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Plain-language writing on production AI systems: what works, what it costs, and how to own it.

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Practical guides for building owned AI

See what belongs in a task briefing, durable memory, and a reusable procedure, plus the failure mode of mixing them together.

A plain-language guide to the boundaries that determine what an AI employee can access, decide, and leave behind for review.

Why the quality of what your AI sees matters more than which model you pick, and how to audit the context your systems are actually working with.

What we built, what it cost, what broke. No announcements about our announcements.