The Every Podcast

Claire Vo built ChatPRD—an on-demand chief product officer powered by AI. It’s now used by over 10,000 product managers and is pulling in six figures in revenue. 
The best part? 
Claire has a demanding day job as the CPO at LaunchDarkly. So she built all of ChatPRD herself—over the weekend—with AI. 
I sat down with Claire to talk about how ChatPRD works, how she built it as a side hustle using AI, and all of the ways she’s using AI tools to accelerate her work and life. 
We get into:

• How she used AI to build ChatPRD over Thanksgiving break
• The part of product management that Claire thinks AI will disrupt
• Why the PMs of tomorrow will be “proto-managers” who create prototypes rather than just specs
• How junior PMs can use AI to upskill faster
• The ways in which ChatPRD is baked into her own workflow
• How building ChatPRD is making Claire a better PM
• How Claire uses AI as a tech-forward parent

This is a must-watch for anyone interested in turning their side hustle into a thriving business or who works in product. 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. 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

Links to resources mentioned in the episode:

• Claire Vo: ⁠https://x.com/clairevo⁠
• ChatPRD: https://www.chatprd.ai/; ⁠https://x.com/chatprd⁠; ⁠https://www.linkedin.com/company/chatprd/⁠; ⁠https://www.youtube.com/@ChatPRD ⁠
• Some of the AI tools that Claire used to build ChatPRD: ⁠http://Clerk.dev⁠; ⁠https://tiptap.dev/ ⁠
• Greeking Out, the Greek mythology podcast that Claire’s son enjoys: ⁠https://www.nationalgeographic.com/podcasts/greeking-out⁠

An interview with best-selling sci-fi novelist Robin Sloan

One of my favorite fiction writers, New York Times best-selling author Robin Sloan, just wrote the first novel I’ve seen that’s inspired by LLMs.

The book is called Moonbound, and Robin originally wanted to write it with language models. He tried doing this in 2016 with a rudimentary model he built himself, and more recently with commercially available LLMs. Both times Robin found himself unsatisfied with the creative output generated by the models. AI couldn’t quite generate the fiction he was looking for—the kind that pushes the boundaries of literature.

He did, however, find himself fascinated by the inner workings of LLMs

Robin was particularly interested in how LLMs map language into math—the notion that each letter is represented by a unique series of numbers, allowing the model to understand human language in a computational way. He thinks LLMs are language personified, given its first heady dose of autonomy. 

Robin’s body of work reflects his deep understanding of technology, language, and storytelling. He’s the author of the novels Mr. Penumbra’s 24-hour Bookstore and Sourdough, and has also written for publications like the New York Times, the Atlantic, and MIT Technology Review. Before going full-time on fiction writing, he worked at Twitter and in traditional media institutions. 

In Moonbound, Robin puts LLMs into perspective as part of a broader human story. I sat down with Robin to unpack his fascination with LLMs, their nearly sentient nature, and what they reveal about language and our own selves. It was a wide-ranging discussion about technology, philosophy, ethics, and biology—and I came away more excited than ever about the possibilities that the future holds.

This is a must-watch for science-fiction enthusiasts, and anyone interested in the deep philosophical questions raised by LLMs and the way they function. 

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. 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 

Links to resources mentioned in the episode:

Robin Sloan: https://www.robinsloan.com/ 

Robin’s books: Mr. Penumbra's 24-Hour Bookstore, Sourdough, Moonbound

Dan’s first interview with Robin four years ago: https://every.to/superorganizers/tasting-notes-with-robin-sloan-25629085 

Anthropic AI’s paper about how concepts are represented inside LLMs: https://www.anthropic.com/news/mapping-mind-language-model 

Dan’s interview with Notion engineer Linus Lee: https://www.youtube.com/watch?v=OeKEXnNP2yA 

Big Biology, the podcast that Robin enjoys listening to: https://www.bigbiology.org/ 

We use it to find bestselling author Steven Berlin Johnson’s next project.

I sat down with bestselling author Steven Johnson to see if we could come up with a concept for his next project—using AI. The results were amazing.

