Two Knowledge Hierarchies: Structuring Context for AI Agents and LLMs

TestSmith has two distinct audiences that need context about the project: AI agents that work on the TestSmith codebase (helping develop and extend it), and the LLM that generates test code for your project at runtime. These are different problems with different solutions.

Layer 1: Agent Context — CLAUDE.md Hierarchies

When an AI agent opens TestSmith to fix a bug or add a feature, it needs to understand the codebase structure without reading every file. A single large context file doesn't work well — an agent fixing a retry bug doesn't need to know the Java driver's fixture generation logic.

The solution is a CLAUDE.md hierarchy:

CLAUDE.md ← package map, invariants, dependency direction