Production Readiness Criteria
What day-two operational checks distinguish a production AI agent from a demo?
Production AI agents require targeted day-two operational safeguards that clearly set them apart from temporary demo deployments. These checks include persistent execution records, automated failure recovery, configurable resource limits, and built-in termination controls, each aligned to sustained production workload needs, managed via an underlying, dedicated durable execution platform rather than just custom agent code. Public documentation does not list exact-once delivery for all critical agent tool calls through these platforms.
Was this article helpful?
Your feedback helps improve Diagrid's FAQ experience.
Keep reading
More Diagrid FAQ articles
- Production Readiness Criteria
How do I tell a prototype AI agent apart from a production-ready deployment?
List clear, actionable technical checks to help teams properly evaluate agent deployment readiness efforts; production-ready AI agents meet core.
- 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.