We loaded 200,000 words of NASA transcripts and all of Steven’s reading notes since 1999 into NotebookLM, Google’s personalized research assistant. We wanted to see if it could help us explore the Apollo 1 fire and find relevant and surprising ideas from history that could work to explain it.

• NotebookLM condensed disparate 200,000 words of NASA transcripts into readable formats like FAQs and chronological timelines.
• It sifted through the material to identify the catalyst for the fire.
• The model even went through Steven’s Readwise notes to find a relevant, and unexpected, story from history that we could use to explain the history and origins of the fire

If you’re a fan of Steven Johnson’s work or you’re interested in AI as a creative tool, you need to watch this episode. 

All of this happens as a live exploration of NotebookLM, and it’s a seriously wild ride. 

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. It’s usually only for paying subscribers, but you can get it here for free.

To hear more from Dan Shipper:
⁠Subscribe to Every⁠
Follow him on ⁠X⁠

Links to resources mentioned in the episode:
⁠Follow Steven Johnson
⁠⁠NotebookLM⁠
Steven’s newsletter, ⁠Adjacent Possible⁠
Steven’s latest book about the rise of the modern detective: ⁠The Infernal Machine⁠
A few of Steven’s other books: ⁠
How We Got to Now
⁠⁠Where Good Ideas Come From
⁠⁠The Ghost Map
⁠⁠Emergence
⁠⁠The Invention of Air

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. 

New York Times journalist Kevin Roose has 18 new friends—none of whom are human. 

Kevin formed a collection of “friends”—AI personas with distinct personalities and backstories—using apps like Kindroid and Nomi. Among these were fitness guru Jared, San Francisco-based therapist Peter, and pragmatic trial lawyer Anna. He talked to them every day for a month, sharing personal stories, seeking advice, and even asking for “fit” checks. And this wasn’t Kevin’s first unusual interaction with AI characters. A year ago, he was the infamous target of Bing’s chatbot Sydney’s romantic overtures.

I don’t think anyone has studied AI companionship as deeply as Kevin, and in this episode, I sat down with him to learn more about his experience.

Kevin is a tech columnist at the New York Times and cohost of the Hard Fork podcast. He’s also the author of three books, most recently Futureproof: 9 Rules for Humans in the Age of Automation, which is about how humans can be happy in a world designed for machines. During our conversation, we also talk about how Kevin is using AI in his work and life every day.

This is a must-watch for anyone curious about how AI is changing the way we form relationships.

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. 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 

Links to resources mentioned in the episode:

Kevin Roose: @kevinroose

Hardfork, the podcast that Kevin cohosts: https://www.nytimes.com/column/hard-fork 

Kevin’s latest book about being human in a world designed for machines: https://www.kevinroose.com/futureproof 

Kevin’s piece in the New York Times about his experience making AI friends: https://www.nytimes.com/2024/05/09/technology/meet-my-ai-friends.html?unlocked_article_code=1.qk0.9dZN.6XiiP3RjRZxv&smid=nytcore-ios-share&referringSource=articleShare&sgrp=c-cb 

Two of the apps that Kevin used to create AI companions: https://landing.kindroid.ai/; https://nomi.ai/ 

Dan’s piece that explains why AI writing will feel real through psychologist D.W. Winnicott’s theory: https://every.to/chain-of-thought/will-you-read-writing-from-an-ai   

Every’s piece that explores AI companion app Replika: https://every.to/cybernaut/artificial-intimacy 

Nick Dobos, maker of the #1 programming GPT, on prompt-gramming with AI

You can go from having an idea to deploying a live website in minutes.

All you have to do is prompt Grimoire, the number-one custom GPT for programming, with an image or even a single word about your idea. As you watch the LLM process your request, Grimoire works with a web host on the backend, and just minutes later, your website will be live on the internet.

Grimoire, which has facilitated over 1 million chats, can help you with a lot more than just making websites: It includes a comprehensive guide to learning how to code, from basic concepts to advanced instruction, and serves as a tool for programmers to resolve their questions in real time.

The creator of Grimoire is Nick Dobos, who was an iOS developer at Twitter until Musk bought the company and laid off a majority of its staff. With plenty of free time suddenly on his hands, Nick started experimenting with ChatGPT, and ended up building Grimoire. He’s since emerged as one of the foremost experts in the world on building successful custom GPTs and coding with ChatGPT. 

