2026-06-14 20:31:44
Mark Pincus founded Zynga—the company behind Words With Friends, FarmVille, and Zynga Poker—and has arguably created more hit consumer products than anyone in history. At Zynga, eight of 10 major game launches became massive hits, reaching over a billion players. Over the past five years, Mark has been synthesizing everything he’s learned about building successful consumer products and turning it into a book, Life at the Speed of Play, which comes out on June 23. This is the first interview he’s done about the book.
Listen on YouTube, Spotify, and Apple Podcasts
His “Proven, Better, New” framework: copy what’s proven, make it better so that 10 out of 10 people say “f*ck yes, I’ll use this”—then add something new
Why being less ambitious is the path to the most ambitious ideas
His rule of thumb that your instincts are right 95% of the time, but your ideas are wrong 75% of the time
“Kill hope before hope kills you”
How to raise kids in the age of AI
WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more
Vanta—Automate compliance, manage risk, and accelerate trust with AI
• LinkedIn: https://www.linkedin.com/in/markpincus
• Website: https://www.lifeatthespeedofplay.com
• Tribe.net: https://en.wikipedia.org/wiki/Tribe.net
• Zynga: https://www.zynga.com
• Sid Meier: https://en.wikipedia.org/wiki/Sid_Meier
• Electronic Arts: https://www.ea.com
• CityVille: https://en.wikipedia.org/wiki/CityVille
• Words With Friends: https://wordswithfriends.com/
• Scrabble: https://playscrabble.com
• Reddit: https://www.reddit.com
• TED Radio Hour, MIT Media Lab founder, 1984 TED talk.: https://www.ted.com/talks/nicholas_negroponte_5_predictions_from_1984
• Peter Thiel on LinkedIn: https://www.linkedin.com/in/peterthiel
• FarmVille: https://en.wikipedia.org/wiki/FarmVille
• Craig Newmark: https://en.wikipedia.org/wiki/Craig_Newmark
• How to consistently go viral: Nikita Bier’s playbook for winning at consumer apps (co-founder of TBH, Gas, advisor, investor): https://www.lennysnewsletter.com/p/how-to-consistently-go-viral-nikita-bier
• Angry Birds: https://www.angrybirds.com/
• OMGPop: https://en.wikipedia.org/wiki/OMGPop
• Draw Something: https://en.wikipedia.org/wiki/Draw_Something
• Slack founder: Mental models for building products people love ft. Stewart Butterfield: https://www.lennysnewsletter.com/p/slack-founder-stewart-butterfield
• Brian Chesky’s new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach
• Garry Tan on LinkedIn: https://www.linkedin.com/in/garrytan
• Brian Armstrong on LinkedIn: https://www.linkedin.com/in/barmstrong
• Jason Citron on X: https://x.com/jasoncitron
• Stanislav Vishnevskiy on LinkedIn: https://www.linkedin.com/in/svishnevskiy
• Jeff Bezos on X: https://x.com/JeffBezos
• Andy Jassy on X: https://x.com/ajassy
• Niantic: https://nianticlabs.com
• Pokémon Go: https://pokemongo.com
• Bing Gordon on LinkedIn: https://www.linkedin.com/in/binggordon
• Life at the Speed of Play: Launch Products People Love!: https://www.amazon.com/Life-Speed-Play-Launch-Products/dp/0063352575/ref=tmm_hrd_swatch_0
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Lenny may be an investor in the companies discussed.
2026-06-14 04:54:15
👋 Hello and welcome to this week’s edition of ✨ Community Wisdom ✨ a subscriber-only email delivered every Saturday, highlighting the most helpful conversations and events happening in our subscriber-only Slack community.
A big thank-you to this month’s community sponsor, Strella. Strella is an AI-powered qualitative research platform that allows teams to run, analyze, and share customer interviews at scale without sacrificing depth. Usability testing, concept validation, discovery research, and more, Strella delivers insights fast and makes them accessible right where you work, including Claude, ChatGPT, and Figma, so your research keeps working long after the initial readout.
