2026-09-22 –, Main Stage All times in US/Mountain
I've built banking pipelines for 10 years. My company just told me we're deploying AI agents. I started researching what changes — and found 5 things my pipeline has no answer for:
- "Build passed" — but the model wasn't tested against this week's data
- "Health check passed" — but "up" doesn't mean "correct" for AI
- "Deployment successful" — but which version: the code, the model, or the context?
- "Cost normal" — but token costs don't appear in your cloud bill like compute does
- "No alerts" — but the AI failed silently because nobody defined what "wrong" looks like
5 failure modes that your current pipeline has no answer for. 5 slides each. 5 minutes. Drawn from production failures documented in public post-mortems and infrastructure gap analysis from 10 years of banking deployments.
A fast, opinionated 5-minute format: one failure mode per minute, drawn from documented production post-mortems and infrastructure gap analysis. The structure maps cleanly to the Ignite format — 4 slides per failure mode (the assumption, why it breaks for AI, what it costs, and the right question to ask instead). No tools, no demos — just the 5 mental model shifts every DevOps engineer needs before their first AI deployment. Designed to spark open space conversations rather than close them.
Saideep Navakoti is an Architect with 11 years of experience building and operating cloud-native banking infrastructure on Kubernetes. His career has been entirely in financial services — designing CI/CD pipelines, deployment automation, and observability systems for platforms handling critical financial transactions. SaiDeep holds AWS Solutions Architect and CKA certifications, and is co-author of published research on context engineering for AI agents (arXiv:2603.14057). Currently focused on the intersection of platform engineering and AI/ML workloads in regulated banking environments. Based in Atlanta, GA.