Writing effective tools for AI agents—using AI agents

Anthropic’s sharpening the blueprint for building tools that play nice with LLM agents. Their Model Context Protocol (MCP) leans hard into three pillars: test in loops, design for humans, format like context matters—because it does.

They co-develop tools with agents like Claude Code. That means prototyping side-by-side, pressure-testing with structured evals, and prompt-wrangling tool specs until Claude stops hallucinating and starts calling the right APIs.

Big shift: You're no longer building for checkbox-clicking APIs. You're building for opinionated, non-deterministic models with vibes. Forget rigid abstractions. Focus on flexible scaffolding, tight eval cycles, and giving the model what it needs, when it needs it.