AI Agents Don’t Need More Context — They Need Typed Context

The article argues that AI agents face a context typing issue rather than merely a lack of context. It explains how flattening instructions, memory, evidence, and tool outputs into a single string erases semantic boundaries, and presents a lightweight, zero‑dependency Python runtime that preserves these boundaries, tracks provenance, and rejects invalid transformations before they reach the model. The post details the implementation, testing, and the guarantees and limitations of this approach.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Towards Data Science.

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