AI and I

Dan Shipper
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AI and I

Learn how the smartest people in the world are using AI to think, create, and relate. Each week I interview founders, filmmakers, writers, investors, and others about how they use AI tools like ChatGPT, Claude, and Midjourney in their work and in their lives. We screen-share through their historical chats and then experiment with AI live on the show. Join us to discover how AI is changing how we think about our world—and ourselves. For more essays, interviews, and experiments at the forefront of AI: https://every.to/chain-of-thought?sort=newest.

  1. 5 HR AGO

    How We Incubate and Launch New Products With AI - Ep. 40 with Danny Aziz, Brandon Gell

    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

    1h 1m

  2. 20 NOV

    His GPT Wrapper Has Half a Million Users—And Keeps Growing - Ep. 39 with Vicente Silveira

    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)

    1h 3m

  3. 13 NOV

    How to Win With Prompt Engineering - Ep. 38 with Jared Zoneraich

    Prompt engineering matters more than ever. But it’s evolving into something totally new:  A way for non-technical domain experts to solve complex problems with AI. I spent an hour talking to prompt wizard Jared Zoneraich, cofounder and CEO of PromptLayer, about why the death of prompt engineering is greatly exaggerated. And why the future of prompting is equipping non-technical experts with the tools to manage, deploy, and evaluate prompts quickly. We get into: His theory around why the “irreducible” nature of problems will keep prompt engineering relevant Prompt engineering best practices around prompts, evals, and datasets Why it’s important to align your prompts with the language the model speaks How to run evals when you don’t have ground truth Why he believes that the companies who have domain experts to scope out the right problems will win in the age of gen AI This is a must-watch for prompt engineers, people interested in building with AI systems, or anyone who wants to generate predictably good responses from LLMs. 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 Jared’s hot AGI take: 00:09:54 An inside look at how PromptLayer works: 00:11:49  How AI startups can build defensibility by working with domain experts: 00:15:44 Everything Jared has learned about prompt engineering: 00:25:39 Best practices for evals: 00:29:46 Jared’s take on o-1: 00:32:42 How AI is enabling custom software just for you: 00:39:07 The gnarliest prompt Jared has ever run into: 00:42:02 Who the next generation of non-technical prompt engineers are: 00:46:39 Links to resources mentioned in the episode:  Jared Zoneraich: @imjaredz PromptLayer: @promptlayer, https://www.promptlayer.com/ A couple of Steven Wolfram’s articles on ChatGPT: What Is ChatGPT Doing … and Why Does It Work?, ChatGPT Gets Its “Wolfram Superpowers”!

    1h 2m

  4. 8 NOV

    How Notion Cofounder Simon Last Builds AI for Millions of Users - Ep. 37 with Simon Last

    This episode is sponsored by Notion. I’ve been using Notion to manage my professional and personal life for almost 10 years. As a company, they pay attention to the craft and ideas underlying the software they build, and that comes through in the experience of using Notion every day. If you’re a startup, get up to 6 months of Notion Plus with unlimited AI—worth up to $6,000—for free by going to https://ntn.so/every, selecting Every in the drop-down partner list, and using the code EveryXNotion. Notion cofounder Simon Last told me everything he’s learned from integrating AI into a platform that has over 100 million users. Simon likes to keep a low profile, even though he’s the driving force behind Notion AI, one of the most widely scaled AI applications in the world. In his first-ever podcast interview, we get into: What he would build if he started Notion from scratch today with AI How to get high quality and reliable results from AI at scale The future of human creativity in a world with machines that think   This is a must-watch for anyone interested in building reliable AI products at scale. 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: 00:01:57 How AI changes the way we build the foundational elements of software: 00:02:28 Simon’s take on the impact of AI on data structures: 00:10:07 The way Simon would rebuild Notion with AI: 00:13:05 How to design good interfaces for LLMs: 00:23:39 An inside look at how Notion ships reliable AI systems at scale: 00:28:22 The tools Simon uses to code: 00:35:41 Simon’s thoughts on scaling inference compute as a new paradigm: 00:38:16 How the growing capabilities of AI will redefine human roles: 00:49:10 Simon’s AGI timeline: 00:50:28 Links to resources mentioned in the episode: Simon Last: @simonlast Notion AI: https://www.notion.so/product/ai The AI code editor Simon uses: Cursor OpenAI’s definition of AGI that Simon ascribes to: https://openai.com/charter/

    56 min

  5. 30 OCT

    How Union Square Ventures Built an AI Brain for Venture Capital - Ep. 36 with Matt Cynamon