The Lenny and Friends Summit returns on September 10 in San Francisco. This will be the greatest assembling of product leaders in history.
We’re keeping it intentionally small (about 1,000 people)—every attendee will be handpicked—and along with in-depth talks from the world’s top operators, we’ll have interactive workshops, tons of opportunities to get to know other attendees, and a few fun surprises.
Here’s the initial lineup of speakers (with more to be announced soon):
Given that we’re anticipating lots of interest and the venue has limited capacity, we’re asking people to apply to attend. Paid newsletter subscribers will get priority access.
P.S. We’ve expanded capacity at the venue, so if you’ve received an email saying there wasn’t a spot for you, reply to this email and we’ll take another look at your application.
Click the city name to RSVP:
Amsterdam. June 17th. Thanks to @Adriana Mosnoi, @Ruslan Doronichev & @Luke Rynne Cullen!
Asheville. June 17th. Thanks to @Nathan Phillips!
Atlanta. June 25th. Thanks to @Ravish C.!
Austin. June 25th. Thanks to @Mark Vandegrift & @Andy Keil - Austin!
Bellevue. June 23rd. Thanks to @Aman Goyal!
Boston. June 17th. Thanks to @David Jorjani!
Chicago. June 17th. Thanks to @Jason Siegel!
Boulder. June 25th. Thanks to @Dave Carlyle!
Hong Kong. June 17th. Thanks to @Manny Reimi!
Lisbon. June 22nd. Thanks to @Gabriela Naumnik & @Nina Un!
Munich. June 16th. Thanks to @Lukas Gerhardt!
Philadelphia. June 17th. Thanks to @Keriann Sabatini & @Doug Clark!
San Francisco. June 25th. Thanks to @Tarek Sadi!
Santa Barbara. June 15th. Thanks to @Joni Hoadley, @Cody Landstrom, & @Oliver Barton!
Shenzhen Afternoon Meetup. June 18th. Thanks to @Ivan Xu!
Toronto. June 24th. Thanks to @Jessie Wang!
Valencia. June 26th. Thanks to @Paul Boudet!
Vienna. June 16th. Thanks to @Serge Versille!
Warsaw. June 16th. Thanks to @Matt Swulinski!
We have a special event for the community’s #book-club this month: June’s book club selection is The Mom Test by Rob Fitzpatrick, and the man himself, Rob, will be joining us on June 24 for a Q&A!
Join the #book-club channel to participate, and be sure to RSVP by June 23. Huge shoutout to Akil Bhagat for running the current iteration of our book club.
We’d love to get your perspective on what it’s like to work in tech right now. The survey will take less than 5 minutes to complete, and we’ll send you the anonymized raw data so you can perform your own analysis, along with an early look at the results before we share them publicly.
Father of the iPod and iPhone on building taste, judgment, and creativity in the AI era | Tony Fadell: YouTube, Spotify, Apple Podcasts
Claude Fable 5 review: what the new Mythos model gets right (and very wrong): YouTube, Spotify, Apple Podcasts
5 Career Questions Your Old Playbook Can’t Answer: YouTube, Spotify, Apple
Thought of posting this on #talk-lol, but this is such an interesting use case and it seems real. Someone “hooked my Whoop to my work calendar to find which coworker gives me the most stress.” One of the replies: “HR reviews could never, this has actual data. Somewhere an Anthropic PM is adding ‘coworker stress forensics’ to the use case list. Legend behavior, monetize it.” ↗
—Guy Peled
Jeremy: I did a similar thing a few months ago, but used Apple Watch heart rate data. I only tried it once, but noticed that my heart rate was lower in larger meetings, but certain 1:1s definitely caused a spike. I’m fairly confident it was related to the level of engagement, but it was a fun vibe-coded experiment.
Guy Peled: Love it. So many factors go into this. Definitely beyond the people in the room:
Amount of people
Your host/participant role
Content (e.g. department restructuring announcement meeting)
etc.
