizational best practices. ### 5. Go-To-Market Strategy and Trust Launch AI products that meet evolving customer expectations and build trust. - **Action:** Define the 7 GTM pillars and prioritize transparency in data usage. - **Reference:** See `references/gtm_strategy.md` for the launch framework. ### 6. Ethics, Safety, and Responsible Deployment Ensure your AI products are safe, trustworthy, and aligned with human values. - **Action:** Implement multi-layered guardrails and conduct rigorous red teaming. - **Reference:** See `references/responsible_ai.md` for the safety framework. - **Template:** Use `templates/red_teaming_plan.md` to structure your testing. ## Self-Improving Loop This skill incorporates a self-improving feedback loop to continuously refine your PM processes based on real-world execution data. 1. **Collect Telemetry:** After completing a major PM activity (e.g., a prototype sprint, an eval run, or a product launch), gather the outcomes, friction points, and user feedback. 2. **Run the Loop:** Execute `scripts/pm_feedback_loop.py` with the collected data. 3. **Analyze and Adapt:** The script will analyze the systemic friction and suggest updates to your templates, workflows, or evaluation rubrics to improve future performance. ## Resources - **`scripts/pm_feedback_loop.py`**: The engine for continuous improvement of PM processes. - **`references/`**: Detailed guides for each of the 6 core workflows. - **`templates/`**: Standardized formats for roadmaps, evals, and red teaming plans.


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