    Union Square Ventures is building an AI operating system to support their investment team.  But it’s not what you think: It’s a constellation of AI tools that captures and synthesizes the firm's collective wisdom. It’s evolving every day, and Matt Cynamon is the mad scientist in charge Matt calls himself a “regular” at USV. In practice that means he’s responsible for running experiments with AI for the firm. As an inherently curious person with the professional obligation to tinker, he’s built a suite of tools for the firm, including:  The Librarian, a chatbot trained on around 15,000 articles from USV’s blog Portfolio Tracker, a GPT that analyzes the investments made by the firm Meeting Notes, a tool that makes it possible for team members to interact with meetings   I sat down with Matt to talk about how AI is enabling him to bring his ideas to life as a generalist, get demos of the tools listed above, and exchange notes on all the other projects he has in the works at USV. We edit actionable insights extracted by an AI from meetings at USV and prepare them to be posted on the firm’s X handle live on the show. We even try out an art project at USV’s office called The Dream Machine, which generates art from conversations. Here’s a link to the episode transcript.    This is a must-watch for anyone interested in riding the AI wave by learning how to ship useful products quickly. 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: (00:00:52) How Matt became in charge of everything AI at USV: (00:01:56) How AI empowers generalists to be creators: (00:06:22) The Librarian, a chatbot trained on everything USV has published: (00:10:41) Portfolio Tracker, an AI tool to track USV’s investments: (00:21:09) The AI projects that Matt has in the pipeline at USV: (00:27:21) Meeting Notes, USV’s AI note-taking tool: (00:34:33) Prompting AI to generate a post for USV’s X handle: (00:44:57) Why it’s important to diversify ownership over data: (01:00:20) The Dream Machine, AI that generates images from conversations: (01:03:20) Links to resources mentioned in the episode: Matt Cynamon: @mattcynamon Union Square Ventures: @usv, https://www.usv.com/  More about the AI tools at USV: https://www.usv.com/people/the-librarian/, https://www.usv.com/writing/2024/02/ai-aesthetics/  The X post generated live on the show: https://x.com/usv/status/1847354782941663523

    1h 9m

  6. 23 OCT

    Building AI That Builds Itself - Ep. 35 with Yohei Nakajima

    Yohei Nakajima leads a double life.  By day, he’s a general partner of a small venture firm, Untapped Capital.  By night, he’s one of the most prolific internet tinkerers in AI. (He also sometimes works on automating his job as a venture capitalist.) He’s the creator of BabyAGI (@babyAGI_), the first open-source autonomous agent that went viral in March 2023. Yohei has since released seven iterations of BabyAGI (each one named after a different animal), a coding agent called Ditto, a framework for building autonomous agents, and, most recently, BabyAGI 2o, a self-building autonomous agent (that follows OpenAI’s unfortunate naming convention). Even more incredible, Yohei isn’t a professional developer. His day job is as the general partner of Untapped Capital (@UntappedVC). I sat down with Yohei to talk about: What feeds Yohei’s drive to create new tools The evolution of BabyAGI into a more powerful version of itself  What Yohei learned about himself by tinkering on the internet Yohei’s personal philosophy about how the tools we build our extensions of ourselves Why founders in AI should think about their products from a modular lens, by addressing immediate problems while enabling growth in the future Yohei’s insight into a future where models will train themselves as you use them We experiment with Ditto live on the show, using the tool to build a game of Snake and a handy scheduling app. Yohei also screenshares a demo of BabyAGI 2o in action. This is a must-watch for anyone curious about autonomous agents, building cool AI tools on the internet, and the future of AI tooling. 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) BabyAGI and its evolution into a more powerful tool: (00:02:26) How better models are changing the way Yohei builds: (00:05:00) Using code building agent Ditto to build a game of Snake: (00:08:10) The ins and outs of how Ditto works: (00:13:24) How Yohei gets a lot done in little time: (00:19:21) Yohei’s personal philosophy around building AI tools: (00:21:50) How Yohei experiments with AI as a tech-forward parent: (00:33:13) Demo of Yohei’s latest release, BabyAGI 2.0: (00:39:29) Yohei’s insights on the future of AI tooling: (00:51:24) Links to resources mentioned in the episode:  Yohei Nakajima: @yoheinakajima, http://yohei.me  Untapped Capital: @UntappedVC, https://www.untapped.vc/  My first interview with Yohei, around the time he released BabyAGI: https://every.to/chain-of-thought/this-vc-is-slowly-automating-their-job  The other AI tools Yohei has created: Ditto, BabyAGI 2, BabyAGI 2o The tweet thread about AI bots being let loose on a Discord server: https://x.com/AISafetyMemes/status/1847312782049333701

