All you need is taste And evals

Honestly they really could have just taken midtown while they’re at it

Sometimes I just copy paste an architecture diagram or PRD into o3 and ask: “So what’s your hot take?”

There clearly is a $500m consulting business TODAY in finishing folks' Replit and Loveable apps Maybe bigger

This was such a great episode! I love it how YouTube surfaces a gem like this now and then. Loved listening to both Aman Khan and Lenny Rachitsky

accurate

It was pretty amazing to have a small role on this one and see the team execute at such a detailed level - shoutout to Andy Dai (researcher), Julia Gomes, Priyan Jindal Jason Lopatecki and Aparna Dhinakaran for rigorously testing an early idea that made sense intuitively and

This has been such a reoccurring theme in discussions lately - we know the PM role has changed, but how do we stay ahead of all the advancements happening in AI?

So many people out there throw around buzzwords saying they will completely change your job and the AI space. Personally, I think to cut through the hype, it's more important to learn how these new systems and products work - and see what you can learn from this process of

Everyone’s Using Claude Code—But How Is It Actually Planning? Claude Code is everywhere right now. It’s fast, competent, and incredibly good at multi-step tasks out of the box. Kicking off a short series with agent-level breakdowns on how to evaluate Claude Code using

1️⃣ AI PM Foundations Marily Nika: How to become an AI PM - youtube.com/watch?v=GQd54g… Sam Kawsarani: 15+ Years PM in Era of AI - tinyurl.com/2txs9mab Aman Khan: Prototyping → Observability → Evals - youtube.com/watch?v=Ej4pBD…

Superintelligent AI girlfriend confirmed

Prebuilt evals don’t always cut it - at some point, you’ll need to build your own LLM evaluator from the ground up, tailored to your exact use case. This can be tricky if you aren't sure where to start. My latest tutorial covers this! We being by building a benchmark dataset

Quick GPT-5 takes: - It's better

Pretty convinced there is still pretty sizable arb in document parsing and RAG for enterprise because the top search results are (1) sponsored (2) bounties and (3) stale reddit threads

New research on prompt learning + a hands on notebook using our open source product arize-phoenix!

shyamal When I hear evals, I remember Aman Khan!

95% seems really high and kind of a made up number, just saying.