Levels of AI Mastery

• Level 1: Foundation concepts
  • MCP
    • reaches into software ecosystems outside of AI agent’s knowledge via helper processes
  • skills
    • context efficiency
    • composeability
    • encapsulation of reuseable unit of work
    • supported by multiple vendor products: Claude Code, Codex, Github Copilot and more
    • opens Pandora box of governance challenges more so than MCP, unless if there are guardrails such as entitlement, sandbox or server-side protections
  • Claude hooks
    • lifecycle management
  • Claude subagent
    • context management
  • Claude commands
• Level 2: Better harness
  • orchestrate AI Agents continuously with limit awareness
  • structured storage of conversation history with AI capabilities
  • control over distribution channels: internet-facing web, mobile, local CLI agnostic of vendor-specific solutions
• Level 3: Autonomous
  • automated introspection of execution log to improve token efficiency and reliability
  • automated discovery and organization of knowledge
  • rapid mobilization of information advantage

Back to index