Abdussamad Bello: Has to be a PM!
Miroslav Pavelek: I love the idea! But in comments it is also correctly pointed out that, well, Whoop (or any other device on the market) is not really good at measuring stress.
Jeremy: @Miroslav Pavelek It’s best to view them as directional instead of completely accurate. Exploring the concept with this level of data feels reasonable to me.
For managers of managers, how do you have your leaders provide weekly status reports for non-sprint/dev-related work? For example, initiatives that involve other divisions/teams, GTM work, research, etc.—how do you stay up to date with progress and what their teams are focused on? ↗
Ian McAllister: For anything weekly sent via email, do your teams a favor and enforce a very short/crisp format. Green/Yellow/Red status for key projects with a path to Green for anything Yellow or Red. Anything longer simply won’t get read, so all the effort writing it is wasted.
Save the thoughtful descriptions and details for monthly reviews when there is time to process and discuss.
Aaron Nichols: I think this depends greatly on why you want those updates. I’ve operated in teams where those updates needed to go to someone else—in which case I can just observe what gets reported through those normal means. I’ve also operated in orgs where my teams operated fine without my oversight on regular execution and MBR/QBR updates were sufficient to keep tabs. I tend to be more worried about whether my teams are getting good context and signal from me and their stakeholders than about status updates to me—but this all depends on your level, the size of your org, maturity, etc.
There’s a reality here that you simply do not stay up to date on what everyone is doing. You’ll spend all your energy keeping tabs instead of doing the work you actually should be doing.
Cindy Cohen: I’ve found the most effective updates focus on outcomes, risks, and decisions needed.
For cross-functional initiatives, I typically ask leaders to provide:
Objective / desired outcome
Current status (green/yellow/red)
Key accomplishments since last update
Next 1–2 priorities
Risks, dependencies, or blockers
Decisions or support needed from leadership
Then I use 1:1s to go deeper where needed rather than reviewing everything in detail.
The biggest mistake I see is reporting activity (“met with X, researched Y”) instead of progress toward an outcome. A short update tied to objectives usually provides enough visibility without creating reporting overhead.
Adam Thackeray: Put @Ian McAllister recommendation in bold. Simple is better. Get to the point and what help is needed (if at all).
Question for solo founders and 2–5-person teams where everyone is an engineer or PM: how are you handling marketing/GTM day-to-day?
Roughly three paths I keep seeing, curious which one you took and how it went:
Hire an agency/freelancer—pay someone external to run SEO, content, ads, etc.
Hire a GTM/marketing person—first marketing hire, in-house
DIY—founder learns the tools and systems (SEO, email, social, ads) and just does it
React with (1), (2), (3) for what you actually did, and if you have 2 minutes I’d love to hear:
Roughly what it costs you per month (money and/or founder hours)
What you’d do differently if starting today
(Context: solo founder with a product background here—figuring out how much of marketing I should learn vs. buy. Not selling anything in this thread.) ↗
—Jake Luo
Shawn Jones: Hermes agent + company context brain (LLM-wiki) + growth skills + management tool (Notion/Linear/etc.).
Jake Luo: Cool solution. Would you mind sharing what growth skills you use? Do you use the Hermes agent to run your SoMe and ads campaigns as well?
Shawn Jones: I recommend creating your own custom skills for your industry/business, but have your agent reference these for inspiration: https://github.com/coreyhaines31/marketingskillsi
Primarily have my agent focused on the content development and management side. I’m planning to set up ad management next.
Christos Apartoglou: I think it is hard to assess what the right direction for your team is with the information you provided. My recommendation is to do the following exercise:
Spend some time understanding what your team needs at this life stage. Is it validating PMF? Is it demand generation? Something else?
For the needs you have identified, it will be important to then understand if they are one-offs or evergreen and the relative degree of prioritization. This can guide you on identifying the skills and competencies you may need to add to the team and for how long.
