The Missing Engineering Stack for Production AI Agents

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The "build an agent in 5 minutes" tutorials get you to a demo. They don't get you to production. Here's the field guide for the four primitives that decide whether your agent survives contact with real users, real data, and real adversaries — context-window discipline, skill composition, capability-based security, and drift telemetry. Concrete patterns, named tradeoffs, and the enterprise integrations that let you ship past prototype.

This is part 1 of a 3-post series. Part 2 — Why current IDEs need to be redesigned for the agent era — covers the developer-tooling argument. Part 3 introduces what I'm shipping next.

1. Tokens — context-window discipline

A token is the unit of inference cost, the unit of latency, and the unit of model attention. Treat it like memory in a 1990s embedded system: budget every byte, evict aggressively, and never assume the next call gets the same allocation.

Prompt caching is...

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