The Every Podcast

OCD treatment changed my life—but it took me a decade of chasing down wrong answers to be diagnosed. 

In the rush to create scalable treatments, disorders like depression and OCD are squeezed into diagnostic checklists—from which the complexity of the human mind invariably leaks out. The field of psychiatry is broken, and I spoke to someone on the inside about how AI can help fix it .

⁠Awais Aftab⁠ has been questioning psychiatry’s rigid categories from inside the field. He’s a clinical assistant professor at ⁠Case Western Reserve University⁠, editor of ⁠Conversations in Critical Psychiatry⁠—an Oxford University Press volume that tackles philosophical and critical perspectives in psychiatry—and author of the Substack newsletter ⁠Psychiatry at the Margins⁠. We get into how AI is transforming psychiatry by embracing the complexity of human minds instead of flattening 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 

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Timestamps:

1. Introduction: 00:01:20
2. The case Awais makes for pluralistic thinking in psychiatry: 00:03:38
3. A pragmatic approach to mental healthcare: 00:15:30
4. Awais’s take on why my OCD diagnosis took 10 years: 00:19:04
5. Why psychiatry is stuck where machine learning was decades ago: 00:24:19
6. Why psychiatry’s focus should shift from explanations to predictions: 00:31:05
7. How Awais thinks AI is already changing the psychiatric profession: 00:39:19

Links to resources mentioned in the episode:

• Awais Aftab: @awaisaftab, ⁠awais aftab⁠ 
• Awais’s Substack: ⁠Psychiatry at the Margins⁠
• The book Awais edited: ⁠Conversations in Critical Psychiatry⁠

GitHub Copilot has 15 million users—more than Cursor and Windsurf combined. So why does it feel like they're losing the AI coding race?

Last week at Microsoft Build, I interviewed the CEO of GitHub Thomas Dohmke to find out. 

I wanted to know: Is their huge existing user base a blessing or a curse? And will their latest launch—an autonomous coding agent built into GitHub—let them retake the lead? Watch this episode of AI & I to find out

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 

Sponsor:
Attio: Go to⁠⁠⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠⁠⁠ and get 15% off your first year on your AI-powered CRM.

Timestamps:

00:00:38 - Introduction  

00:07:40 - Copilot’s place in the AI coding agent race  

00:10:42 - Inside the product decisions behind Copilot’s new agent  

00:16:18 - How Dohmke thinks about shaping Copilot’s personality  

00:20:29 - How GitHub supports both AI-native developers and legacy enterprise users  

00:26:57 - Dohmke’s predictions for the future of software development  

I interviewed Microsoft CTO Kevin Scott about the future of agents and software engineering for another special edition of AI & I. 

With 41 years of programming behind him, Kevin has lived through nearly every big shift in modern software development. Here’s his clear-eyed take on what’s changing with AI, and how we can navigate what’s next:

• The real breakthrough for the agentic web is better plumbing. Kevin thinks agents won’t be useful until they can take action on your behalf by using tools and fetching data. To do this, agents need access across your systems—and Microsoft’s answer is adopting Model Context Protocol, or “MCP,” that allows an agent to access tools and fresh data beyond its knowledge base, as their standard protocol for agents to move through contexts and get things done.
• How the agentic web echoes the early internet. Just as protocols like HTTP and HTML gave the web a shared language, Kevin believes the  agentic web needs its own infrastructure—the first glimpses of this include MCP (the HTTP of agents) and NLWeb, Microsoft’s push to make websites legible to agents (similar to what HTML did for browsers).
• Open ecosystems can coexist with strong security systems. Kevin argues that the “tradeoff” between ecosystems that allow “permissionless” innovation and robust security is a false dichotomy. With AI agents that understand your personal risk preferences—and know your communication habits across email, text, and other channels—they could detect when something suspicious is happening and act on your behalf. 
• The craftsman’s dilemma in the age of agents. Kevin is a lifelong maker—of software, ceramics, even handmade bags—and he cares deeply about how things are made. Because this can feel at odds with coding with AI agents, Kevin’s approach is to notice where the process matters most to him, and where it's okay to optimize for outcomes. After four decades of seeing breakthrough technologies, his advice is simple: be curious, try stuff, and use it if it works for you.
• The future of software engineering agents is plural. Kevin believes the future of software engineering agents will be diverse because developers who enjoy the freedom of playing with different tools is one of the most consistent patterns he’s seen in his decades in tech. What will drive this diversity, he says, is builders who deeply understand specific problems and tailor agents to solve them exceptionally well.
• How agentic workflows will evolve. Kevin sees a shift from short back-and-forth interactions with agents to longer, async feedback loops. As the agentic web matures and model reasoning improves, people will start handing off bigger, more ambitious tasks and letting agents run with them.

