AI and I

Building an email client used to take many years and millions of dollars. But Every’s Kieran Klaassen built Cora—a totally new way to manage your inbox with AI—in just 3 months. He even shipped the original MVP of the product in a single day—something that just wasn’t possible before the current state of generative AI.  Now, there are almost 10,000 people on the waitlist for Cora, and we’re onboarding new users every single day.  Every’s head of Studio Brandon Gell and I worked closely with Kieran as he built Cora, and to kick off my podcast, AI and I, in 2025, I invited both of them on the show to talk about it. We go behind the scenes, getting into: How Kieran built the product with Cursor, o1, and o1 Pro What we’re learning as we onboard new users every day The future of Cora and of Every as a multi-modal media company This is a must watch for anyone curious about our approach to building with AI at Every. 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: 00:01:56 How the maker of Cora describes the product: 00:02:33 Our first mistake while building Cora: 00:06:31 The story of how Kieran shipped the first MVP overnight: 00:09:37 Why Dan believes software is becoming content: 00:13:44 Products with a point of view will win: 00:16:40 How Kieran approaches building a new product: 00:19:16 Best practices while using Cursor: 00:31:55 Hacking together a copy editor in Cursor live on the show: 00:41:05 The future of Cora, and the hardest challenge we face today: 00:53:58

AI is going to change science forever. Small scale studies will give way to large scale open data gathering efforts. We’ll shift from seeking broad general theories to making contextual predictions in individual cases. The traditional research paper will change fundamentally. That’s why I had Alice Albrecht on the show. Few people straddle the worlds of science and AI like she does: She holds a Ph.D. in cognitive neuroscience from Yale and is a machine learning researcher with almost a decade of experience. Her startup re:collect built an app to augment human intelligence with AI and was acqui-hired by SmartNews earlier this year. She now heads up AI product there. We get into the contours of this new paradigm in science: - Whether research papers are still the best format to “release” science in - The increasing importance of data in scientific discovery - Why AI is making N-of-1 studies imperative—when they’re normally seen as unscientific - The case for big tech to open-source their data for scientific research - The power of unbundling data and interpretations, in science and media This is a must-watch for anyone interested in how AI is changing the future of scientific research. 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: (00:00:59) Everything Alice learned about growing an AI startup: (00:04:50) Alice’s thesis about how AI can augment human intelligence: (00:09:08) Whether chat is the best way for humans to interface with AI: (00:12:47) Ideas to build an AI model that predicts OCD symptoms: (00:23:55) Why Alice thinks LLMs aren’t the right models to do predictive work: (00:37:12) How AI is broadening the horizons of science: (00:38:39) The new format in which science will be released: (00:40:14) Why AI makes N-of-1 studies more relevant: (00:45:39) The power of separating data from interpretations: (00:50:42) Links to resources mentioned in the episode:   Alice Albrecht: @AliceAlbrecht The company that recently acquired Alice’s startup: SmartNews The piece Alice wrote for Every about how AI can augment human intelligence: The Case for Cyborgs Every’s product incubations that we discuss in the context of how AI is changing media: Extendable Articles, TLDR

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