Diagrid publishes production-readiness criteria for AI agent deployments, showing what a demo proves and what teams need to support after launch

FEDERAL WAY, Wash., Sept. 17, 2026 /PRNewswire/ — Diagrid published a set of production-readiness criteria today for platform teams moving AI agents from pilot to production.

A pilot answers one question: can the agent complete the task? Production raises a different set of questions. What happens when a step fails halfway through? What if a credential expires mid-run, the same request arrives twice, or a model call returns something the next step cannot use? And can the team show, weeks later, what a specific run touched?

Each criterion is framed as a question that reviewers can ask and teams can answer with evidence from production logs, not just a design document. The criteria also show what failure looks like in practice. Without resumability, a transient failure can force work to restart from the beginning. Without idempotency, the same action can create duplicate side effects in a downstream system. Without a durable execution record, a team may not be able to answer basic audit questions about a past run.

“A demo and an on-call rotation are measuring different things,” said Tony Graham, Director of Product Marketing at Diagrid. “Getting an agent into production is not just about making it smarter. Teams also need to know what happens on the paths the demo never hit.”

Diagrid’s position is that these production properties belong in the runtime, not rebuilt inside each agent’s application code. Retries, checkpointing, resumability, idempotency and execution records are established distributed systems patterns. Rebuilding them for every agent can leave teams with different failure behavior and operating rules across the same company.

The production-readiness criteria are published alongside reference pages covering durable execution, failure recovery and long-running agent workflows.

About Diagrid

Diagrid provides infrastructure for AI agents and distributed applications, with a focus on durable execution, agent identity and production operations. The company is a contributor to the open-source Dapr project. For more information, visit diagrid.io.

Additional Resources

Agentic Reliability Engineering (ARE) Vol. I, Diagrid Research: https://www.diagrid.io/reports-and-ebooks/agentic-reliability-engineering

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SOURCE Diagrid