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How we build the execution layer for enterprise AI: the architecture, the security model, and what we learn putting agents to work inside real companies.

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The clearest way to understand the execution layer is to watch an agent run one of your real workflows, inside your own stack, under your own permissions. Talk to us.

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Applets: generate the interface

Two records of every action

The graduation ratchet

Connector permissioning

How an agent asks for permission

Sleep-time compute

The reward desert

There is no benchmark for your definition of quality

Deploying agents in your own VPC

Agents as first-class principals

A filesystem for institutional knowledge

Durable agents on ephemeral compute

Why the orchestration layer wins

Own the data, rent the methods

Runbooks your whole team can read

Prompt injection is an authorization problem

Agents with zero credentials

Giving an agent its own computer

The deployment gap

Same models, different infrastructure

See Context on your own work