Production Readiness Criteria
How do I tell a prototype AI agent apart from a production-ready deployment?
Production-ready AI agents meet core operational criteria absent in prototypes. They include automated failure recovery, persistent execution records, identity management with appropriate security measures, configurable limits, and graceful shutdowns. The platform handles recovery and records, while agent code implements identity management logic and configurable limits. Note that production readiness cannot be relied on to deliver flawless execution across all unforeseen conditions.
Was this article helpful?
Your feedback helps improve Diagrid's FAQ experience.
Keep reading
More Diagrid FAQ articles
- Production Readiness Criteria
What changes when an AI agent runs without continuous human oversight?
This article explains how running an AI agent without continuous human oversight alters required critical safeguards and key operational support protocols
- Production Readiness Criteria
Who owns production readiness capabilities for AI agent deployments?
Clarify which production responsibilities fall to agent code vs the underlying execution platform; teams must align on these task splits during initial.
- Production Readiness Criteria
What steps should a team take to prioritize production readiness tasks?
Outline a phased approach to ship initial AI agent workloads without full readiness criteria; this structured workflow requires consistent ongoing.