    58 min

  7. 11 SEPT

    How to Use AI to Become a Learning Machine - Ep. 34 with Simon Eskildsen

    This episode is sponsored by Reflect. It’s the ultra-fast note-taking app that’s about to change the way you take notes. To boost your productivity with advanced features like custom prompts and voice transcripts, give Reflect a try by clicking on this link: https://reflect.app/?utm_source=every&utm_medium=sponsorship&utm_campaign=september2024 Simon Eskildsen is a learning machine.  I first interviewed him in 2020 about how he leveled up from an intern at Shopify to the company’s director of production engineering by reading and applying insights from hundreds of books. A lot has changed over the last four years. LLMs have made it possible to contextualize information like never before—and in this episode, I sat down with Simon to talk about how this changes the way he learns. Simon is now the cofounder and CEO of AI startup turbopuffer, which is building a search engine that makes vector search easy and affordable to run at scale. We get into: How Simon’s learning rituals have evolved over time, as the cofounder of a growing startup and a new parent  The ways Simon has integrated ChatGPT, Claude, and Notion AI to do everything from writing legal documents to maintaining his rural cabin in Quebec  The custom AI commands in productivity tool Raycast that Simon uses to learn new words and cook creative dishes Simon’s take on how language models will reshape the future of learning, especially skills like language acquisition, for the next generation  As we talk, we screenshare through his Anki setup, including the flashcard template he finds most useful, and try out his custom AI commands in Raycast to understand the meaning of two of my favorite obscure words, “lambent” and “eigengrau.” This is a must-watch for note-taking aficionados and anyone who wants to supercharge their learning with 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: 00:01:06 How entrepreneurship and parenthood changed Simon’s learning rituals: 00:02:51 How Simon accelerates his learning by using LLMs to find associations: 00:12:59 Simon’s Anki setup and the flashcard template he swears by: 00:18:24 The custom AI commands that Simon uses most often: 00:26:02 How Simon uses LLMs for DIY home projects: 00:37:45 Leveraging LLMs as intuitive translators: 00:40:48 Simon’s take on how AI is reshaping the future of learning: 00:51:38 How to use Notion AI to write: 00:59:10 The AI tools that Simon uses to write, read, and code: 01:08:53 Links to resources mentioned in the episode:  Simon Eskildsen: @Sirupsen Simon’s startup, turbopuffer: turberpuffer.com, @turbopuffer My first interview with Simon in 2020: https://every.to/superorganizers/how-to-build-a-learning-machine-299655  The productivity tool through which Simon uses LLMs, Raycast: https://www.raycast.com/  The other AI tools that Simon is experimenting with: voice-to-text tool superwhisper, copilot for developers Supermaven, code editor Cursor

    1h 14m

  8. 4 SEPT

    How to Supercharge Your Writing With AI Tools - Ep. 33 with Evan Armstrong

    How do two professional writers use AI to do the best work of their lives? In today’s show, Every’s lead writer Evan Armstrong and I conduct an expert workshop on how we use ChatGPT, Claude, AI-powered word processor Lex, and the prompt builder that Every launched, Spiral, to feed our obsession with words—and help us write for more than 78,000 readers every day. We talk about how AI helps us: Understand our taste—understanding what good is Pick a topic—knowing what to write about Craft our words—everything from sketching out an outline to writing and editing Build an audience—learn how to reach people We get into: How I used Claude and ChatGPT to help me identify the kind of writing I like—and why that’s critically important for mastery  How Evan uses ChatGPT to explore his taste across books, movies, and paintings  The way I use Claude Projects to help me turn a vast amount of research into a clear thesis statement for major projects The routine Evan swears by to publish two pieces every week How Evan and I use Lex to push through writer’s block and catch common writing mistakes like passive voice My workflow inside Claude to craft emphatic metaphors How we use Spiral to write viral tweets  Evan is the lead writer at Every who writes the column Napkin Math twice a week. He’s smart, funny, curious—and has the rare combination of business acumen, way with words, and crazy required to be a professional writer. This is a must-watch for aspiring writers, or anyone whose job involves writing more than six sentences in a row. 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: 00:01:04 How to develop good taste: 00:04:28 Dan uses Claude to articulate his taste in books: 00:13:34 How to use LLMs to explore art cross different mediums: 00:21:06 The way Evan chooses his next essay topic: 00:33:45 Go from research notes to clear thesis in Claude Projects: 00:38:20 How Evan uses AI to master new topics quickly: 00:46:51 Evan leverages AI to power through writer’s block: 00:59:21 How to use Claude to find good metaphors: 01:04:28 The role of AI in building an audience: 01:11:44 Links to resources mentioned in the episode:  Evan Armstrong: @itsurboyevan The column Evan writes at Every: Napkin Math Evan’s upcoming course about how to write with AI: https://www.writewithai.xyz/  The piece Dan wrote about using LLMs to articulate his taste: "What I Do When I Can’t Sleep" Dan’s article about admitting that he wants to be a writer: "Admitting What Is Obvious"

    1h 35m
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About

Learn how the smartest people in the world are using AI to think, create, and relate. Each week I interview founders, filmmakers, writers, investors, and others about how they use AI tools like ChatGPT, Claude, and Midjourney in their work and in their lives. We screen-share through their historical chats and then experiment with AI live on the show. Join us to discover how AI is changing how we think about our world—and ourselves. For more essays, interviews, and experiments at the forefront of AI: https://every.to/chain-of-thought?sort=newest.

Information

  • Creator
    Dan Shipper
  • Years Active
    2023 - 2024
  • Episodes
    41
  • Rating
    Clean
  • Copyright
    © Dan Shipper
  • Show Website
    AI and I

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