AI and I

Chris Pedregal knows how to build AI products that people love. Chris is the cofounder and CEO of Granola, an AI notepad for meetings. We use it all the time at Every—Granola listens in on a meeting and, when it ends, generates notes and a shareable transcript for anyone who missed it.  Granola is one of my favorite consumer AI products because it’s equal parts delightful and useful. So my question for Chris was: How do you do it? How do you make an excellent product in AI?  We spent an hour talking about: How Chris uses intuition while making product decisions  The importance of building products with “soul” How to develop your product thinking muscles When Chris trusts his gut over listening to user feedback    How fewer users gives startups a leg up over big tech Why Chris is bullish on founders building specialized AI tools for professionals This is a must-watch for anyone interested in building valuable, sticky AI products that users will love. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps for Spotify: Introduction (00:00:48) How Chris made early product decisions at Granola (00:09:14) Chris’s philosophy around product development (00:13:36) When to follow your intuition v. listen to your users (00:19:24) How to build a product with “soul” (00:20:40) Chris’s advice on becoming a better product thinker (00:25:12) The role travel plays in shaping Chris’s intuition (00:31:17) Why having fewer users is an advantage for AI startups (00:45:52) Why Chris is bullish on startups building specialized AI tools (00:52:09) Where Chris sees Granola in the next year (00:56:52) Links to resources mentioned in the episode:   Chris Pedregal: @cjpedregal Granola: http://Granola.ai, @meetgranola  The piece Chris wrote for Every about building useful AI products: https://every.to/thesis/how-to-build-a-truly-useful-ai-product 

Here’s the most compelling benchmark of AI progress:  A task that took 60 minutes a year ago now takes 60 seconds. In January 2024, Geoffrey Litt and I spent an hour coaxing ChatGPT and Replit to build an app live on my podcast.12 months later, Steve Krouse and I built the same app with one prompt in less than a minute.  Steve is the cofounder and CEO of Val Town, a cloud-based platform for developers to write, share, and deploy code directly in the browser. We used Townie, Val Town’s AI assistant, to build an app to keep track of time on the podcast, take notes, and generate questions for the guest.   Townie generated the app even before Steve could finish describing it on the show. As we demo Townie, we get into: Why Steve believes programming can rewire the way you think  The rise of the non-technical AI developer and what that means for the future of coding How Townie works under the hood, including the details of the system prompt  How Steve is evolving ValTown’s strategy as AI progress continues to unfold The power of small, dense engineering teams  This is a must-watch for founders building AI-powered developer tools, and anyone interested in the future of programming. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Introduction (00:00:55) How programming changes the way you think (00:03:24) Building an app in less than 60 seconds (00:11:22) How Val Town’s AI assistant works (00:17:19) Steve’s contrarian take on the non-technical AI programmer (00:23:05) The nuances of building software that isn’t deterministic (00:33:38) How to design systems that can capitalize on the next leap in AI (00:39:05) What gives Val Town a competitive edge in a crowded market (00:40:47) The power of small, dense engineering teams (00:47:34) How Steve is positioning Val Town in a strategic niche (00:52:26) Links to resources mentioned in the episode:  Steve Krouse: https://stevekrouse.com/, @stevekrouse  Val Town: https://www.val.town/  Townie, the AI assistant integrated into Val Town: https://www.val.town/townie/signup?next=%2Ftownie  Pieces on Val Town’s blog about how the team built Townie: How we built Townie—an app that generates fullstack apps, Building a code-writing robot and keeping it happy  The book by Seymour Papert about how programming changes the way you think: Mindstorms: Children, Computers, and Powerful Ideas

Over the last few months at Every, we’ve: Launched two AI products Acquired tens of thousands of users Released a new incubation in private alpha The weird thing is: We’re a media company with < 10 full-time employees, and we’re mostly bootstrapped. That’s not how things are supposed to work in startups. When we started our product incubation arm six months ago, many people told us it wouldn’t work: divided focus, not enough money, and the biggest one—it would be too hard to find talented people to run the products we build. Yesterday, we proved out one of the biggest risks to our strategy: We launched a brand-new version of our AI product Spiral (https://spiral.computer) with Danny Aziz as GM—who left a $200K salary to join us.  The question is: Why? Why did he join us, and why is the model working when it “shouldn’t” be? That’s why I invited Danny and Brandon Gell, Every’s head of Studio, on the show. We get into the details of Every’s business model, what makes our flywheel turn, where each of us sees ourselves one year from now, and what happens when you mix media, software, and AI under one roof. This is a must-watch for anyone who wants to build a business on their own terms, and have a lot of fun while doing it.  If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Introduction: 00:01:08 All about Spiral, the tool we recently launched: 00:02:15 Why Danny left a $200,000 salary to work at a bootstrapped media company: 00:04:06 How we do a lot of things well at Every: 00:10:33 What makes Every’s flywheel turn: 00:14:44 The kind of people who fit right in at Every: 00:17:11 How Every is differentiated from a standard VC-backed startup: 00:23:25 How Danny found his way into the world of startups: 00:36:11 The tech industry’s affinity for potential over experience: 00:46:43  Where each of us sees ourselves in the next one year: 00:52:38 Links to resources mentioned in the episode:  Danny Aziz: @DannyAziz97 Brandon Gell: @bran_don_gell Try Spiral here: https://spiral.computer/   More about Every’s product incubation arm: https://every.to/p/introducing-every-studio 

Everyone told Vicente Silveira that his startup—a GPT wrapper—would fail.  Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store.  Vicente is the cofounder and CEO of AI PDF, a tool that can help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload PDFs to ChatGPT, the consensus was that his startup, and all the other GPT wrappers out there, were toast.  Some of his competitors even shut shop, but Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building.  A year later, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it all with a five-person team, and a friends and family round.  I sat down with Vicente to understand, in granular detail, the success of AI PDF. We get into: Why staying small and specialized is a bigger advantage than you think The power of building with your early adopters Why lean startups are better positioned than frontier AI companies to create radical solutions  When a growing startup should think about raising venture capital The emerging role of ‘AI managers’ who will be responsible for overseeing AI agents  We even demo an agent integrated into AI PDF, prompting it to analyze recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements. This is a must-watch for small teams building profitable companies at the bleeding edge of AI.  If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Introduction: (00:00:35) AI PDF’s story begins with an email to OpenAI’s Greg Brockman: (00:02:58) Why users choose AI PDF over ChatGPT: (00:05:41) How to compete—and thrive—as a GPT wrapper: (00:06:58) Why building with early adopters is key: (00:20:49) Being small and specialized is your biggest advantage: (00:27:53) When should AI startups raise capital: (00:31:47) The emerging role of humans who will manage AI agents: (00:34:53) Why AI is different from other tech revolutions: (00:45:25) A live demo of an agent integrated into AI PDF: (00:54:01)