This information can help guide your staffing approach between the three options you are contemplating. If you already have done this work I am happy to jump on a quick 30-minute call and help make sense of it. I was an in-house marketing lead for many companies in the past and now have a fractional consulting practice (though I am not attempting to sell you anything—I don’t have capacity for more clients atm).
Matthew Stublefield: Founder and solopreneur here. I recommend the books Obviously Awesome and Crossing the Chasm and learning about positioning and copywriting. I have built and bought some AI tools that help me with copywriting and SEO, and that combined with some reading and learning has helped. I also paid for some inexpensive digital courses that helped (Csaba Borzasi and Katelyn Bourgain).
Bal Sieber: Path 3, with an asterisk. Solo consultancy here, product design background, so writing was never the scary part. The system was. What I actually run: I do the thinking and the voice, and a set of scheduled AI jobs does the reps. Sourcing who to talk to, drafting engagement, keeping the daily floor. My time lands around an hour a day of reviewing and steering rather than producing. Tooling is a few hundred a month all in. No agency, no hire. What I’d do differently: skip the months of treating marketing as the thing I’d get to after the real work. It only started compounding once it got the same seriousness as client work, a daily floor and a weekly review. One caveat: This shape works because my buyer hangs out where text lives. If your customers need ads or SEO at scale, my setup says nothing about that.
Jake Luo: Seems like many folks focus on content writing and SEO, which is great for building organic pipeline. But sometimes I feel like it’s slow. I would consider doing performance marketing to accelerate user acquisitions. Then how to run paid ads efficiently and effectively is another challenge to tackle.
Mih Fodor: Buy the Demand Curve program and go through it. You’ll have everything planned after that, and you can use what @Shawn Jones suggested.
Bal Sieber: Paid is the one lane I can’t speak to with real numbers, so season this hard. The one thing I’d check before buying acceleration, since it’s the part I do see every week: what the first session after the click does. Ads multiply whatever your signup-to-first-value path already does, so if that path leaks, paid mostly accelerates the leak, at CPC prices. The slow organic phase is annoying, but it’s also cheap rehearsal. You find the funnel holes while the traffic is free. I’d want evidence the path holds before paying to fill it.
Dinuka Wijesinghe: As a starting point before you think about execution, I’d encourage you to spend high-quality time developing the following:
Target market/ICP
Market dynamics incl. competitors and alternatives
Your positioning in relation to market dynamics (value prop, problem & solution statements, pricing etc.)
Likely acquisition channels based on where you think your ICP is and where you’re likely to recognize their trigger point
One primary GTM metric (e.g. # of users, amount of usage, $s etc.) and a goal for that metric—start with only one metric
Interrogate these with your team/investors/trusted advisors—once you feel like you know this back to front and have confidence in it, then think about how you could systematically execute outreach. For example, pick 2-3 channels to test, what would be an ideal cadence of outbound activity you’d need to execute to get meetings/users. At first this will be an educated guess, but you can refine once you get more data. Only then should you consider the mechanics of execution (i.e. the options you and others have listed here)—and the answer will become clearer. More importantly, you’ll have the rationale for the decision you made, which will make it easier for you to adjust if the data you get is different. Take your GTM as seriously as your product. Throwing AI at it or hiring an agency from the start won’t deliver good results if you as the founder don’t have the clarity to ask the right questions. If you want to chat specifics in relation to your market, I can do a short call.
Harshil Bhimani: I have worked with founders before, going 0 to 1. Usually they have a very good understanding of ICP. So the main goal is to find message-market fit. I think all options have tradeoffs. Imo you can do it yourself if you have bandwidth, otherwise outsource it to a good agency/freelancer. Hiring FT is very costly if you don’t have a playbook imo. Wish you luck!
I’m curious to know, how has AI actually changed the way your product team operates?
For context, I’m working on re-organising the product operating model in my org and want to understand what’s working for others.
Two things I’m keen to learn from people who’ve gotten their hands dirty:
What’s one thing that’s genuinely changed in how your team works—not just speed, but how you’re structured, how you hand off to engineering, or how decisions get made?
