Agent Skills: 🚀 Skill: Product Pro (v1.1.0)

🚀 Skill: Product Pro (v1.1.0)

Executive Summary

The product-pro is the orchestrator of the product's vision, strategy, and "Magic Moments." In 2026, Product Management has evolved from managing deterministic backlogs to curating Probabilistic AI Loops. This skill focuses on building products that "Think," leveraging Agentic Workflows for rapid validation, and maintaining Strategic Integrity in a world of high-velocity AI development.

📋 Table of Contents

1. AI Product Philosophies
2. The "Do Not" List (Anti-Patterns)
3. Scientific Hypothesis Generation
4. AI Product Strategy
5. Rapid Agentic Prototyping
6. Context Engineering for PMs
7. Reference Library

🏛️ AI Product Philosophies

1. Confidence over Certainty: Design for probabilistic outcomes. What happens at 70% confidence?
2. Magic Moments First: Focus on the core reasoning loop that provides 80% of the value.
3. Context is the Moat: The more your AI knows about the user's domain, the harder you are to replace.
4. Agentic Velocity: Use AI agents to build and test prototypes in days.
5. Ethical Guardianship: Ensure that AI decisions are transparent, biased-free, and secure.

🚫 The "Do Not" List (Anti-Patterns)

| Anti-Pattern | Why it fails in 2026 | Modern Alternative | | :--- | :--- | :--- | | Deterministic Roadmaps | AI features fail or pivot rapidly. | Use Experiment Loops. | | Silent AI Failures | Destroys user trust instantly. | Use Graceful Uncertainty UI. | | "AI for AI's Sake" | High cost, low business value. | Problem-First Integration. | | Thin Context | Leads to hallucinations. | Context Engineering. | | Ignoring Data Privacy| Legal and brand catastrophe. | Privacy-by-Design Architecture. |

🧪 Scientific Hypothesis Generation

We use a rigorous method to test AI improvements:

1. Observation: "Users are confused by Feature X."
2. Hypothesis: "If we add a Reasoning Agent to Feature X, then completion rate will rise 20%."
3. Experiment: Build a minimal agentic prototype.
4. Validation: Measure helpfulness and accuracy logs.

📖 Reference Library

Detailed deep-dives into AI Product Excellence:

• AI Product Strategy: Navigating the probabilistic era.
• Rapid Prototyping: Building with agentic velocity.
• Context Engineering: Curating truth for AI agents.
• Hypothesis Criteria: Framework for rigorous testing.

Updated: January 22, 2026 - 20:30