Training gave us powerful models, but inference is where the real production battle begins. Agentic workflows are burning money by the second, GPU economics are tightening each quarter, and a single unpredictable latency tail or silent kernel failure can turn a working system into an outage. Reliability thus is no longer just about uptime.This keynote is a call to SREs, GPU engineers, and LLMOps practitioners. I’ll share some of the hard lessons, emerging patterns, and new rules shaping the next decade of reliable AI systems
Abi Aryan is the founder of Abide AI, educator and author of the O'Reilly book LLMOps and an upcoming book in GPU Engineering. With over 10 years of experience productionizing AI/ML systems and prior research experience at UCLA under Dr. Judea Pearl, she has been focusing on making AI systems reliable, observable, and sustainable at scale.