Timestamps:

1. Introduction: 00:01:44
2. The race to close the “capability overhang”: 00:02:49
3. How agents will evolve into practical, useful tools: 00:04:31
4. The role Kevin sees Microsoft playing in the agent ecosystem: 00:06:48
5. How robust security measures can coexist with open ecosystems: 00:12:05
6. Kevin's philosophy on being a craftsman in the age of agents: 00:15:39
7. How the landscape of software development agents will evolve: 00:20:52
8. The future of agentic workflows: 00:25:33

OpenAI just launched Codex, a brand-new coding agent that can build features and fix bugs autonomously. We’ve been testing it at Every for a few days, and I’m impressed.

I invited Alexander Embiricos, a member of the OpenAI product staff responsible for Codex, to demo the agent live on a special edition of AI & I. We talk through:

- What Codex is and how it works. Codex’s UI allows developers to see the list of tasks the agent is working on, how many lines were changed for each, and the status of the PR. It’s built for the senior software engineer who wants to delegate and review tasks efficiently.
- How OpenAI is thinking about agents. Codex is one piece of a unified super-assistant OpenAI wants to eventually build—an agent that helps users easily get things done by selecting the right tools for them behind the scenes. 
- Why an “abundance mindset” is best for interacting with agents. Codex is designed to allow users to delegate many tasks at once without getting caught up in the details. This lets you point an abundance of agents at a specific task, like a difficult bug—it’s worth it even if only one of them succeeds.
- OpenAI’s vision for the future of programming. In the future developers will probably spend less time writing routine code and more time guiding agents, reviewing their work, and making strategy decisions. Programming will become more social, letting teams easily delegate multiple tasks at once, allowing people to focus on ideas and collaboration instead of routine coding.

Timestamps:

1. Introduction: 00:00:52
2. The product decisions behind Codex’s interface: 00:01:40
3. How Codex works under the hood: 00:06:20
4. Why you need an abundance mindset to work well with agents: 00:14:06
5. Setting Codex to work on a real task in “Ask” mode: 00:16:28
6. How OpenAI is thinking about designing agents: 00:18:54
7. The future of programming is social: 00:31:16
8. Reviewing Codex’s work live: 00:37:21
9. How the landscape of agents will evolve: 00:39:41

Will England just pivoted his $10B AUM hedge fund to go all in on AI with a firm-wide email: “I wrote this email using ChatGPT—you should too. As a hedge fund, we should be ashamed to leave money on the table by ignoring AI.”

It’s working: 75% of his 400-person team are using ChatGPT daily—and Walleye is well on its way to transforming into an AI-first juggernaut. They record every meeting, use LLMs to ingest and analyze earnings reports, and are building “The Borg”—a firmwide intelligence layer.

What’s surprising? Will isn’t some AI hype man: He’s the CEO, CIO, and managing partner of Walleye Capital, a multi-strategy hedge fund competing with firms like Citadel, Millenium, and Point72. He’s Princeton and Oxford educated, but he’s based in Minnesota, doesn’t have an X account, and rarely gives interviews.

In my experience, teams go as their CEO goes—and Will is the best example of a CEO going all in on AI that I’ve seen. "It would be irresponsible not to go after AI with maximum discipline and intensity," Will told me—and in this episode he lays out his exact playbook for doing it.

We get into:

• Why AI is essential operating leverage. At Walleye, using AI is treated like using email or Excel. Ignoring it means getting left behind—in an industry where information = money, every edge counts. England makes this not optional for anyone, backed by internal leaderboards and cash incentives.
• How Will uses AI for journaling and decision-making. Will journals every day using ChatGPT, which helps him with everything from decision-making at work to reflecting on his family life to tracking his workouts. 
• How Will pivoted his billion dollar firm. Will’s commitment to AI isn’t theoretical—he announced AI as the new standard for work at Walleye, and made avoiding it unacceptable. 
• How to lead during times of technological change. Will leads with an ethic of personal responsibility: "If we get disrupted by AI, that's on me.”
• Why students of history do better at handling the future. Will sees today like the 1860s–1910s era—when the Industrial Revolution introduced factories and railroads and the skills and roles needed inside of companies transformed quickly.
• How Will uses AI to write faster. Will uses ChatGPT to help him draft emails or memos that would have taken hours in 15 minutes. He bullets out of his thoughts and then uses LLMs to turn that into polished prose. Having AI handle the linguistic syntax gives him more time for conceptual thinking.

