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I write Lenny's Newsletter (the #1 business newsletter on Substack), and host Lenny's Podcast (top ten tech podcast globally). Previously, I spent seven years at Airbnb leading supply growth, conversion, trip quality, and community, and before Airbnb, I was an engineer and a founder (exited to Airbnb).
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Setting Goals - Issue 23
Setting Goals - Issue 23
🔒 This is a free preview of a subscriber-only post 🔒 Q: How do you think about setting goals for your team (and…
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408K followers
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Lenny Rachitsky shared thisClaire Vo: "We can now ship all our bad ideas. Congratulations!" Watch the full talk here: https://lnkd.in/gBsKP-de
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Lenny Rachitsky shared thisGeoff Charles (CPO of RampRamp): I see 3 paths for product managers long-term: 1. The technical PM 2. The tastemaker PM 3. The GM Clip from his full talk below: https://lnkd.in/geUrdABB
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Lenny Rachitsky shared thisMarty Cagan: "Fundamentally good product work is about thinking. I did not appreciate the lengths that people would go to in order to avoid thinking." Watch the full talk here: https://lnkd.in/gyT6jj4k
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Lenny Rachitsky shared thisOne of my favorite lessons from Robby Stein's talk at the Lenny & Friends Summit: "People say the PM's main craft is that you do lots of things pretty well. Above all else though, the craft of PM is one simple thing: decision-making. You should be students of what it takes to make great decisions." Full talk here: https://lnkd.in/gmQkaEsp
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Lenny Rachitsky shared thisNow that the Lenny & Friends Summit is a few weeks behind us, I’ve had a chance to reflect on the day. Here are the top five themes and takeaways that have stuck with me most: https://lnkd.in/gUWU6Tuq Also, a little slideshow. It’ll warm your heart. 👇
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Lenny Rachitsky posted this25 awesome early-career PM roles hiring right now (via LennysJobs.com): 1. Databricks — Associate Product Manager, New Grad (2027 Start) ($133–150K) https://lnkd.in/ghMJERuf 2. Roblox — Associate Product Manager, Early Career ($143K) https://lnkd.in/gZz3z87K 3. Robinhood — Associate Product Manager (New Grad) ($130K) https://lnkd.in/ga5287Rf 4. Google — Associate Product Manager, University Graduate, 2027 Start https://lnkd.in/gZPx6RJb 5. Stripe — Product Manager: New Grad Accelerator https://lnkd.in/gZeYB5E4 6. Solace Health — Associate Product Manager (College Grad 2027) https://lnkd.in/gfSNrXSB 7. Meta — Rotational Product Manager https://lnkd.in/gqjUFm82 8. Adobe — 2027 MBA University Graduate - Product Manager https://lnkd.in/g4s3UbKC 9. Uncountable Inc. — Product Manager (New Grad) ($125–140K) https://lnkd.in/gU93CH_V 10. IBM — Entry Level Product Manager, IBM Power - Austin, TX - 2027 https://lnkd.in/gGf8yaPw 11. EliseAI — Associate Product Manager | Housing ($150–220K) https://lnkd.in/gaCpgWch 12. Fireworks AI — Associate Product Manager ($160–180K) https://lnkd.in/g6eYee5n 13. AppLovin — Associate Product Manager ($111–167K) https://lnkd.in/gHxruMGg 14. IXL Learning — Associate Product Manager, New Grad ($95–120K) https://lnkd.in/g66UhcFk 15. Red Ventures — 2027 Early Career: Associate Product Manager, AI - NYC https://lnkd.in/gxwi6hp2 16. First Resonance — Associate Product Manager ($120–150K) https://lnkd.in/gc2PqYSG 17. FourKites, Inc. — Associate Product Manager ($90–120K) https://lnkd.in/gpUd6DeZ 18. Saronic Technologies — Associate Product Manager https://lnkd.in/gDh94-Rx 19. Fanatics — Associate Product Manager, Baseball ($72–84K) https://lnkd.in/gJ-FQjCK 20. Hive — Associate Product Manager, Hive Models ($90–120K) https://lnkd.in/g-wsTxPb 21. Google — Associate Product Manager Intern, Summer 2027 https://lnkd.in/g-PmVWdq 22. Coinbase — Associate Product Manager Intern https://lnkd.in/gpstYXXR 23. Duolingo — Associate Product Manager, Intern https://lnkd.in/gp5KWx26 24. Atlassian — Product Management Intern, 2027 Summer U.S. https://lnkd.in/gva7Ej6G 25. Datadog — Product Management Intern ($100–110K) https://lnkd.in/g53w7n7H Browse all roles: lennysjobs.com
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Lenny Rachitsky shared thisThree more talks from the Lenny & Friends Summit now online: 1. Elena Verna (Head of Growth at Lovable) 2. Tamar Yehoshua (CPO and Chief AI Officer at Atlassian) 3. Robby Stein (VP Product, Head of Google Search) Find them here: https://lnkd.in/g4C5tS2C
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Lenny Rachitsky shared thisMy biggest takeaways from Molly Graham: 1. Grief is a legitimate response to this moment, and leaders need to make more space for it. 2. At the same time, the fear narrative around AI job displacement is overblown, and it’s making it harder for people to lean in. 3. The more useful reframe: your job will always exist; it will just look completely different every few years. 4. Giving your Legos to AI is not the same as delegating to a human. 5. Some Legos should never be given away. 6. Her “Give away your Legos” advice still holds in one critical way: change is scary, and your instinct to resist it is the problem. 7. Every knowledge worker is now a manager, whether they trained for it or not. 8. Your manager is the single biggest lever on your happiness at work. 9. Zoom out. You are living through history, and the story you’re building right now is going to matter.
