claude

pm-ai-products

PM skills for building AI-native products: strategy, requirements, risk assessment, metrics, experiment design, agent UX, and AI market sizing.

0 on GitHubby Paweł Hurynv1.0.0MITupdated 8 months agoproduct-management
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Plugin pm-ai-products from marketplace pm-skills in tomershahar/pm-skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (7)

  • agent-ux-design

    Design UX for agentic AI workflows: task delegation, human-in-the-loop checkpoints, error recovery, and trust calibration. Use when designing a product where AI takes multi-step actions on behalf of users.

  • ai-experiment-design

    Design experiments to validate AI features: evaluation datasets, shadow mode deployment, A/B testing, and feedback loop design. Use when planning how to test an AI feature before or after launch.

  • ai-market-sizing

    Estimate TAM/SAM/SOM for an AI product accounting for compute costs, commoditization risk, and platform dependency. Use when sizing the market for an LLM-based or ML-powered product.

  • ai-metrics-framework

    Design a metrics framework for an AI product combining model quality metrics with product and business metrics. Use when setting up measurement for an AI feature or LLM-based product.

  • ai-product-requirements

    Write product requirements for an AI feature covering model behavior specs, training data needs, edge cases, fallback design, and evaluation criteria. Use when writing a PRD for an LLM-based or ML-powered feature.

  • ai-product-strategy

    Create a product strategy for an AI-native product covering data moats, model improvement loops, AI value propositions, and defensibility. Use when building strategy for LLM-based, ML-powered, or agentic products.

  • ai-risk-assessment

    Identify and prioritize AI-specific risks: hallucination, bias, drift, privacy, security, and regulatory exposure. Use when launching an AI feature, reviewing an AI product, or preparing for compliance.

Slash commands (3)

  • /pm-ai-products:ai-prd

    Write a PRD for an AI feature including model behavior specs, evaluation criteria, and fallback design

  • /pm-ai-products:ai-risk

    Run an AI risk assessment covering hallucination, bias, drift, privacy, security, and regulatory exposure

  • /pm-ai-products:ai-strategy

    Create a full product strategy for an AI-native product

View source on GitHub productcompass.pm

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