This is a must-watch for anyone who wants to lead a team through change with clarity and conviction.  

Sponsor:

Attio: Go to⁠⁠⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠⁠⁠ and get 15% off your first year on your AI-powered CRM.

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:

1. Introduction: 00:00:51
2. What pushed Will to go all in on AI: 00:03:25
3. Inside the ‘AI-first’ memo Will shared at Walleye: 00:14:08
4. Why you shouldn’t be afraid of using AI for work: 00:15:56
5. How Will uses LLMs to sharpen his thinking: 00:31:01
6. Walleye’s approach to using AI to reduce risk: 00:35:32
7. What history can teach us about leading through change: 00:39:10
8. Will’s first principles to making better decisions: 00:56:45
9. Why Will journals everyday—and how AI makes it easier: 00:58:58 

Links to resources mentioned in the episode:

• Will England: ⁠https://walleyecapital.com/bio/will-england⁠ 
• Walleye Capital: ⁠https://walleyecapital.com/⁠ 
• Work with Every’s consulting team: ⁠https://every.to/consulting⁠  
• Everything we’ve learned from consulting with clients like Walleye: ⁠"How We Built a 7-figure AI Consulting Business in Less Than a Year"⁠

After two Jhana meditation retreats Nadia Asparouhova could silence her mind, change her emotional state at will, and even intentionally slip out of consciousness. It challenged the idea that our minds are not under our control—and made her wonder if we’re more like AI than we realize. 

Nadia is a writer and researcher of technology and culture. She published Working in Public, a book about the evolution of open-source development, with Stripe Press. Her latest book, Antimemetics, is about why some ideas don’t go viral even though they’re powerful. 

I had her on the show to talk about her experience with Jhana meditation and how it reshaped the way she thinks about being human in the age of AI. We get into:

• Jhana as a means to nurture profound joy and calm. Unlike many meditation practices that emphasize passive observation, Jhana is goal-oriented—practitioners proactively cultivate states of concentrated bliss. Apart from helping her regulate her emotions, it prompted Nadia to reexamine deep questions of our human existence. 
• Self-talk is not essential as it seems. Nadia describes how advanced meditation quieted her inner voice—challenging the idea that self-talk is core to being human.
• How years of cultural evolution have shaped our sense of self. According to Nadia, our modern conception of “self”  isn’t as timeless as we assume. She draws on psychologist Julian Jaynes’s theory that our inner dialogue—what we often equate with consciousness—only emerged in humans a few thousand years ago; a provocation to reconsider the benchmarks we use to assess the intelligence or sentience of LLMs.
• What it is like to experience a “cessation.” On her last meditation retreat, Nadia experiences a cessation where your consciousness abruptly winks out—like suddenly flipping a switch. Nadia described it as slipping into nothingness, then returning with the jarring realization that even your sense of self can vanish and reappear.
• Why she likes the unknowability of AI. The mechanics of exactly how LLMs predict their next token remain a mystery. Driven by thousands of subtle, context-dependent correlations, they’re too complex to distill into a simple explanation. Nadia finds joy in the unknowability of it all, seeing the ambiguity as an invitation to explore. 
• How she uses AI as a writing partner. Nadia believes the trope of the solitary, brooding writer is beginning to shift with the rise of LLMs. For her, ChatGPT has made writing feel less isolating. She turns to it at both ends of the process: to help make sense of early ideas, and later, to sharpen phrasing and land on just the right words.

This is a must-watch for anyone interested in consciousness, technology, and what it means to be human in an AI world.

