Working notes from product people

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01 — TopicsFourteen drawers, sorted.

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Open drawer · 05

Building AI products

298 notes · 90 people · 2014–2026
Lenny’s Newsletter · Free post♥ 724

Build your personal AI copilot

Jul 22, 2025 · 27 min

“One of my favorite collaborators, Tal Raviv, is back with another incredible piece that will change how many of you operate at work. If you’re looking for the promised AI productivity gains everyone’s talking about, start here. For more from Tal, check out his 63 free video tutorials on using AI agents at work, his other guest post, “PM is an unfair role. So work unfairly”, and his episode on Lenny’s Podcast. You can also book Tal for…”

Lenny’s Podcast128 min

Inside ChatGPT: The fastest-growing product in history

Nick Turley · Aug 9, 2025
Key learnings
  • Ship early to learn what people actually want; with AI, the valuable behaviors are emergent, so you won't know what to polish…
  • Treat the model itself as a product: iterate on it using real user use cases, personality/vibe checks, and new capabilities like…
  • Set the team's pace deliberately by asking whether work is 'maximally accelerated', separating fast product iteration from…
Lenny’s Newsletter♥ 578

How to build AI product sense

Feb 3, 2026 · 34 min
Subscriber post — summary only

Tal and Aman argue that the fastest way to build intuition for AI products is to use coding agents like Cursor for non-technical product work rather than consumer chat tools. The post walks readers through setup, model…

@ttorres · Teresa Torres on X♥ 97
"The only way to know if our AI products and workflows are any good is with evals." 💡 If you're using AI to write PRDs, analyze customer feedback, or build customer-facing AI products, you need to understand evals. This guide breaks down what evals actually are and why product teams should be…
Lenny’s Podcast116 min

OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more

Kevin Weil · Apr 10, 2025
Key learnings
  • Build products at the edge of current model capabilities, since models improve every few months and a barely-working product can…
  • Treat evals as unit tests for models: define hero use cases, write evals for them, and hill-climb on those evals to know whether…
  • Expect AI behavior to be fuzzy: a model right 60%, 95%, or 99.5% of the time implies very different product designs, so study…
Lenny’s Podcast93 min

Anthropic’s CPO on what comes next

Mike Krieger · Jun 5, 2025
Key learnings
  • Use AI as an independent strategy critic: ask it to be brutal or to challenge your thinking, since default prompts tend to…
  • As AI writes most code, bottlenecks shift upstream to deciding what to build and aligning people, and downstream to merge queues…
  • Give teams a minimum viable strategy so people feel empowered to build and explore at the edge of model capabilities without…
@lennysan · Lenny Rachitsky on X♥ 968
My conversation with Head of ChatGPT and Codex, @thsottiaux We discuss: 🔸 Why the model picker is likely going away 🔸 Why loops and graphs are a passing phase 🔸 Why most actions on the internet will soon be taken by agents 🔸 OpenAI’s approach to AI safety Listen now 👇

02 — FrameworksModels, annotated.

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03 — PeopleWho wrote the notes.

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04 — QuestionsAnswered from the notes.

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Where notes come from

NewsletterLenny’s Newsletter106 free posts, with a longer excerpt.
Subscriber postsSummary only229 paid posts: our summary, at most two short quotes, and a link.
PodcastLenny’s Podcast322 episodes, each with 5–8 key learnings and timestamps.
EssaysSVPG · The Beautiful Mess499 essays from Marty Cagan and John Cutler.
Substack & blogsShreyas · Julie · Jason · Hiten577 essays and posts from independent writers.
XPosts on product58 posts, filtered for product relevance.