Resilient AI: How to Protect, Verify, and Recover Your Agents Before They Fail You

A model gets deprecated and there's nothing to roll back to. A prompt gets a one line edit to fix an edge case and the agent's behavior changes with no review, because a prompt edit doesn't look like a change, it looks like a configuration update. A new connector gets added and nobody signed off on what data or tools that agent can now reach. None of this trips an alarm. Performance can degrade while the dashboard still shows green, and the bill that tells you token costs moved usually arrives weeks after the decision that caused it.

Traditional RTO plans assume a disruption event: something breaks at a specific moment, you roll back, you move on. AI doesn't give you that moment, and you're often not even the one making the change. The provider deprecates the model on their schedule, not yours.

This session breaks down the three areas where that gap actually lives, operational, technical, and financial, and what building resilience into each one looks like in practice.

Watch on demand for the full breakdown of how to build promotion gates, a control plane, and cost caps into your AI systems before the next change forces your hand.