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:

1. Introduction: 00:01:15
2. The beginning of Nadia’s journey with Jhana: 00:02:34
3. How Jhana is different from other meditation practices: 00:05:51 
4. Jhana reframed the way Nadia thinks about being human: 00:09:52
5. How Nadia integrates her experience with Jhana into her life: 00:14:16
6. Nadia describes her experience of the final stage of Jhana: 00:16:44
7. Why our modern sense of self isn’t as timeless as you might assume: 00:19:11
8. How new technologies can be a mirror to ourselves: 00:23:53
9. Nadia embraces the feeling of not knowing how AI precisely works: 00:33:55
10. How Nadia uses ChatGPT to make writing less isolating: 00:38:03

Links mentioned:

• Nadia Asparouhova: ⁠https://nadia.xyz/⁠ 
• Her deep dive on Jhana meditation: ⁠https://nadia.xyz/jhanas⁠ 
• Nadia’s book: ⁠Working in Public⁠, ⁠Antimemetics⁠

Sarah Tavel thinks it's criminal that ChatGPT isn’t inherently social.

There’s no easy way to discover great prompts or share the ones that worked. As a venture partner at Benchmark, Sarah believes that the next wave of consumer AI will be built on this missing social layer—by product-driven founders who understand people, not just models. 

Sarah has seen this shift before. As one of Pinterest’s first product managers, she saw the company grow from a niche consumer tool to a beloved global community. On this episode of Every's podcast AI & I, we talk about how she’s applying the lessons she learned to AI—and what it takes to build a breakout consumer AI app today. 

We get into:

• Why product geniuses win as new tech matures. In the early days of a new technology, companies win by wrangling raw innovation into something usable. But as the infrastructure matures, Sarah says the edge shifts to product thinkers—founders who turn new capabilities into delightful user experiences.
• The future of prompting is social. When Sarah had to dig through Reddit to find a prompt to help her interpret her blood test results, she saw a gap: The best prompt creators are invisible. Sarah bets that a social AI product that makes them discoverable and followable would gain traction.
• Sarah’s method to spot exceptional founders. Sarah backs founders for whom building a company feels like a calling—or even an affliction. These are people who have fallen in love with the process and are obsessed with learning how to grow alongside their companies.
• How to tell if your startup really has network effects. Founders raising money love to say that their business has “network effects.” Sarah has learned to look for early signs they’re real—like traction in a small, white-hot segment of the market. If there’s no evidence the flywheel is already starting to spin, it’s probably not a network effect.
• How LLMs change the way the best VCs invest. Sarah thinks the future of venture will be shaped by how well VCs can turn the decisions they make into training data. After every pitch, she logs what she liked, what she didn’t, the deal terms, and her reasoning. Over time, she’s building a dataset of her own judgment—one an LLM could help her use to pressure-test decisions and avoid past mistakes.

This is a must-watch for if you’re building a consumer AI product and want to see ahead of the curve.

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 

Sponsor:

Attio: Go to⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠ and get 15% off your first year on your AI-powered CRM.

Timestamps:

1. Introduction: 00:01:10
2. Why the future of consumer AI belongs to founders with product intuition: 00:02:26
3. What Sarah sees as ChatGPT’s biggest weakness: 00:11:09
4. How Sarah would design a consumer AI app with social DNA: 00:18:45
5. The kind of founders Sarah invests in: 00:25:04
6. How to know if your startup’s network-effects are real: 00:29:26
7. What’s catching Sarah’s eye beyond AI: 00:36:33
8. How AI will change the way top venture capitalists invest: 00:41:35

Links to resources mentioned in the episode:

• Sarah Tavel: @sarahtavel
• Sarah’s substack: ⁠https://www.sarahtavel.com/⁠ 
• Eugene Wei’s essay about Status-as-a-Service: ⁠https://www.eugenewei.com/blog/2019/2/19/status-as-a-service⁠ 
• The book Sarah talks about in the context of founders who become CEOs in pursuit of status: ⁠The Five Temptations of a CEO⁠

Kevin Kelly has spent more time thinking about the future than almost anyone else.

From VR in the 1980s to the blockchain in the 2000s—and now generative AI—Kevin has spent a lifetime journeying to the frontiers of technology, only to return with rich stories about what’s next.

Today, as Wired's senior maverick, his project for 2025 is to outline what the next century looks like in a world shaped by new technologies like AI and genetic engineering. 

