It’s Never Different This Time: LLM Reliability Without the Hype with Julien Simon
Description
In this episode, Julien Simon, longtime voice in the open-source ML world, reminds us that even in the era of GenAI, reliability fundamentals haven’t changed.
Julien breaks down why calling “the same model” from different providers can produce wildly different results, how deployment choices introduce hidden variability, and why reliability teams need to think of LLM systems as distributed systems.
He explains the growing gap between experimentation and production, the operational pitfalls of fast-moving open-source tooling, and why enterprises increasingly turn to open-weight models for performance, cost control, and deeper domain alignment.
From the fluidity of today’s AI stacks to the emerging discipline of GenAI ops, this episode offers a grounded, hype-free look at what it really takes to run LLMs reliably at scale.
United States