I think Grimoire is a platform to examine the possibilities that “prompt-gramming”—an emerging way of coding by prompting AI—can enable. I sat down with Nick to explore what this means about the future of programming, the best way to use the coding assistant, and the role AI plays in his life beyond coding. As we talk, Nick uses Grimoire to build a website about coffee and generate a QR code from its URL live on the show.

This is a must-watch for coders, creative people, and anyone curious about how AI is changing the way we interact with computers.

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. 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 

Links to resources mentioned in the episode:

Nick Dobos: @NickADobos

Grimoire: https://chat.openai.com/g/g-n7Rs0IK86-grimoire 

Nick’s website for his experiments with AI: https://mindgoblinstudios.com/ 

AI-first code editor Cursor: https://cursor.sh/ 

Open Interpreter: https://www.openinterpreter.com/ 

Lisa Feldman Barrett’s book: How Emotions Are Made

Demo Hume, the empathetic AI voice: https://demo.hume.ai/ 

The future of AI technology isn’t just faster or more powerful—it’s empathetic. My guest for this episode, Alan Cowen, is leading the charge with the first-ever emotionally intelligent AI.

Alan is the co-founder and CEO of Hume, an AI research laboratory developing models trained to identify and measure expressions of emotion from voice inflections and facial expressions. The best part? Once it understands these emotions, the AI is designed to interact with users in a way that optimizes for human well-being and leaves them with a positive emotional experience.  

Previously, Alan—who has a Ph.D. in computational psychology—helped set up Google’s research into affective computing, a field focused on developing technologies that can understand and respond to human emotions. He operates at the intersection of AI and psychology, and I sat down with him to understand the inner workings of Hume’s models. Alan walks me through the shortcomings of traditional theories of emotional science and breaks down how Hume is addressing these challenges. While talking about the potential applications of the models, we also discuss the tricky ethical concerns that come with creating an AI that can interpret human emotions.

This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions.

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. 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 

Links to resources mentioned in the episode:

Alan Cowen: @AlanCowen

Hume: @hume_AI; hume.ai

If you want to demo Hume: demo.hume.ai

The nonprofit associated with Hume: Hume Initiative

Lisa Feldman Barrett’s book: How Emotions Are Made

The serial based on Paul Ekman’s theory of emotion: Lie to Me

Learn how to use philosophy to run your business more effectively

Reid Hoffman thinks a masters in philosophy will help you run your business better than an MBA.

Reid is the cofounder of LinkedIn, a partner at venture capital firm Greylock Partners, the host of the Masters of Scale podcast, and a prolific author. But before he did any of these things, Reid studied philosophy—and by helping him understand how to think, it made him a better entrepreneur.

A good student of philosophy rigorously engages with questions about truth, human nature, and the meaning of life, and, over time, learns how to think clearly about the big picture. This is a powerful tool for founders faced with existential questions about their product, consumers, and competitors, and enables them to respond with well-reasoned answers and enviable clarity of thought.

This show is usually about the actionable ways in which people have incorporated ChatGPT into their lives, but in this episode, I sat down with Reid to tackle a deeper question: How is AI changing what it means to be human? How might it change the way we see ourselves and the world around us?

This episode is a must-watch for anyone curious about some of the bigger questions prompted by the rapid development of AI.

Thanks again to our sponsor CommandBar, the first AI user assistance platform, for helping make this video possible. ⁠https://www.commandbar.com/copilot/⁠

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. 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 

Links to resources mentioned in the episode:

Reid Hoffman: @reidhoffman

The podcast Reid hosts: Masters of Scale

Reid’s book: Impromptu

The book Reid recommends if you want to be more philosophically inclined: Gödel, Escher, Bach

Reid’s article in the Atlantic: "Technology Makes Us More Human"

The book about why psychology literature is wrong: The WEIRDest People in the World by Joseph Henrich

The book about how culture is driving human evolution: The Secrets of Our Success by Joseph Henrich

Seth-Stephens Davidowitz wrote a book in 30 days—and he did it with ChatGPT.

Seth is a data scientist, economist, and author who challenged himself to write a book—Who Makes the NBA?—in less than 1 month after realizing how fast he could work by using ChatGPT plugin Advanced Data Analysis. 

