Operations | Monitoring | ITSM | DevOps | Cloud

Only 50% of companies monitor their ML systems. Building observability for AI is not simple: it goes beyond 200 OK pings. In this episode, Sylvain Kalache sits down with Conor Brondsdon (Galileo) to unpack why observability, monitoring, and human feedback are the missing links to make large language model (LLM) reliable in production.

Is “good code” still the right measure of engineering success in an AI-driven world? In this episode of *Humans of Reliability*, Rob Zuber, CircleCI CTO, joins Sylvain to explore how coding assistants are reshaping developer workflows and changing what teams value. Rob shares what he’s seeing across CircleCI’s customer base: a clear boost in throughput, new bottlenecks shifting from code creation to code review, and the rise of “vibe coding,” where engineers trust AI-generated code they may not fully understand.

Read our post: https://rootly.com/blog/the-art-of-incident-management-part-i

What does it really take to move from firefighting incidents to building reliability at scale? In this episode of Humans of Reliability, Shery Brauner (Razor, ex-Zalando) shares her unique journey from frontend and backend engineering to leading site reliability practices. She explains why protecting the user journey is the key to effective incident management, how SLOs cut through noisy alerts, and why observability must come first.