I’m hearing PMs or designers pushing changes directly to GitHub a lot. We are not there yet, so for those who do, what does that look like in practice, and what did you need to be in place for it to work?
If you’ve worked with teams experimenting with BMAD or similar approaches, I’d love to hear what the PM side of that looks like.
If this has been answered before, happy to be pointed to the relevant thread. ↗
—Nishanth D’Souza
2026-06-10 02:32:03
Claude Fable 5 is the first Mythos-class intelligence model to be generally available, and I got early access to test it before launch. I walk through what Anthropic is promising, what actually stood out when I used it on real work, and where I think it fits in your AI stack.
Listen or watch on YouTube, Spotify, or Apple Podcasts
(00:00) Introduction: Fable 5 is finally here
(00:31) What Anthropic says about the model
(05:14) Token-intensive by design
(06:28) Safety classifiers and the new fallback concept
(07:46) Is this or is this not Mythos?
(08:30) New product launches: Managed Agents and more
(09:20) Crushing benchmarks
(09:55) What it’s actually like to use (the good and the bad)
(11:40) Test 1: product graph spec
(12:56) Test 2: designing a skills registry
(14:04) Conservative on execution
(14:43) Test 3: multi-agent orchestration
(15:39) My takeaways
• Claude Fable 5: https://www.anthropic.com/news/claude-fable-5-mythos-5
• Claude Managed Agents: https://platform.claude.com/docs/en/managed-agents/overview
• SWBench Pro benchmark: https://www.swebench.com/
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
2026-06-09 21:11:29
👋 Hey there, I’m Lenny. Each week, I answer reader questions about building product, driving growth, and accelerating your career. For more: Lenny’s Podcast | Lennybot | How I AI | My favorite AI/PM courses, public speaking course, and interview prep copilot
P.S. Get a full free year of Google AI, Cursor, Lovable, Notion, Manus, Replit, Gamma, n8n, Canva, ElevenLabs, Factory, Wispr Flow, Fin, Supabase, Bolt, Linear, PostHog, Framer, Railway, Granola, Warp, Gumloop, Magic Patterns, Mobbin, Stripe Atlas, and ChatPRD, by becoming an Insider subscriber. Yes, this is for real.
On the heels of part 1 of my essential books for product builders series, I’m excited to share part 2.
As with last time, the books are organized by their jobs-to-be-done in your work and life. I’m again limiting myself to only three per category that I’ve personally read (and completed), and only books that have stood the test of time (i.e., no new books). As a bonus, at the end of the post I’ve also included a dozen fan favorites that either fell just below the ones I picked or I haven’t had a chance to read yet.
I know it’s hard to find time to read a whole book, and when you do, it’s hard to retain anything. As I mentioned in part 1, what’s worked for me is to read 10 minutes before bed as part of my wind-down routine. This has the added benefit of helping me sleep better! And as I read, I try to find one nugget or tactic that I can bring into my work that week. I take a photo of it and email it to myself (using this sweet app) for the next morning. My philosophy is that if I retain just one golden nugget per book over the years, I’m happy. That’s how it usually ends up working out anyway.
So, as I share the book recommendations, I’ll also highlight a nugget of wisdom that’s still with me over the many years since I first read these books.
Let’s get into it.
“Books are the closest thing you’ll ever come to finding cheat codes for real life. You can access the entire learnings of someone else’s career in a few hours.” —Tobi Lütke
Before reading these books, I thought design was a squishy, subjective thing. It’s not. Don’t Make Me Think taught me how to objectively make a product UI work (and feel) better. The Design of Everyday Things showed me that when I struggle with a product, it’s not my fault—it’s the design’s. Refactoring UI gave me a ton of specific design tactics.