But along the way he discovered something else: Writing with AI wasn’t just faster, it was also way more fun. 

Seth outsourced the boring parts of data analysis—like cleaning data, merging files, and looking up code snippets—to AI. This left him to focus on what he loves: thinking up questions to ask the dataset.

In a world where AI can answer any question humans know the answer to, asking the right questions is becoming increasingly important—a skill Seth isn’t just really good at, but also finds joy in. 

In this episode, Seth walks me through how he used AI to analyze data and write a book in 30 days. We get into:

- How to create and edit complex charts with AI in seconds

- Using ChatGPT to brainstorm creative ideas 

- How AI is redefining who can be an artist 

- Why ChatGPT is an excellent tool to get a quick ballpark estimate

- Developing a sixth sense about when ChatGPT is wrong

- The power of AI instantly answering hard questions that would normally take months of research 

We also use ChatGPT to analyze a dataset of Olympic athletes live on the show—in pursuit of finding out which sport I’m best suited for!

This episode is a must-watch for anyone curious about data science and how AI is transforming the future of creativity (or who is just a fan of the NBA).

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. It’s usually only for paying subscribers, but you can get it ⁠here for free⁠. 

To hear more from Dan Shipper:

• Subscribe to ⁠Every ⁠
• Follow him on ⁠X⁠

Links to resources mentioned in the episode:

Seth Stephens-Davidowitz: ⁠https://twitter.com/SethS_D⁠ ⁠http://sethsd.com⁠

Seth’s books: ⁠Who Makes the NBA?⁠ , ⁠Everybody Lies ⁠ and ⁠Don’t Trust Your Gut 

Nicholas Thorne is building Squarespace for the AI age. It’s called Audos, and it’s an AI chatbot to help any entrepreneur go from idea to:
- Pitch deck
- Working website
- Custom GPT
- User interviews with real customers
All in just a few minutes. And he did it using ChatGPTapp. It’s AI all the way down—and it’s one of the most impressive AI businesses I’ve ever seen.
Nicholas is a general partner at Prehype, an incubator that launched Barkbox and Ro Health. It’s also where I started Every, so it was great to come full circle.
Nicholas’s job at Prehype is to launch new companies. He’s taken everything he’s learned running an incubator and used it to help entrepreneurs start businesses at scale—with AI.
As we talk, Nicholas walks me through the interactions of Audos’s chatbot with a user live on the show.
Nicholas tells me that he used ChatGPT to prototype most of Audos’s features—despite being non-technical himself. He shares exactly how he did this by showing me how he’s using AI to create a new feature for the product.
We get into:
- Ways AI can make you a more effective founder
- How to use ChatGPT to build your prototype
- Strategies to refine problem statements with AI
- Using GPTs to gather and synthesize customer feedback
This episode is a must-watch for anyone who has ever toyed with the idea of starting a business—and wants to do it 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. It’s usually only for paying subscribers, but you can get it here for free: https://every.ck.page/ultimate-guide-to-prompting-chatgpt

To hear more from Dan Shipper:
Subscribe to Every: ⁠https://every.to/subscribe⁠
Follow him on X: ⁠https://twitter.com/danshipper⁠

Timestamps:
00:00:00 - Teaser
00:00:48 - Introduction
00:12:10 - How AI can make you a more effective founder
00:17:03 - Live demo of Audos!
00:24:07 - Why Nicholas built an AI tool to enable entrepreneurs
00:25:35 - How Audos puts you in “edit mode” instead of “create mode”
00:28:12 - Tools to gather customer feedback, generated by Audos
00:32:58 - How Audos actually works
00:35:07 - Nicholas uses ChatGPT to prototype a new feature
00:42:37 - How to establish checks and balances while using ChatGPT
00:57:20 - AI as a force for pushing entrepreneurship to new heights

Links to resources mentioned in the episode:
Nicholas Thorne: ⁠@thorneny⁠; ⁠[email protected]⁠
Audos: ⁠https://www.audos.com/⁠
Nicholas’s book, Me, My Customer, and AI, is slated to publish next month. Follow him on X for updates: https://mmcai.super.site/