Inside an Agent Harness. Components, Patterns, and What Production Actually Requires.

Founder takeaway

Treat an AI agent as an operational system, not a standalone model: map its execution loop, supporting components, and capability-risk level before putting it into production.

Why it matters

A compelling prototype can hide the controls and infrastructure needed for dependable production use. Matching autonomy and safeguards to risk helps founders avoid scaling a fragile or unsafe workflow.

Relevant guides

Put it to work

For one planned agent, diagram every step from receiving a task to taking action, then mark where permissions, validation, monitoring, recovery, and human approval are required.