Part 2 of 3 — building and testing MCP agents Every AI agent is a bundle of decisions, most of which get made once, informally, and never revisited: which model, what system prompt, which tools it's allowed to touch, how many steps it gets before you give up on it. Nobody writes these down as a config. They just happen, in code, and then everyone forgets they were choices at all. In Part 1 I argued those decisions have a shape: an agent definition (the class — loop, system context, capa...