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Humans of Reliability
Rootly
20 episodes
3 days ago
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. Conor dives into the shift from traditional test-driven development to evaluation-driven development, where metrics like context adherence, completeness, and ac...
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Technology
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All content for Humans of Reliability is the property of Rootly and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
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. Conor dives into the shift from traditional test-driven development to evaluation-driven development, where metrics like context adherence, completeness, and ac...
Show more...
Technology
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How AI broke serverless and what to do about it with Vercel’s Mariano Fernández Cocirio
Humans of Reliability
13 minutes
8 months ago
How AI broke serverless and what to do about it with Vercel’s Mariano Fernández Cocirio
Mariano, Staff Product Manager at Vercel, explains why serverless architectures are hitting unexpected limits—they’re too fast. The industry has spent millions optimizing serverless for speed, but AI workloads are changing the game. In the AI realm, slower execution often leads to better results. The challenge? Paying for all that idle compute time while waiting for AI responses. Mariano explains how Vercel Fluid is introducing a new execution model that blends the best of serverl...
Humans of Reliability
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. Conor dives into the shift from traditional test-driven development to evaluation-driven development, where metrics like context adherence, completeness, and ac...