Product Talk · Teresa TorresJun 30, 2026
Jun 30, 2026
“Listen to this episode on: Spotify | Apple Podcasts Think you don't have big enough problems for AI to help with? Think again. In this episode, Petra and Teresa tackle one of the most common blockers people face when starting out with AI: not knowing where to begin. It's”
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…
@ttorres · Teresa Torres on X♥ 12
What does it take to build an AI app builder specifically for product managers—not engineers—inside an already crowded market? In this episode of Just Now Possible, Teresa Torres talks with Brian De Haaff (CEO and Co-Founder), Chris Waters (CTO and Co-Founder), and Sarah Moisan-Thomas (Senior…
Product Talk · Teresa TorresSep 3, 2025
Sep 3, 2025 · 33 min
Teresa Torres describes building Product Talk's Interview Coach, an AI tool that gives students feedback on their customer interviews, and how she designed evals to measure its quality. She explains the core idea of…
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…
Product Talk · Teresa TorresSep 23, 2025
Sep 23, 2025
Teresa Torres and Petra Wille explore AI evals: what they mean, why they matter beyond quality assurance, and how teams can build them. Drawing on Teresa's experience building the Interview Coach tool, the conversation…
@lennysan · Lenny Rachitsky on X♥ 1,133
Linear CEO @karrisaarinen: "I took a break this summer from paying attention to AI. I thought that when I came back, I'd feel left behind. But when I came back, I realized that nothing has really changed. There's new models, there's new techniques, there's new agents. But in the
Product Talk · Teresa TorresNov 19, 2025
Nov 19, 2025 · 25 min
Teresa Torres synthesizes conversations with nine product teams building AI features in production, highlighting recurring patterns across their work. She argues that small cross-functional teams, domain expertise, and…
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 NewsletterAug 19, 2025
Aug 19, 2025 · 20 min
Subscriber post — summary onlyAishwarya Reganti and Kiriti Badam introduce the Continuous Calibration/Continuous Development (CC/CD) framework for building AI products. They argue AI systems are non-deterministic and require negotiating a tradeoff…
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 NewsletterSep 9, 2025
Sep 9, 2025 · 20 min
Subscriber post — summary onlyHamel Husain and Shreya Shankar outline a practical playbook for building AI evaluation systems that improve a product rather than just producing dashboards. The core argument is to start with error analysis by a domain…
Product Talk · Teresa TorresOct 2, 2025
Oct 2, 2025
Teresa Torres and Hamel Husain discuss how to evaluate and debug AI products with a scientist's mindset. Hamel draws on his machine learning background at Airbnb and GitHub, and his consulting work with startups like…
Product Talk · Teresa TorresDec 4, 2025
Dec 4, 2025
This podcast episode follows Perk, a company that eliminates 'shadow work' like travel booking, as its team built a voice AI agent that calls hotels to verify virtual credit card payments. The project grew from a…
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…
Product Talk · Teresa TorresAug 20, 2025
Aug 20, 2025 · 26 min
Teresa Torres recounts a 90-day, self-directed journey building her first AI product, an Interview Coach that gives feedback on customer interviews, which she built while recovering from a broken ankle. She argues that…
Lenny’s Newsletter♥ 261
Aug 20, 2024 · 7 min
Subscriber post — summary onlyLenny Rachitsky argues, in response to anxiety over AI replacing product managers, that PMs are the best-positioned tech role to thrive in an AI-driven world. He contends that AI excels at execution while PMs' soft…
SVPG · Marty CaganApr 16, 2024
Apr 16, 2024 · 9 min
Marty Cagan and Marily Nika argue that AI product management means building AI-powered experience products, not AI infrastructure, and that most PMs will soon need these skills just as mobile PM became essential. They…
SVPG · Marty CaganJun 9, 2025
Jun 9, 2025 · 6 min
Marty Cagan argues that the products most PMs will build in the coming years are "intelligent products" that blend deterministic and probabilistic behavior. He traces the history of AI from 1980s expert systems, whose…
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…
Product Talk · Teresa TorresSep 2, 2026
Sep 2, 2026 · 5 min
Teresa Torres introduces a practical test harness for running AI product evals. Manually running every input through a prompt, saving outputs, scoring them against evals, and repeating for each prompt variant is…
@ttorres · Teresa Torres on X♥ 9
🎙️Delivery Isn’t Free Everyone's saying it: "Now that AI makes delivery free…" But is it? In this episode of All Things Product, Petra Wille and Teresa Torres pull apart one of the most repeated claims in product right now. They dig into why building a single feature has gotten dramatically…
SVPG · Marty CaganJun 15, 2025
Jun 15, 2025 · 3 min
Marty Cagan argues that the current resistance to AI products mirrors the denial that greeted the Internet in the mid-1990s. Back then, many organizations insisted their old Waterfall funding, building, and shipping…