•1 min read•from Towards Data Science
AI Agents Don’t Need More Context — They Need Typed Context
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—guarantee.
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Tagged with
#AI Agents
#Context Typing
#Context Problem
#Semantic Boundaries
#Python Runtime
#Provenance Tracking
#Context Transformations
#AI Models
#Instructions
#Memory
#Retrieved Evidence
#Tool Outputs
#Zero-Dependency
#Implementation
#Testing
#Lightweight
#Data Science
#String
#Valid Context
#Runtime