AI Agents Don’t Need More Context — They Need Typed Context
Provides architectural patterns for developers building complex agent systems with multiple context sources to improve correctness and observability.
AI Summary
A lightweight Python runtime introduces a context type system that enforces type safety on agent context objects before serialization to prevent type confusion bugs.
Excerpt
AI agents don’t just have a context problem—they have a context typing problem. When instructions, memory, retrieved evidence, and tool outputs are flattened into one string, their semantic boundaries can disappear. I built a lightweight, zero-dependency Python runtime that keeps those boundaries explicit, tracks provenance, and rejects invalid context transformations before they reach the model. This article walks through the implementation, tests, and what this approach does—and does not—guara