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SE Radio 610: Phillip Carter on Observability for Large Language Models

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Manage episode 410491133 series 215
Content provided by SE-Radio Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SE-Radio Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Phillip Carter, Principal Product Manager at Honeycomb and open source software developer, talks with host Giovanni Asproni about observability for large language models (LLMs). The episode explores similarities and differences for observability with LLMs versus more conventional systems. Key topics include: how observability helps in testing parts of LLMs that aren't amenable to automated unit or integration testing; using observability to develop and refine the functionality provided by the LLM (observability-driven development); using observability to debug LLMs; and the importance of incremental development and delivery for LLMs and how observability facilitates both. Phillip also offers suggestions on how to get started with implementing observability for LLMs, as well as an overview of some of the technology's current limitations. This episode is sponsored by WorkOS.

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986 episodes

Artwork
iconShare
 
Manage episode 410491133 series 215
Content provided by SE-Radio Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SE-Radio Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Phillip Carter, Principal Product Manager at Honeycomb and open source software developer, talks with host Giovanni Asproni about observability for large language models (LLMs). The episode explores similarities and differences for observability with LLMs versus more conventional systems. Key topics include: how observability helps in testing parts of LLMs that aren't amenable to automated unit or integration testing; using observability to develop and refine the functionality provided by the LLM (observability-driven development); using observability to debug LLMs; and the importance of incremental development and delivery for LLMs and how observability facilitates both. Phillip also offers suggestions on how to get started with implementing observability for LLMs, as well as an overview of some of the technology's current limitations. This episode is sponsored by WorkOS.

  continue reading

986 episodes

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