Lenny’s Podcast131 min
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 · 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…
@ttorres · Teresa Torres on X♥ 5
What happens when you hand your opportunity solution tree to an AI? Vistaly rebuilt its entire product to find out—and the agents were the easy part. In this episode of Just Now Possible, Teresa Torres talks with Matt O'Connell (Co-Founder and CEO), CP Dehli (Co-Founder), and Steve Klein…
Lenny’s Podcast108 min
Claire Vo · Apr 7, 2024
Key learnings- Know what you want from your career and your next role, and ask for it clearly, framed around how the role solves a real problem…
- Time promotion conversations to the company's talent calendar and pitch concrete org-level gaps you can fill, such as an org…
- Lean into your zone of genius by auditing your calendar, grouping activities by energy, and deliberately protecting time for the…
Product Talk · Teresa TorresMay 14, 2026
May 14, 2026 · 3 min
“Listen to this episode on: Spotify | Apple Podcasts Only 10% of the plastic we manufacture gets recycled. We've been trying to solve this for a hundred years using the same mechanical and chemical tools that created the problem. What if biology—specifically, engineered enzymes—is the missing piece? In”
The Beautiful Mess · John Cutler♥ 55
Aug 17, 2026
John Cutler examines the sudden enthusiasm for measuring "return on tokens" as AI usage grows inside companies. He argues that vendors and executives eager for clean numbers are reaching for yet another proxy, much like…
@lennysan · Lenny Rachitsky on X♥ 93
Linear CEO @karrisaarinen: "Making products produces two things: the product, and the learning. The effort you put into building and designing things teaches you something about what the problem is, what the customers want. We're in this time now that there's this danger of
Lenny’s Podcast104 min
Brian Balfour · Oct 5, 2023
Key learnings- Building a great product is necessary but not sufficient; durable winners separate themselves by building strong distribution…
- New distribution platforms tend to follow a cycle: competitive consensus, identifying a moat, opening a third-party ecosystem…
- Being early to a new platform matters because late adopters face shrinking windows, since platform cycles appear to be getting…
Lenny’s Newsletter · Free post♥ 306
Apr 30, 2024 · 15 min
Lenny Rachitsky interviews Johnny Ho, co-founder and head of product at Perplexity, about how a fast-growing AI search company builds product with a very small team. Perplexity uses AI to answer its own operational…
Product Talk · Teresa TorresMar 11, 2026
Mar 11, 2026 · 5 min
Teresa Torres introduces a new series, Conversations with Claude, showing how she uses Claude Code for real work. Her first example is a content audit of Product Talk, which she delegated to Claude with a task file and…
The Looking Glass · Julie Zhuo♥ 131
Apr 21, 2026
Julie Zhuo's short essay, titled "I am an idiot," reflects on intellectual humility in an era when AI systems can seem to know more than we do. The piece is framed as personal notes rather than a formal argument, using…
Product Talk · Teresa TorresApr 21, 2026
Apr 21, 2026
Teresa Torres and Petra Wille argue that confident predictions about AI-driven change are often wrong, and that betting everything on one forecast is risky. Humans are poor at forecasting, and early adopters' experience…
Lenny’s Podcast85 min
Garrett Lord · Aug 24, 2025
Key learnings- Post-training, not pre-training, now drives most model gains, so high-quality expert data targeting specific capability gaps is…
- The labeling market has shifted from cheap generalist labor to domain experts, so the right supply is credentialed specialists…
- Access to a trusted audience is the real moat in human data; owning an audience removes customer acquisition costs compared with…
Lenny’s Podcast115 min
Eric Simons · Mar 13, 2025
Key learnings- Eric Simons says deep technology bets can take years to find their market; his team stayed alive by bootstrapping and keeping…
- Simons advises treating spending as a default no until you see real customer pull, and buying software with the goal of cutting…
- Simons notes that when a launch unexpectedly takes off, pricing and infrastructure often break first; Bolt rolled out upgrade…
Product Talk · Teresa TorresJun 3, 2026
Jun 3, 2026 · 13 min
Teresa Torres recounts how a worm known as Mini Shai-Hulud, which spread through popular JavaScript packages in May, pushed her to rethink the security of her AI-assisted building. She explains that most malware follows…
Lenny’s Podcast108 min
Ben Horowitz · Sep 11, 2025
Key learnings- Hesitation is usually the most destructive leadership mistake; when both options look bad, make an explicit decision rather than…
- Leaders add real value only when they make decisions most people disagree with; if everyone agrees, the leader added nothing.
- Success is built from a long chain of small, hard decisions, and each good choice sets up the next, so keep making the next one.
Lenny’s Podcast91 min
Adriel Frederick · Oct 20, 2022
Key learnings- Make new R&D or incubation teams feel core to the company mission and share their wins, so the rest of the organization doesn't…
- For algorithm-heavy products, decide explicitly what the algorithm owns versus what people own, and design interfaces that let…
- Treat operational control as a first-order product requirement when a marketplace needs day-to-day human adjustments like weather…
SVPG · Marty CaganApr 17, 2025
Apr 17, 2025 · 3 min
Marty Cagan argues that product teams often conflate empowerment and autonomy, and that the two should be considered separately. Empowerment means a team can choose how to solve a problem, while autonomy means it can…
SVPG · Marty CaganJun 19, 2021
Jun 19, 2021 · 34 min
Marty Cagan's first published article, from a 1986 HP Journal issue, is a technical overview of Hewlett-Packard's internal AI Workstation research program and its first product, a Common Lisp development environment. It…
The Beautiful Mess · John Cutler♥ 30
Jul 3, 2026
John Cutler reflects on the growing role of AI in product and team work, framing it as something that can play several supporting roles: a scribe that captures notes, a thought partner that challenges ideas, a tool that…
SVPG · Marty CaganMay 5, 2025
May 5, 2025 · 5 min
Marty Cagan introduces a re-recorded audio edition of INSPIRED and reflects on how the book has held up since its 2007 and 2017 editions. He argues its focus on underlying principles rather than current process is why…
Lenny’s Newsletter♥ 184
Jul 30, 2024 · 15 min
Subscriber post — summary onlyLenny Rachitsky and Palle Broe analyze how 44 application-layer tech incumbents monetize AI features, comparing direct and indirect strategies. They argue direct monetization (add-ons, standalone products, or plan…
Lenny’s Newsletter♥ 338
Aug 5, 2025 · 9 min
Subscriber post — summary onlyLenny Rachitsky and Peter Yang distill tactics from AI-forward companies like Shopify, Ramp, Zapier, Duolingo, Intercom, and Whoop on driving employee AI adoption. The core argument is that the main barrier is…
HEY World · Jason FriedMar 20, 2026
Mar 20, 2026
Jason Fried argues against the idea that AI will spark a bespoke software revolution where everyone builds their own custom tools. He notes that custom software already exists and is usually bloated because clients pay…