GUIDE

AI Agents in Production: Autonomy Needs Approval, Memory and Audit

A practical framework for taking tool-using agents from a demo to a safe and measurable production workflow.

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AI Agents in Production: Autonomy Needs Approval, Memory and Audit

Agents are becoming operational software

An agent is not just a chat interface with a longer prompt. It can inspect context, select tools, maintain state and take actions. That makes it useful, but it also means the architecture must handle identity, permissions, budgets, observability and rollback.

Start with a bounded workflow

Choose a task with a clear input, output and owner. Separate read tools from write tools. Require approval for external side effects. Store durable memory separately from temporary context, and define retention and deletion rules.

Measure the whole trajectory

Track task completion, tool errors, human interventions, latency, cost and policy violations. A good agent is not the one that takes the most actions; it is the one that completes the task with the fewest unnecessary and risky actions.