AI & ML

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How to Design the Trusted Agent Controller: Enterprise Agent Control Plane Series, Part 2

TL;DR A trusted agent controller is the deterministic authority around an AI agent. It owns the run, not the model. The controller should bind authenticated identity to every task, maintain authoritative workflow state, evaluate versioned policy, pause for scoped approvals, enforce budgets and concurrency, coordinate retries and cancellation, terminate unsafe loops, and preserve evidence that

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How to Canary and Roll Back Model, Prompt, or Tool Changes Without Breaking Production

TL;DR Treat every production AI change as a versioned behavior release, not as an isolated model, prompt, or tool edit. Package the model identifier, prompt content, tool schemas, retrieval settings, policy, runtime code, and evaluation thresholds into one immutable release bundle. Prove the candidate offline, replay production traffic in shadow mode without side effects, move

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