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Eugene Yan shares insights on LLM system building and AI engineering trends

Eugene Yan presented key learnings from building with Large Language Models (LLMs) at the AI Engineer World's Fair 2024. The keynote, co-authored with others, focused on practical aspects of LLM system development, including evaluations, Retrieval-Augmented Generation, and guardrails. Yan also discussed challenges in consistently evaluating LLMs, citing concerns raised by researchers at OpenAI, Anthropic, and others regarding benchmark reliability and task relevance. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

RANK_REASON The content is a presentation and reflection on practical LLM engineering, drawing from prior writings and community feedback, rather than a new model release or significant industry event.

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COVERAGE [2]

  1. Eugene Yan TIER_1 ·

    AI Engineer 2024 Keynote - What We Learned from a Year of LLMs

    Special double-feature closing keynote from the 6 authors of the hit O'Reilly article on Applied LLMs.

  2. Eugene Yan TIER_1 ·

    AI Engineer 2023 Keynote - Building Blocks for LLM Systems

    Evals, retrieval-augmented generation, guardrails, and collecting feedback; all that good stuff.