Lenny’s Podcast73 min
Asha Sharma · Aug 28, 2025
Key learnings- Treat AI products as living systems: build the loop of collecting usage signals, defining rewards, A/B testing, and fine-tuning…
- Invest in post-training and fine-tuning on your own data, not just off-the-shelf models; once models are large, adapting them to…
- Watch for a shift from GUIs toward composable, code-native interfaces, since text streams and composability connect better with…
Lenny’s Podcast100 min
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…
Lenny’s Podcast118 min
Dan Shipper · May 24, 2026
Key learnings- Keep using the newest models and agent tools for your real work, and experiment on your own time if your employer restricts…
- Expect most company AI to start as one shared agent that everyone can talk to, likely in Slack, rather than many personal agents…
- Design products so agents can be users too: make them easy to drive via CLI and browser-friendly, because the customer's own AI…
Lenny’s Podcast107 min
Varun Mohan · Apr 20, 2025
Key learnings- Expect your first big bet to be wrong; stay irrationally optimistic about the vision while ruthlessly testing and discarding the…
- Be willing to pivot fully and quickly when hypotheses break, as Varun's team did when model architectures converged on…
- Build the interface where AI-generated code gets reviewed, not just where it gets typed; Windsurf's tripled acceptance rate after…
Lenny’s Podcast71 min
Aparna Chennapragada · May 18, 2025
Key learnings- Prototype and build to see what you want before committing; prompt sets and prototypes can replace traditional PRDs as the…
- Time to first demo is shrinking while time to full deployment grows, so raise the bar for what earns scale and avoid chasing…
- Treat conversational interfaces as designed products: prompts, editable plans, progress display, and follow-up suggestions are…
Lenny’s Podcast115 min
Nikhyl Singhal · Apr 19, 2026
Key learnings- Expect the information-moving part of product work to be automated; judgment about what to build and whether changes are good…
- Build with AI tools to solve your own daily problems; you don't need to be an engineer, you need to know what good looks like.
- Aim to obsolete yourself: automate the parts of your job you dislike, as the best engineers do.
Lenny’s Podcast115 min
Max Schoenig
Key learnings- Prototyping in code forces you to understand the medium, so designers and PMs gain better judgment about what the real product…
- Agency, the willingness to treat your company and role as malleable, matters more than any single skill as AI tools make…
- Start by making things; tinkering builds the belief that the world around you can be changed, which Max sees as the root of…
Lenny’s Podcast121 min
Howie Liu · Aug 31, 2025
Key learnings- Leaders should stay close to the product details, since in AI-era products the interaction design and underlying behavior are the…
- Use AI products constantly, even multiple times an hour, and build small weekend projects to understand what models can do and…
- Ask whether you would build the same mission from scratch as an AI-native company; if your existing assets don't give a real…
Lenny’s Podcast110 min
Aishwarya Naresh Reganti + Kiriti Badam · Jan 11, 2026
Key learnings- AI products differ from traditional software mainly because user inputs and model outputs are both non-deterministic, so behavior…
- Each time you grant an AI system more decision-making autonomy, you give up some human control; autonomy should be earned through…
- Start with low-agency, high-human-control versions (e.g., suggestions to human agents) and log human corrections to build a…
Lenny’s Podcast68 min
Amjad Masad · Nov 21, 2024
Key learnings- Replit aims to remove the setup friction of building software by bundling the editor, runtime, packages, database, and deployment…
- Once AI removes the build bottleneck, the limiting factor shifts to how fast you can generate and articulate good ideas, so…
- Product managers can use an AI agent to build a v1 prototype, test it with real users, and then hand a validated concept to…
Lenny’s Podcast153 min
Peter Deng · Jun 22, 2025
Key learnings- Before scaling past product-market fit, invest in systems and architecture that let the team move sustainably faster, since…
- Build a growth team early; a growth leader forces instrumentation and rigorous questioning of what is actually happening in the…
- Balance growth-focused and craft-focused people deliberately, so the tension between metrics and product quality produces…
Lenny’s Podcast103 min
Gustav Söderström · May 21, 2023
Key learnings- Expect the internet's next shift from recommendation to generation to require rethinking products and business models, much as…
- Design UIs to match your model's real accuracy: if predictions are right only one in four or five times, show several options at…
- Treat generative AI as a distinct paradigm rather than more of the same machine learning, and ask what experience couldn't exist…
Lenny’s Podcast98 min
Guillermo Rauch · Apr 13, 2025
Key learnings- Treat taste as a skill you can build by increasing exposure hours: deliberately spend time watching people use your product and…
- Learn how systems work under the hood, since knowing the right technical tokens helps you steer AI models toward your intent more…
- Put product feedback loops inside the product itself, as Rauch suggests borrowing from Stripe's in-product feedback button…
Lenny’s Podcast91 min
Eoghan McCabe · Aug 21, 2025
Key learnings- When growth stalls in a late-stage SaaS business, cut costs hard and pick one clear strategic lane instead of trying to serve…
- Simplify and fairly price your product even at short-term revenue cost; McCabe gave away roughly $50M ARR to replace confusing…
- Price AI products on outcomes that align with customer value, like charging 99 cents per resolved ticket, rather than on the…
Lenny’s Podcast67 min
Inbal S · Dec 1, 2023
Key learnings- Engineers using AI tools need to shift from writing code to systems and architecture thinking, which lets junior developers spend…
- Don't adopt AI for its own sake; start from the customer problem and ask how AI can best solve it, rather than asking what to do…
- AI tools must fade into the background: any extra setup, asking, or waiting adds friction and developers will abandon the tool.
