Explore essays on governed autonomy, approval design, audit trails, and multiplayer work with AI agents.
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Open protocols are solving how agents reach tools. The harder problem is deciding what an agent may do, proving what it did, and stopping it mid-run. Here is how we think about that.
The jump from AI assistance to AI execution is not a model problem alone. It is an operating model problem: who owns the work, what systems can be touched, and how every action is reviewed.
The engineering behind approval gates: suspension, evidence, expiry, revalidation, revocation, and safe continuation.
Approval is often treated as the thing slowing automation down. In business AI execution, it is the mechanism that lets more work move without pretending every action has the same risk.
Different AI and automation categories solve different parts of the work problem. The missing category is the governed AI agent that can plan, pause, execute, and produce evidence.
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