Webinar
How do you respond when your AI tooling and models fail?
October 14 at 12 PM ET / 5 PM BST
Description
AI is now part of how most engineering teams write, review, ship and run software. That makes the models and tools behind it a dependency like any other, except most teams haven't treated them like one. When a model provider goes down, gets rate-limited or changes behaviour, the failure doesn't look like a normal outage. It shows up as internal incidents nobody has a runbook for.
Michael Tweed from Skyscanner joins the engineers building AI at incident.io for an honest conversation about what happens when AI tooling becomes a single point of failure, and what both teams are doing about it.
In this live session, we'll be talking about:
- How AI tooling and models quietly became critical-path infrastructure, and where the single points of failure hide.
- What an AI-dependency incident actually looks like, and why it is different from a normal outage.
- How Skyscanner is approaching AI tooling resiliency today.
- What we've learned at incident.io as a company that both depends on model providers and builds AI that customers depend on.
- Practical patterns: fallbacks, degradation, detection, ownership and runbooks for AI dependencies.
- An open Q&A.