Lenny’s Podcast110 min
Shaun Clowes · Dec 29, 2024
Key learnings- Start every document from the customer, market, and competitor perspective rather than internal execution, since…
- Right-size qualitative research: interview roughly 7 to 14 people, because fewer gives too little signal and more stops yielding…
- Use LLMs to hunt for where your strategy doesn't fit customer feedback, not to confirm what you already believe, and to infer…
Lenny’s Podcast105 min
Tara Seshan · Aug 30, 2026
Key learnings- Be prolific and empirical rather than theoretical: get to something testable with users as fast as possible instead of writing…
- Sharpen the single most important hypothesis (the 'eigenquestion') and design fast tests to resolve it; that loop has always been…
- Build for where models will be in two to three months: building for current capabilities or for distant future capabilities are…
Lenny’s Podcast100 min
Jeanne Grosser · Nov 30, 2025
Key learnings- Treat go-to-market as an integrated lifecycle spanning marketing, sales, customer success, and support, mapping the jobs to be…
- Expect the buyer experience of being sold to to become a differentiator, so design the sales journey as a distinctive, valuable…
- Frame value around avoiding pain and reducing risk, since many buyers purchase to avoid downside rather than chase upside…
Lenny’s Podcast81 min
Brendan Foody · Sep 18, 2025
Key learnings- Treat evals as the product requirement document for a model: if you cannot measure what success looks like for a task, you cannot…
- Companies should build a systematic test of how AI automates their core value chain, since that measurement is the prerequisite…
- Evals also serve as sales collateral, showing customers and researchers concretely which real-world capabilities a model or…
Lenny’s Podcast105 min
Sherwin Wu V2 · Feb 12, 2026
Key learnings- Build for where models are going rather than where they are today, since products that are almost-working now can become…
- Treat fast-changing AI scaffolding skeptically: models often absorb tooling like vector stores and agent frameworks, so avoid…
- Don't blindly follow customer feature requests in AI; customers may anchor on local maxima while the underlying models are…
Lenny’s Podcast54 min
TiboSottiaux
Key learnings- Expect most actions on the internet to be taken by agents, so build products that can serve agent traffic at scale and handle the…
- Design for the capabilities you expect in roughly a year (about 10x better than today), not just what current models can do, to…
- Favor systems that learn from your goals and feedback over hand-tuned agent loops and workflows, which Tibo thinks will be…
Lenny’s Podcast142 min
Simon Willison · Apr 2, 2026
Key learnings- Coding agents crossed a reliability threshold around November 2025, so they now usually do what you ask, which changed how…
- Writing code is now cheap, so the bottlenecks move to ideation, prototyping, testing, and process; build several quick prototypes…
- Use test-driven development with agents: have them write tests, run them, and watch them fail first (Red/Green TDD) to keep…
Lenny’s Podcast93 min
Tamar Yehoshua · Sep 26, 2024
Key learnings- Excel in your current role before chasing the next one; advancement follows demonstrated impact, not just hitting goals or…
- Evaluate a potential employer's engineering partner before joining, since great ideas that can't be built lead nowhere.
- Don't assume a company must be well run to succeed; hyper-growth firms often run chaotically, but prioritize companies whose…
Lenny’s Podcast102 min
Roman Ugarte · Sep 8, 2026
Key learnings- Build a new product from scratch with a small, isolated team rather than retrofitting an existing surface, so each micro-decision…
- Onboard early users by hand and sit in on calls; fixing failures the same day compresses learning dramatically.
- Let users reveal patterns on their own before productizing them, then gently encourage the winning patterns without making them…