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Lenny Rachitsky shared this"The engineering job used to be rowing, and now it's steering. There's a lot of people out in the world right now that are like, I don't want to f*cking steer. I want a row. I liked rowing." Listen to my full conversation with Molly Graham: https://lnkd.in/gM35Y_wx
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Lenny Rachitsky reacted on thisLenny Rachitsky reacted on thisEric Ries joined the Lenny's Newsletter book club event this morning, hosted by Annie Warner, to discuss his new book, "Incorruptible: Why Good Companies Go Bad... and How Great Companies Stay Great." This was a particularly fun session for me because Eric played a role in influencing my thinking very early in my career. He had visited our offices at Pulse Energy before "The Lean Startup" was published and his insights rubbed off on us and inspired a lot of our processes. We were very early adopters of the methodology. With his new book, he builds off the wealth of experience he has gathered in helping companies to grow over the past twenty years and draws from the unique insights he gained as Founder of the Long Term Stock Exchange. It's an excellent book that forces companies to question a lot of things that are taken for granted about how companies. It also sheds light on the long term cost and consequences (financial and otherwise,) of going with "the way things have always been done." In addition to being a great book for companies, I think many of the lessons also apply to governments and non-profits. Thanks Annie for hosting and Eric for being available and sharing your wisdom.
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Lenny Rachitsky reacted on thisLenny Rachitsky reacted on thisHaving a little fun with my GrokBot setup 😅
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Lenny Rachitsky reacted on thisLenny Rachitsky reacted on thisHiring managers: ever read a perfect take-home and wondered whether the candidate crushed it, or their AI did? For the past two months, Aaron Keys and I have been building something to solve this problem and give the take-home interview a new life. We've talked to ~30 hiring managers and recruiters. Nearly everyone agreed take-homes used to be one of their best signals. AI changed that. Most teams have landed in one of three places: → Move away from take-homes → Add friction: 8+ hour take-homes, live presentations, recorded walkthroughs, costing everyone time → Ban AI and test for yesterday's job We think there's a better way to run a take-home when candidates use AI, and we're looking for a handful of design partners to build it with. We’re focused on data, product, FDE, ops, and marketing roles. If you have a take-home going out to candidates in the next month, DM me. We'll set it up with you and run it on real submissions.
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Lenny Rachitsky liked thisLenny Rachitsky liked thisAnnouncing a brand new private resource: this is a Vimeo playlist of 23 super candid videos of mine, with answers to your real career questions & dilemmas—no fluff, no BS, no nonsense. (Get the link to request the resource and the password in the comments)
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Lenny Rachitsky liked thisLenny Rachitsky liked thisAnother Lenny’s on the books! Milan fish 🐟 restaurant always on spot! Lorenzo Roveda Andrea Saporiti Francesco Villa Jasmine Comi Jacob Sprake FRSA Davide Carlomagno Anna Sapelnikova Subir Paul Matteo Risso Angelica Maria Puddu Simone Santonocito Marco Pedersini and myself
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Empirical expert determination and question routing system and method
Filed US 2866123
Systems and methods for empirical expert determination and question and answer routing are provided. They system collects location tracking data about each user and analyzes the location tracking data to empirically determine the level of expertise a particular user has for a specific venue/event or a specific geographic region at a particular scale on a map. The system receives questions about a specific venue/event or about a category of venue/event in a specific geographic region at a…
Systems and methods for empirical expert determination and question and answer routing are provided. They system collects location tracking data about each user and analyzes the location tracking data to empirically determine the level of expertise a particular user has for a specific venue/event or a specific geographic region at a particular scale on a map. The system receives questions about a specific venue/event or about a category of venue/event in a specific geographic region at a particular scale on a map and routes those questions in real time to one or more experts for the specific venue/event or the category of venue/event in the specific geographic region. The system receives a response to the question from at least one of the one or more experts and routes the response back to the requestor, also in real time. The system also efficiently represents the location of a plurality of venues/events and/or users within a specific geographic region on a displayed map at a plurality of scales of the map.
