Drawer 05 · 298 notes · 90 people · 2014–2026

Building AI products

AI-native products, evals, agents, and how AI changes product work

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Answers from Building AI products notes, cited
Lenny’s Podcast76 min

Lessons on building product sense, navigating AI, optimizing the first mile, and making it through the messy middle

Scott Belsky · May 18, 2023
Key learnings
  • Build product sense by developing genuine empathy for the customer's problem before getting attached to a particular solution…
  • Optimize the first mile of the experience: users arrive lazy, selfish, and impatient, so onboarding, orientation, and defaults…
  • Re-examine onboarding for each new customer cohort, since later pragmatist users are less forgiving and need a reimagined…
SVPG · Marty CaganNov 6, 2025

Prototypes vs Products

Nov 6, 2025 · 4 min

Marty Cagan argues that a new wave of generative AI prototyping tools has been a good development for product discovery, but it has created confusion among product managers who fail to distinguish a prototype from a…

Lenny’s Newsletter♥ 328

How top PMs increase their leverage with AI

Jun 30, 2026 · 13 min
Subscriber post — summary only

Lenny Rachitsky, introducing a guest post by Colin on AI leverage for product managers, argues that PM work is shifting from coordination toward hands-on building with AI. The post lays out three ladders of leverage…

@hnshah · Hiten Shah on X♥ 35
We asked Claude what changed with Linear’s competitors. The first answer used an old source as if it were recent. It also stated a guess as fact. Then we gave the same model our competitive skills. It showed its limits up front. It explained how it ranked the changes and kept
Lenny’s Podcast111 min

I’ve run 75+ businesses. Here’s why you’re probably chasing the wrong idea.

Andrew Wilkinson · Jul 3, 2025
Key learnings
  • Choose a business in an area you're genuinely interested in, but look for the unglamorous niche where competition is low…
  • Pick a first business that delivers a quick, simple win, since early success builds the confidence and narrative needed to keep…
  • Look for a unique edge (skills, background, or access to audiences) and pivot toward the most profitable customer segment for…
@ttorres · Teresa Torres on X♥ 4
How do you build trustworthy AI diagnostic tools in one of medicine's most historically under-researched areas? In this episode of Just Now Possible, Teresa Torres talks with Tulsi Patel (Director of Product and Technology), Lorna Brightmore (Head of Data and AI), and Jack Pickard (Head of…
Lenny’s Podcast53 min

Product lessons from Waymo

Shweta Shriva · Apr 9, 2023
Key learnings
  • Build autonomous driving to feel natural and predictable, using human driving data while discarding bad driving behavior, so…
  • Expect the MVP bar to be far higher when safety is at stake, but still ship early and iterate on real-world deployment.
  • Track both commercial/operational metrics (trips, active users, cost) and system behavior metrics (safety versus human…
Lenny’s Podcast78 min

OpenAI’s Head of Design: This is the best time in history to be a designer

Ian Silber · Aug 16, 2026
Key learnings
  • Designers are still early in adapting to AI; nobody has a settled design process, so starting to experiment today already gives…
  • Design work has not sped up as much as engineering because the process still requires messy iteration, trying and discarding…
  • Use AI tools across the whole design process, including dropping early ideas into a coding or agent tool to prototype and think…
SVPG · Marty CaganFeb 4, 2026

Product Coaching and AI

Feb 4, 2026 · 9 min

Marty Cagan argues that the scarcest resource for product people is effective coaching, since most managers lack the time or skill to provide it, and that foundation AI models configured with good instructions and…

Lenny’s Podcast117 min

The power user’s guide to Codex: parallelizing workflows, planning techniques, advanced context engineering tips, automating code reviews, and more

Alexander Embiricos · Jan 12, 2026
Key learnings
  • Ship a product to a small group first, then learn empirically from usage rather than over-planning, especially in fast-moving AI…
  • Onboard users into agentic tools by first working alongside them in the local IDE or terminal, then gradually configure…
  • Give AI coding tools your hardest real tasks rather than trivial ones, and build trust by having the agent first understand the…
Lenny’s Podcast117 min

Elena Verna 4.0

Elena Verna 4.0 · Dec 18, 2025
Key learnings
  • Expect most of your classic growth playbook to transfer poorly in fast-moving AI categories; Elena estimates only 30-40% of her…
  • Build in public: pair regular product shipping with founder-led and employee social posts so the market sees constant change and…
  • Give the product away generously, including credits for hackathons and events, since removing the barrier to trying an AI product…
Lenny’s Newsletter♥ 739

How to use AI for your next job interview

Feb 24, 2026 · 22 min
Subscriber post — summary only

Lenny Rachitsky and researcher Noam Segal interviewed over 30 tech professionals about using AI in job hunts and found the strongest candidates built personal feedback loops with AI. The post packages those techniques…

Lenny’s Podcast131 min

How Devin replaces your junior engineers with infinite AI interns that never sleep

Scott Wu · Sep 8, 2025
Key learnings
  • Treat an AI agent like a junior engineer: scope it with well-defined tasks rather than open-ended problems, and start with small…
  • Run several agents asynchronously in parallel and only step in for the portions needing human judgment, such as scoping…
  • Invest up front in setup for the agent: connect repositories, teach it how to run lint and CI, and give it a virtual machine so…
Lenny’s Podcast131 min

Boris Cherny

Boris Cherny · Feb 19, 2026
Key learnings
  • Ship with minimal scaffolding and let the model choose tools and order of operations, rather than boxing it into rigid workflows…
  • Watch how people hack your product for purposes it wasn't designed for; that latent demand, like data scientists using a terminal…
  • Bet on the more general model over time instead of fine-tuning or tiny models, since scaffolding gains of 10-20% often vanish…