エピソード

  • The 90% AI Agent Problem

    The 90% AI Agent Problem
    2026/04/18
    Building an AI agent that works is easy. Building one that doesn't break is 90% of the work. In this episode, I break down the five pillars of agent architecture, the LLM vs. Code divide, and how I improved a production agent from 40% to 60% using code changes alone.
    続きを読む 一部表示
    19 分
  • The Complete AI Architecture Deep Dive: From LLM to Autonomous Agent (48 min)

    The Complete AI Architecture Deep Dive: From LLM to Autonomous Agent (48 min)
    2026/03/28
    The extended 48-minute deep dive into every layer of the AI stack — tokenization costs, Function Calling in production, MCP server architecture, real-world agents (Claude Code, Cursor, Copilot), progressive disclosure, and token economics. For engineers who want the full picture.
    続きを読む 一部表示
    48 分
  • The AI Stack Explained: LLM, Token, Context, Function Calling, MCP, Agent, Skill — They're All the Same Thing

    The AI Stack Explained: LLM, Token, Context, Function Calling, MCP, Agent, Skill — They're All the Same Thing
    2026/03/28
    A 22-minute first-principles breakdown of the entire AI stack. An LLM can only output text — the program does everything else. Learn how Function Calling, MCP, Agents, and Skills all follow one pattern: LLM talks, program walks.
    続きを読む 一部表示
    22 分