Don’t Make Me Think by Steve Krug
The Design of Everyday Things by Don Norman
Refactoring UI by Adam Wathan and Steve Schoger
I’ve always looked up to people who have great taste, and lucky for me, guests on my podcast consistently remind me that it isn’t something you’re born with—taste is something you can learn. The War of Art helped me learn how to recognize and overcome the internal “resistance” that comes with creating something new and different. The Work of Art showed me the creative process of dozens of high-taste creators. Creativity, Inc. taught me to protect my (and my team’s) “ugly babies”—early half-baked ideas that otherwise get squashed.
The War of Art by Steven Pressfield
The Work of Art by Adam Moss
Creativity, Inc. by Ed Catmull
Influence—maybe you’ve heard it’s important? It’s something I was very bad at early in my career, and I’ve had to learn how to do it well. How to Win Friends and Influence People showed me the power in being interested vs. interesting. Influence taught me the fundamentals of how people change their mind: social proof, authority, scarcity, and simply being liked. Never Split the Difference taught me how to shift a negotiation from “you vs. me” to “us” working together to solve the problem.
How to Win Friends and Influence People by Dale Carnegie
Influence by Robert Cialdini
Never Split the Difference by Chris Voss
I’ll be honest, I didn’t read a lot of books when I was starting my company. But I should have. When I finally read The Lean Startup, it showed me how to be smart about where to start, and how to iterate efficiently. Crossing the Chasm taught me what a good early user looks like. Fall in Love with the Problem, Not the Solution finally gave me a very practical guide for every step of the founder journey.
The Lean Startup by Eric Ries
Crossing the Chasm by Geoffrey Moore
Fall in Love with the Problem, Not the Solution by Uri Levine
There are certain books you read and you’re just like, “Wow, this really explains what’s going on around here.” These three did that for me. Great at Work showed me that people who rise fastest focus on fewer things but do them extremely well. 7 Rules of Power taught me that, often, it isn’t the most talented or nice people who end up winning. The Effective Executive helped me understand that efficiency is doing things well, while effectiveness is doing the right (highest-leverage) things.
Great at Work by Morten T. Hansen
7 Rules of Power by Jeffrey Pfeffer
The Effective Executive by Peter Drucker
A few readers suggested that this category should have come first last time—what else matters if you can’t be happy? So I’m including another three books that made me a happier person. The Subtle Art of Not Giving a F*ck taught me that freedom from work isn’t the real goal. Instead, it’s your opportunity to figure out what problems you want to spend time solving, because the most lasting fulfillment comes from solving problems we care about. A Guide to the Good Life gave me the skill of “negative visualization,” which I use to this day. Stumbling on Happiness showed me that we’re often (very) wrong about what will make us happy.
The Subtle Art of Not Giving a F*ck by Mark Manson
A Guide to the Good Life by William B. Irvine
Stumbling on Happiness by Daniel Gilbert
2026-06-08 23:01:21
Listen now on YouTube • Spotify • Apple Podcasts
Brought to you by:
Merge—Connective infrastructure for production AI
Jira Product Discovery—Prioritize with insights, build with confidence
In this solo episode, Claire puts Google Flow and Gemini Omni to the test by cloning herself into an AI avatar and using it to build a full hype reel in about 15 minutes. She walks through the whole workflow live: scanning her face, generating scenes, troubleshooting weird outputs, stitching the video together, and reacting to the very real uncanny-valley moments along the way. It’s part tutorial, part tech demo, and part “wait, this is already possible?” glimpse into how AI video tools are making high-quality creative production accessible to anyone with an idea and a laptop.
AI video tools are unlocking creative capabilities for non-video professionals. Claire, who describes herself as “creative, but not video-creative,” was able to produce a complete one-minute hype video without any prior video production experience. The entire process—from creating an avatar to final video—took roughly 15 minutes, demonstrating how these tools democratize creative work that previously required specialized skills and expensive equipment.
AI can serve as a creative collaborator, not just a tool. Rather than just generating videos, Google Veo acted as a creative partner, helping Claire brainstorm scenes, develop a storyboard, and think through the overall narrative arc. The AI asked clarifying questions about setting, tone, and style, then proposed a seven-scene structure that Claire could refine and execute.
