Hamel Husain Summarizes 13 AI Engineering Sessions: Key Takeaways on Retrieval, Post-training, and Evals
HamelHusain · x · 2026-08-13
Hamel Husain has published a blog post summarizing 13 AI engineering sessions he co-hosted with Reya, covering topics like retrieval, post-training, inference, and evals. The notes are organized by theme with links to source materials. Key insights include: optimizing retrieval and context is the lowest-hanging fruit; then improve systems and harness; only consider post-training your own model after exhausting other approaches. The notes cover evals (e.g., data-agent benchmarks, model cascades for cost reduction, automated error analysis, production evals case study) and context (e.g., multi-vector retrieval, improving search agents).
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