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Lenny’s Podcast109 min

Slack founder: Mental models for building products people love ft. Stewart Butterfield

Stewart Butterfield · Nov 20, 2025
Key learnings
  • Plot features on a utility curve to see whether extra investment is still on the steep part of the value gain or has reached…
  • Judge a product by whether users understand what it does; in many places the real challenge is comprehension, not friction, so…
  • Cultivate taste deliberately: taste can be trained, and leaning into craft can become a competitive advantage that less-attentive…
HEY World · Jason FriedNov 18, 2025

Quality: The Concept2 RowErg

Nov 18, 2025

Jason Fried, co-founder of Basecamp, praises the Concept2 RowErg indoor rowing machine as a benchmark of product quality. He describes its simple, durable construction, low maintenance, easy assembly and compact…

Lenny’s Podcast78 min

The Godmother of AI on jobs, robots & why world models are next

Dr. Fei Fei Li · Nov 16, 2025
Key learnings
  • Large labeled datasets were the missing ingredient that unlocked modern AI; big data, neural networks, and GPUs together formed…
  • Pursue a north-star problem and commit to it for years, as ImageNet's object recognition focus did for her lab.
  • Be willing to take intellectual and career risks, such as leaving tenure track or joining new ventures, when the mission and…
Lenny’s Podcast164 min

“Dumbest idea I’ve heard” to $100M ARR: Inside the rise of Gamma

Grant Lee · Nov 13, 2025
Key learnings
  • Treat product-market fit as a real word-of-mouth engine: if over half of new signups come from organic sharing, the core growth…
  • Make the first 30 seconds of the product magical, focusing on one clear 'egg' of value rather than many features, so new users…
  • Practice founder-led marketing: write provocative but useful posts, share learnings regularly, and build credibility by giving…
Lenny’s Newsletter♥ 389

Ecosystem is the next big growth channel

Nov 11, 2025 · 15 min
Subscriber post — summary only

The post argues that as AI makes building and reaching customers easier for everyone, traditional B2B channels like search, outbound, events and lifecycle email are getting noisier and less effective. It makes the case…

Lenny’s Podcast97 min

"Sell the alpha, not the feature": The enterprise sales playbook for $1M to $10M ARR

Jen Abel · Nov 9, 2025
Key learnings
  • Founder-led sales is a competitive advantage because founders are the visionary and can spot budding insights that salespeople…
  • Write cold outreach that leads with relevance, a counterintuitive insight, and the problem rather than the solution, kept to…
  • Before buying tools, manually find and write thoughtful notes to about 30 prospects; use the response pattern to refine messaging…
Medium · Hiten ShahNov 7, 2025

Why Tech Still Doesn’t Understand Marketing

Nov 7, 2025 · 5 min

Hiten Shah argues that tech has long misunderstood marketing, treating it as decoration or a growth hack when it is really the translation between what a product does and what it means to customers. He notes that the…

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…

The Looking Glass · Julie Zhuo♥ 126

The Lost Art of Crying

Nov 6, 2025

Julie Zhuo's personal essay traces how she came to see herself as an "ice queen": someone who learned to suppress emotion and present a composed, controlled surface. The piece frames emotional guardedness as a…

@lissijean · Melissa Perri on X♥ 1
This is what separates teams that accelerate with AI from those that get stuck. You don't find perfect data lying around. You create it using the deep product intuition you already have. /end Check out the whole episode with @vlaurenlee here:
@lissijean · Melissa Perri on X♥ 2
They're taking everything they know about commerce, customer behavior, and product strategy, and using that knowledge to systematically generate the training data they need. It transforms the data bottleneck from a passive waiting game into an active engineering challenge. /3
@lissijean · Melissa Perri on X
This week on the podcast, @vlaurenlee from @Shopify shared how her team is using AI to solve AI problems, instead of waiting years for interaction data. "You're basically imparting all of your product intuition into an LLM to then shape yet another LLM." /2
@lissijean · Melissa Perri on X♥ 8
Most teams make the mistake of waiting for data to magically appear before building their AI product. They get stuck in the classic chicken-and-egg problem: you need data to build good AI, but you need users to generate that data. So they wait. And wait. And wait some more. /1
Medium · Hiten ShahNov 3, 2025

The History of Slop

Nov 3, 2025 · 12 min

Hiten Shah traces the idea of 'slop' from 19th-century pig feed and swill milk through naval slop chests, industrial refineries, institutional cafeteria food and today's algorithmic content feeds. His core argument is…

Lenny’s Podcast100 min

How Block is becoming the most AI-native enterprise in the world

Dhanji R. Prasanna · Oct 26, 2025
Key learnings
  • Track AI impact with self-reported time savings plus validation metrics such as PR throughput and feature delivery, which Block…
  • Expect the current AI value baseline to keep rising; adopt tools continuously and re-evaluate where they add value as…
  • Non-technical staff building their own small internal tools with agents can compress weeks of waiting on engineering queues into…
Medium · Hiten ShahOct 25, 2025

The Toy That Becomes an Operating System

Oct 25, 2025 · 3 min

Hiten Shah argues that transformative technologies often look like toys at first, and that Wabi's playful mini-apps are an early stage of a new personal operating system. He compares this to the early personal computer…

Lenny’s Podcast102 min

Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix)

Chip Huyen · Oct 23, 2025
Key learnings
  • Focus on what actually improves AI apps, such as talking to users, improving data, writing better prompts, and optimizing…
  • Be cautious about committing to newly released technologies that have not been widely tested, since switching away from them…
  • Fine-tuning and post-training can shape model behavior a lot, and many teams now focus effort there because base pre-training…