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Original article date: Apr 03, 2026

Skill Refinery Wants to Put Expert Business Methodology Inside Your AI Assistant

April 10, 2026
5 min read

A new Dallas-based platform called Skill Refinery is solving a problem most AI users haven't named yet: the world's best business frameworks, leadership methods, and coaching strategies exist in books and courses that AI can't access — until now.

What Skill Refinery Does

Founded by Matt Cretzman, Skill Refinery converts expert intellectual property into structured "skill cards" that work directly inside Claude, ChatGPT, and Microsoft Copilot via the Model Context Protocol (MCP). The platform's extraction engine processes books, courses, audiobooks, and transcripts in minutes. A typical 200-page business book yields 30–80 structured skill cards, each representing a discrete methodology an AI assistant can apply to real situations in real time.

The AI skills ecosystem is growing fast — more than 5,800 MCP servers are now available with over 97 million monthly SDK downloads — but Cretzman argues that virtually all of them are technical tools. The $15 billion coaching and professional development industry has had no scalable infrastructure for delivering expert methodology through AI. That's the gap Skill Refinery targets.

Key Takeaways

  • Experts earn a 50/50 revenue split with no upfront cost to participate — the platform handles distribution
  • The platform's first published expert is Tony Jeary ("The RESULTS Guy"), a strategist who has coached Fortune 500 leaders at Walmart, Ford, Samsung, Shell, and American Airlines
  • Source files never re-enter AI context windows after extraction — a critical IP protection distinction for organizations concerned about data governance
  • The platform supports creator storefronts, enterprise knowledge libraries, and advisory community hubs

If you work with coaches, authors, or expert advisors, this is a platform worth watching. Proprietary methodology is a competitive asset — and making it accessible inside the AI tools your team already uses changes how knowledge gets applied at scale.

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