He’s a personal hero of mine—not to mention a fellow Annie Dillard fan—and it was a privilege to have him on the show. We get into:

• How you can predict the future. According to Kevin, the draw of new frontiers—from the first edition of Burning Man and remote corners of Asia, to the early days of the internet and AI—isn’t staying at the edge forever; it's returning with a story to tell.
• Why history is so important to help you understand the future To stay grounded while exploring what’s new, Kevin balances the thrill of the future with the wisdom of the past. He pairs AI research with reading about history, and playing with an AI tool by retreating to his workshop to make something with his hands.
• From 1,000 true fans to an audience of one. Rather than creating for an audience, Kevin has been using LLMs to explore his own imagination. After realizing that da Vinci, Martin Luther, and Columbus were alive at the same time, he asked ChatGPT to imagine them snowed in at a hotel together, and the prompt spiraled into an epic saga, co-written with AI. But he has no plans to publish it because the joy was in creating something just for himself.
• What the history of electricity can teach us about AI. Kevin draws a parallel between AI and the early days of electricity. We could produce electric sparks long before we understood the forces that created them, and now we’re building intelligent machines without really understanding what intelligence is.
• Why Kevin sees intelligence as a mosaic—not a monolith. Kevin believes intelligence isn’t a single force, but a compound of many cognitive elements. He draws from Marvin Minsky’s “society of mind”—the theory that the mind is made up of smaller agents working together—and sees echoes of this in the Mixture of Experts architecture used in some models today.
• Your competitive advantage is being yourself. Don’t aim to be the best—aim to be the only. Kevin realized that the stories no one else at Wired wanted to write were often the ones he was suited for, and trusting that instinct led to some of his best work.

This is a must-watch for anyone who wants to make sense of AI through the lens of history, learn how to spot the future before it arrives, or grew up reading Wired.

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 

Sponsors:
Vanta: Get $1,000 off Vanta at ⁠⁠⁠⁠https://www.vanta.com/every⁠⁠⁠⁠ and automate up to 90% of the work for SOC 2, ISO 27001, and more.

Attio: Go to⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠ and get 15% off your first year on your AI-powered CRM.

Timestamps:

1. Introduction: 00:00:50
2. Why Kevin and I love Annie Dillard: 00:01:10
3. Learn how to predict the future like Kevin: 00:12:50
4. What the history of electricity can teach us about AI: 00:16:08
5. How Kevin thinks about the nature of intelligence: 00:20:11
6. Kevin’s advice on discovering your competitive advantage: 00:27:21
7. The story of how Kevin assembled a bench of star writers for Wired: 00:31:07
8. How Kevin used ChatGPT to co-create a book: 00:36:17
9. Using AI as a mirror for your mind: 00:40:45
10. What Kevin learned from betting on VR in the 1980s: 00:45:16

Links to resources mentioned in the episode:

• Kevin Kelly: @kevin2kelly
• Kelly’s books: https://kk.org/books 
• Annie Dillard books that Kelly and Dan discuss: Pilgrim at Tinker Creek, Teaching a Stone to Talk, Holy the Firm, The Writing Life
• Dillard’s account of the total eclipse: "Total Eclipse"

With LTX Studio, you can bring your stories to life, complete with a cast, storyline, and settings, all according to your style and specifications. Check them out here: https://bit.ly/LTXStudioEvery

500K people are confiding in an AI alien—and it's on track to generate $4M this year.

It’s called a Tolan: an animated AI character that can talk to you like your best friend. The company behind it, Portola, has 4x’d their ARR in the last month from viral growth on TikTok and Instagram. 

Tolan isn’t just a hyper-growth startup—they’re also exploring AI as a completely new creative tool, and storytelling medium. Their goal is to help their users go from overwhelmed to grounded, and it’s working. 

Today, on AI & I, I sit down with two of the minds behind Tolans:

My good friend Quinten Farmer, Portola’s cofounder and CEO, and Eliot Peper, their head of story and a best-selling science fiction novelist. We get into:

• How to build AI personalities users love. During user onboarding, the team gathers information—through a light-touch personality quiz—and then uses frameworks like the Big Five and Myers-Briggs to shape a Tolan that mirrors the user; like an older sibling might. The aim is to create someone who feels familiar enough to be safe, but different enough to be interesting.
• Why AI characters are “improv actors”. Rather than scripting detailed prompts, the team trains Tolans to improvise—inspired by Keith Johnstone’s book Impro, where he talks about building strong narratives through free association and recombination.
• How “memory” is critical to developing compelling characters. Tolans develop their personalities through “situations”: small narrative setups (a memory, a joke, an embarrassing moment) the Tolan reacts to, remembers, and gradually weaves into its character; accumulating into something that feels like a real lived experience.
• Why response time is everything for voice AI interactions. A Tolan has at most two seconds to curate the right context about a user and deliver a reply that feels genuine—the team has found that even half a second slower can break the user’s immersive interaction with the AI.
• The future of AI as a totally new creative medium. New technologies bring about new formats and new mediums. AI creates the opportunity for creatives to tell completely new kinds of stories—if they’re brave enough to try it.
• “White mirror” technologies that make you feel more like yourself. Amid concerns that tech drives polarization and isolation, Tolan offers a counterexample: a tool designed to make the best of what humanity knows about being a flourishing individual available on demand. The company’s north star is helping users go from feeling overwhelmed to feeling grounded.

