One step further: make the PRD and the evals the same artifact. Write down what good means. That one thing builds the feature and grades it. Run your PRD. venturebeat.com/security/eva...

AI evals: why they're the new PRD, per Expedia | VentureBeat

Expedia's AI chief Xavi Amatriain explains why AI evals are replacing traditional specs for agent governance, using toll gates calibrated to risk.

venturebeat.com

Almost everything we've learned building AI features starts in one place: deciding what "good" means, in writing, before you build. We'll post notes on how to actually do that. Starting simple, working up.

👋 is there an eval for ai-driven kernel *maintenance*? not generation, but migration. like, cuda→hip, gfx942→gfx950, rocm n→n+1, etc. migration has a built-in verifier (the old kernel is the spec), so it should be way more benchmarkable than greenfield kernel generation who's working on this

First AI feature? Stuck between demo and production? Running live agents and hoping for the best? We're Biene Club. We build your AI, prove it works, and help you adapt. How we do it: biene.club/approach

Approach — Biene Club

How we build and release AI systems: turn intent into measurable artifacts, align the whole team on one shared truth, and keep quality honest from prototype to production.

biene.club

10 short videos about LLM infrastructure to help you appreciate Pages 12-18 of the DeepSeek-v3 paper (arxiv.org/abs/2412.19437) www.youtube.com/watch?v=76gu...

Flash LLMs: Pipeline Parallel

YouTube video by Sasha Rush 🤗

youtube.com

Wrote an intro to evals for long-context Q&A systems: • How it differs from basic Q&A • What dimensions & metrics to eval on • How to build llm-evaluators • How to build eval datasets • Benchmarks: narratives, technical docs, multi-docs eugeneyan.com/writing/qa-e...

Evaluating Long-Context Question & Answer Systems

Evaluation metrics, how to build eval datasets, eval methodology, and a review of several benchmarks.

eugeneyan.com

You built an AI feature. How do you know it's good enough to give to your users? We developed a method where your intent becomes a testable definition of "good," and built Beeline to show you how accessible this method is. Read it, then steal it 🐝 www.biene.club/blog/2026-07...

Beeline: from intent to proof — Biene Club

You can't check every output by hand, and a machine can't check it for you until you write down what "good" means. Beeline turns one sentence into a feature, the evals that judge it, and the proof it ...

biene.club