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Manjeet Singh
Marik Hazan this is a wild and ambitious idea: A fleet of autonomous Agent founders building companies on their own. Imagine an agent picks a niche based on social listening, spot unmet needs, trends, complaints (e.g., AI for property managers), builds a SaaS MVP using vibe coding, runs outbound + paid tests, and iterates based on conversion and engagement. PMF search becomes an optimization problem over a huge agent portfolio, and humans become capital, governance, and exception handlers.
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Ronnie Parsons
I spent Q4 testing agent frameworks with Lab members. Not theoretical demos. Real implementations for solo founder businesses. Some created genuine capacity, freeing founders from operations so they could work on partnerships, products, strategic initiatives. Others? Time sinks that automated nothing meaningful. If you're building agents for your business in 2026, here's where to start: 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻: 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗔𝗜 "𝗮𝗴𝗲𝗻𝘁𝗶𝗰" Google's primer on agentic AI explains the core distinction: autonomy vs. chatbots https://lnkd.in/gFD7EABN This matters because most founders are still thinking in terms of task automation. Agents create something different, systems that handle decisions, not just execution. 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: 𝗛𝗼𝘄 𝗮𝗴𝗲𝗻𝘁𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗼𝗿𝗸 OpenAI Academy's workflow introduction shows how tools and memory combine https://lnkd.in/gtJHCRkK The bridge between "interesting demo" and "runs my lead qualification process" is understanding this architecture. 𝗛𝗮𝗻𝗱𝘀-𝗼𝗻: 𝗚𝗼𝗼𝗴𝗹𝗲'𝘀 𝟱-𝗱𝗮𝘆 𝗶𝗻𝘁𝗲𝗻𝘀𝗶𝘃𝗲 Models, tools, orchestration, memory, evals. The full stack from prototype to production https://lnkd.in/gDixaQcX 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀: 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰'𝘀 𝗰𝗼𝗼𝗸𝗯𝗼𝗼𝗸 Real-world agent patterns that actually work at scale https://lnkd.in/gs3jPjnd This is where you learn what breaks and how to build for reliability. 𝗜𝗻 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲: 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲 Watch agents build agents. Practical walkthrough of agentic coding https://lnkd.in/gjJZuZ26 𝗡𝗲𝘅𝘁-𝗹𝗲𝘃𝗲𝗹: 𝗚𝗼𝗼𝗴𝗹𝗲 𝗔𝗻𝘁𝗶𝗴𝗿𝗮𝘃𝗶𝘁𝘆 Mission Control interface for autonomous development agents https://lnkd.in/gtEeCJZD The progression matters here. Start with understanding agentic vs. automated. Build architecture knowledge. Get hands-on. Learn production patterns. Then deploy. When you're ready to dive in: https://mightyailab.com
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Vishal Singh
Decision modeling is key. Intent + decision traces created by agents need to be modeled to create self learning or ever improving decision quality ( measured via outcomes), while the criteria is non stop shifting. Process modeling - aka crud on system of records will also get eroded and merged with decisions models being stored. This is where Agebt plane and human plane converge.
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Sunil Nagaraj
Software beyond the screen companies have an early revenue path that pure software startups rarely touch. Government agencies fund deep tech R&D through SBIR grants, up to $2 million per award, and when handled right, those grants convert into recurring revenue. Ubiquity Ventures-backed WindBorne Systems is proof! The company just announced its $37 million Series B, and it got there in part on SBIR revenue: more than ten awards across NOAA and the military, each one converted into a recurring contract with the agency. In the newest Ubiquity University module, WindBorne CEO John Dean joins me for a crash course on SBIRs for founders. A few of the hard-won lessons: 👉 Skip any grant that will never become revenue. The good ones are the start of a long-term customer relationship 👉 Sell it like enterprise sales. Find the real buyer inside the agency, understand why the solicitation exists, and build a champion before you submit 👉 Get expert advice, but never outsource the proposal. Nobody knows your tech and your story like you do 👉 You write the milestones and the payment schedule, so make sure they work for your business Full video on Ubiquity University plus the WindBorne Series B news, links in the first comment. #SoftwareBeyondTheScreen #PhysicalAI
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