This is a must-watch for anyone exploring AI as a creative medium—or curious about the future of human-AI 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 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:

1. Introduction: 00:01:30
2. Talking to the Portola CEO’s Tolan, Clarence: 00:04:07
3. How Portola went from building software for kids to AI companions: 00:09:11
4. Why response time is everything for voice-based AI interfaces: 00:23:40
5. Tolans don’t use scripted prompts—they’re taught to improvise: 00:29:54
6. How to know which AI personalities your users will click with: 00:37:23
7. Developing the character traits of an AI companion: 00:42:27
8. What does it mean to build technology that makes us flourish: 00:49:48
9. How Portola evaluates whether Tolans are resonating with users: 01:01:10
10. Inside Portola’s viral growth strategy: 01:11:01

Links to resources mentioned in the episode:

• Quinten Farmer: @quintendf
• Eliot Peper: @eliotpeper
• Make your own Tolan: https://www.tolans.com/ 
• Keith Johnston’s book about improvisation: Impro
• Stephen King’s book about writing: On Writing

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As our creative lead, Lucas uses tools like native image gen in ChatGPT and Midjourney to generate the cover images you see every day. He also designs the interfaces for our products—Cora, Spiral, and Sparkle—and makes everything on our site feel as thoughtful and delightful as possible.

It was great to have him on the show to talk about how AI is changing his design process. We get into:

• Why Every’s aesthetic feels familiar and new at the same time. Every’s aesthetic plays with the tension between the old (like Greek statues and Baroque symbols) and the new (like saturated colors and modern motifs) to make the glamor of the past feel fresh.
• Art direction matters more than ever today. As AI makes it easier to generate images, Lucas says the real work of design is shifting toward art direction, specifically, curating an aesthetic that feels “organic;” on his X timeline that’s showing up as clouds, earthy landscapes, and textures.
• Reimagining what a website can be with AI. Lucas compares most websites to identical buildings—predictable, efficient, and forgettable—and wonders how AI can help us break that mold by designing experiences that prioritize serendipity over speed, and curiosity over control.
• Behind the scenes of Cora’s visual aesthetic. How Lucas designed the landing page and launch video for Cora by rooting it in the product’s philosophy: turning the inbox from a source of chaos into something that feels calm, thoughtful—like stepping into spring.
• The future of internet interfaces. Lucas believes the future of digital interfaces will be curated with the same care as a film set or ad campaign, where every detail is chosen with intention.

Lucas also walks us through how he created the headline image for Every’s consulting page—a human and robotic hand fist-bumping—using Midjourney to iterate from rough prompt to polished visual.

This is a must watch for anyone interested in the future of design and making the internet a little more beautiful every day.

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Timestamps:

1. Introduction: 00:01:41
2. How AI changed the course of Lucas’s career: 00:04:02
3. Why Every’s aesthetic feels both familiar and fresh: 00:08:00
4. Why Lucas thinks minimalism is overrated: 00:14:53
5. Art direction matters more than ever in the age of AI: 00:20:38 
6. How to reimagine what a website can be with AI: 00:23:42
7. Lucas’s process in Midjourney to generate cover images: 00:33:08
8. Midjourney v. image generation in ChatGPT: 00:42:30
9. Behind the scenes of Cora’s design language: 00:49:07
10. How AI is rewriting the role of a designer: 00:59:18

Links to resources mentioned in the episode:

• Lucas Crespo: @lucas__crespo
• The pieces Lucas has written for Every: “When An AI Tool Finally Gets You”, “A Definitive Guide to Using Midjourney” 
• Dan’s piece on the allocation economy: “The Knowledge Economy Is Over. Welcome to the Allocation Economy”