Character consistency remains a major challenge in AI video generation. Throughout the generated videos, Claire’s avatar appeared with different hair lengths, varying backgrounds (some with books, some with plants, different wall colors), and inconsistent environmental details. While the AI pulled some accurate elements from her original photos (like posters in the background), it couldn’t maintain perfect consistency across scenes.
Emotional expression is still a weak point for AI avatars. While some scenes looked remarkably realistic—particularly side profiles and serious expressions—scenes requiring emotion fell flat. Claire described one laughing scene as “100% uncanny valley,” noting she looked like she was “on some kind of medication perhaps.” The technology hasn’t quite mastered the subtle muscle movements that make human expressions feel authentic.
The workflow from idea to finished video is remarkably fast. The entire process included creating the avatar (a few minutes), brainstorming with AI (a few minutes), generating seven video scenes (several minutes total), and stitching them together in the built-in editor (about five minutes). What would have traditionally required a production team, studio time, and significant budget happened in a single session at a desk.
How I Built an AI Avatar and Hype Video in 15 Minutes with Google Flow: https://www.chatprd.ai/how-i-ai/ai-avatar-video-in-15-minutes-with-google-omni-flow
↳ How to Create a Promotional Video with an AI Creative Director: https://www.chatprd.ai/how-i-ai/workflows/how-to-create-a-promotional-video-with-an-ai-creative-director
↳ How to Create a Personalized AI Avatar with Google Flow: https://www.chatprd.ai/how-i-ai/workflows/how-to-create-a-personalized-ai-avatar-with-google-flow
Listen now on YouTube • Spotify • Apple Podcasts
Brought to you by:
Nicole Ruiz has built a Claude-powered shopping system to help her family buy fewer, better things—and avoid the endless noise of Amazon, drop-shippers, and low-quality brands. In this episode, she shares how she uses Claude Projects to vet every household purchase against criteria like craftsmanship, materials, brand history, and return policies, plus how she uses Claude Cowork to make returns faster when something doesn’t hold up. It’s a practical look at how AI can reduce decision fatigue, surface higher-quality products, and help busy parents spend less time managing stuff.
The modern internet shopping experience is broken for people who want quality over convenience. Between paid ads, drop-shipping brands, and knockoff products on Amazon, it’s incredibly difficult to find thoughtfully made items that will last for years. Nicole’s solution: build a Claude Project that holds all her purchasing criteria and trusted brands in one place, so she never has to start from scratch.
Keep a running list of brands you trust, and let AI search through them for you. Nicole maintains a list of shops with decades of history, strong return policies, and proven craftsmanship. When she needs something, she asks Claude to search through these trusted vendors first. This flips the typical shopping flow: instead of searching the entire internet and filtering out garbage, she’s searching a pre-vetted list and only expanding if needed.
Your purchasing criteria should be written down and reusable. Nicole has specific requirements: natural materials, made to last and repair, decades of business history, strong return policies, and no trendy direct-to-consumer brands that over-invest in advertising. By codifying these criteria in a Claude Project, she removes the mental overhead of running through an invisible checklist every time she needs to buy something.
AI can surface brand history and quality signals that would take hours to research manually. When Nicole queries a product, Claude explains why each brand is trustworthy, surfacing details like “This brand has been manufacturing the same tote bag for over 80 years” or “This company got acquired two years ago and reviews have been abysmal since then.” These insights help her make informed decisions without hours of research.
The worst websites often belong to the best manufacturers. Heritage brands that have been making quality products for decades frequently have terrible websites that are hard to navigate. This puts them at a disadvantage compared with Amazon or well-funded DTC brands. AI levels the playing field by making it just as easy to shop from a 100-year-old manufacturer with a clunky website as from Amazon.
Format your AI shopping results to surface the information that matters most to you. Nicole’s Claude Project presents each product with specific details: product name, photo, price, materials (especially important for avoiding plastic), care and maintenance notes, purchase link, and a brief note on the brand’s trustworthy history. This consistent format makes it easy to compare options and make quick decisions.
Use AI to automate the tedious parts of returns and refunds. When a product fails—like J.Crew pants that wore through after six months—Nicole uses Claude Cowork to pull the original receipt from her email, find the order details, and draft a customer service email requesting a refund. What would normally take 10 to 15 minutes now takes 2 to 3 minutes of voice dictation from her phone.
AI can identify manufacturing issues by analyzing review patterns. When Nicole requests a return, Claude often discovers that other customers had the same problem with the same product from the same time period, suggesting a manufacturing defect rather than normal wear. This strengthens her refund request and helps her avoid brands with known quality-control issues.
Build your shopping system for multiple use cases. Nicole uses her Claude Project in three main ways: “Help me find a can opener” (specific item search), “I have $30 for L.L.Bean; what should I buy?” (budget-constrained search), and “What’s your analysis of this brand I found?” (vetting a new brand). This flexibility makes the system useful for different shopping scenarios.
Buying quality items up front reduces household maintenance over time. Nicole’s philosophy is to move as much vetting upstream as possible. She lives in a small Brooklyn apartment with two young children, and every item needs to stand the test of time. By investing time in building a shopping system that prioritizes quality, she spends less time dealing with broken items and processing returns. The goal: buy things that will last for multiple children and can be mended rather than replaced.
Buying High-Quality Goods With Claude: https://www.chatprd.ai/how-i-ai/buying-high-quality-goods-with-claude
↳ Automate Product Returns and Refunds Using Claude Cowork: https://www.chatprd.ai/how-i-ai/workflows/automate-product-returns-and-refunds-using-claude-cowork
↳ Build a Buy-It-for-Life AI Shopping Assistant With Claude: https://www.chatprd.ai/how-i-ai/workflows/build-a-buy-it-for-life-ai-shopping-assistant-with-claude
If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.
Catch you next week,
Lenny
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2026-06-08 20:03:27
Nicole Ruiz is a writer and parent who has built a comprehensive AI-powered shopping system to help her family buy high-quality, long-lasting items while avoiding the noise of drop-shipping brands, paid ads, and poorly made products. She writes an interview series on Substack about how technology is changing the household.
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How to build a Claude Project with custom instructions for vetting brands based on heritage, craftsmanship, and return policies
The shopping criteria that help surface century-old manufacturers over trendy direct-to-consumer brands
How to use Claude to search through trusted vendor websites that have terrible UX
Why AI actually helps small artisans and heritage brands compete against Amazon’s infrastructure
How to use Claude Cowork to automate returns by finding receipts in your email and drafting refund requests
The technique for getting Claude to analyze whether a brand is legitimate or just a drop-shipping operation
How to shop within a specific budget or with gift cards using AI assistance
Orkes—The enterprise platform for reliable applications and agentic workflows
Metaview—The agentic recruiting platform for winning teams
(00:00) Introduction to Nicole and AI-powered shopping
(02:29) The problem
(04:55) Building a Claude Project for household purchasing
(07:44) The “anti-to-do list” concept for reducing mental overhead
(10:30) Shopping for a can opener: the system in action
(15:53) How AI helps century-old brands with terrible websites
(18:45) Processing returns with Claude Cowork
(25:06) Using gift cards strategically
(26:33) Vetting brands
(29:40) Recap, lightning round, and final thoughts
• Claude: https://claude.ai/
• Claude Cowork: https://www.anthropic.com/product/claude-cowork
• Boston General Store: https://bostongeneralstore.com/
• L.L.Bean: https://www.llbean.com/
• Manufactum: https://www.manufactum.com/
• 5 OpenClaw agents run my home, finances, and code | Jesse Genet: https://www.lennysnewsletter.com/p/5-openclaw-agents-run-my-home-finances
• From a $6.90 newsletter to $3M API: How a non-coder built Memelord | Jason Levin: https://www.lennysnewsletter.com/p/from-a-690-newsletter-to-3m-api-how
Substack (The Third Oikos): https://www.thirdoikos.com/
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].