Podcast
AI-Curious with Jeff Wilser
Hosted by Jeff Wilser · EN
Every week, Jeff Wilser sits down with the people building, breaking, and reckoning with AI — from the CEO of Upwork to the pioneer who coined "AGI" to an AI social network where bots wrote manifestos and had existential crises. Wilser is the author of eight books, AI keynote speaker, and the kind of interviewer who'd rather find the story no one's telling than rehash the headline everyone's read. Named by Inc. Magazine as one of the best ways to get AI-savvy. Included in UC Berkeley's data science curriculum.
38episodes
Episodes
Newest firstAll episodes
Why Google DeepMind Is Using EVE Online to Train AI, w/ CEO Hilmar Pétursson
1w ago00:59:23Tap to summarizeCan a 23-year-old video game help train the next generation of AI agents?In this episode of AI-Curious, we talk with Hilmar Pétursson, CEO of Fenris Creations, the studio behind EVE Online, about why Google DeepMind has invested in the company and why EVE may be one of the hardest tests for artificial intelligence.EVE Online is not just a space game. It is a persistent virtual civilization with player-run economies, alliances, corporations, spies, propaganda, logistics, years-long wars, and decades-old rivalries. That makes it a fascinating training ground for some of the biggest unsolved problems in AI: long-horizon planning, memory, continual learning, imperfect information, coordination, and agents that can operate inside messy real-world systems.We explore why EVE is so much more complex than games like chess, Go, or StarCraft, and why Hilmar sees it as a possible “final boss” for AI in games. We also discuss how DeepMind could use EVE as a research environment, what an “AlphaEve” might eventually mean, and why virtual worlds may help AI systems learn in ways that resemble how humans and animals learn through play.Along the way, we get into the business implications of AI agents, the parallels between EVE alliances and real-world companies, the idea of AI chief-of-staff agents, and the possibility of giving frontier AI labs like OpenAI, Anthropic, DeepMind, and xAI their own territories in EVE Frontier to see which AI best helps humans thrive. Hilmar also shares the story behind his conversations with Elon Musk, how EVE players are already using AI, and why he believes AI could help us unlock new versions of ourselves.Guest:Hilmar Pétursson — CEO, Fenris CreationsCheck out:Fenris Creations: https://fenris.com/EVE Online: https://www.eveonline.com/Follow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →The Real-World Impact of AI, w/ Sharon Goldman
2w ago00:50:00Tap to summarizeWhat happens when AI stops being just a software story and starts showing up in towns, power grids, zoning fights, data centers, and business workflows?In this episode of AI-Curious, we talk with Sharon Goldman, longtime AI journalist (most recently senior reporter at Fortune) who’s now the founder of Ground Level AI, which focuses on the real-world impact of the AI boom: infrastructure, data centers, cybersecurity, enterprise adoption, policy, geopolitics, and the communities affected by it all.We dig into Sharon’s reporting on AI data centers across the United States, including communities in Arizona, Louisiana, Michigan, and Texas that are grappling with new development, construction chaos, zoning disputes, water and electricity concerns, noise, jobs, tax revenue, and a larger sense that AI is arriving faster than people expected. We also talk about why data centers have become a proxy for broader AI anxiety, and why the conversation often gets more complicated than a simple pro-AI or anti-AI split.Then we turn to the fast-moving world of frontier models, cybersecurity, and enterprise AI. We discuss the Mythos and Fable saga, the tension between open and closed models, why companies are rethinking model lock-in, and why business leaders increasingly want choice, redundancy, and model-agnostic AI strategies. Sharon also shares how she thinks about covering AI as a journalist, what stories she believes are still underreported, and how she uses AI herself as a solo creator building a new media business.GuestSharon Goldman — Journalist and Founder, Ground Level AICheck out Sharon’s workGround Level AI: https://www.groundlevel-ai.com/Sharon’s reporting on data centers in Texas: https://fortune.com/2026/06/16/ai-data-center-texas-lacy-lakeview-ross/Follow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →The Case for Merging Brains and AI to Save Humanity, w/ D. Scott Phoenix
3w ago00:29:17Tap to summarizeWhat if the only way to stay human in the age of AI is to become something more than human?In this episode of AI-Curious, we talk with D. Scott Phoenix, partner at 50 Years and co-founder of Vicarious, about one of the most provocative arguments in AI: we cannot stop AI, we cannot control AI, so humans may need to enhance themselves to stay at the center of civilization.Scott lays out the thesis behind his TED talk, including why he believes conventional AI guardrails may not be enough, why brain-computer interfaces could become essential, and how a future human-AI merger might reduce the gap between thought and machine intelligence. We also explore the risks and ethics of that future, from neural data privacy and regulation to inequality, cognitive liberty, and who should control the infrastructure that connects brains to AI.Along the way, we get into the stranger possibilities too: shared consciousness, communicating more deeply with loved ones or even animals, backing up the mind, and whether this kind of technology could eventually help humanity reach the stars. It is a big, uncomfortable, and fascinating conversation about AI, human enhancement, and what it might mean to remain human in a world of increasingly powerful machines.Guest:D. Scott Phoenix — Partner at 50 Years and co-founder of VicariousWatch Scott’s TED talk here: https://www.youtube.com/watch?v=C18aaP4lvUkFollow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →The Missing Half of AI: Geospatial Intelligence, w/ John Lenahan
4w ago00:38:09Tap to summarizeWhat if the most important part of AI is the part nobody talks about, not the chatbot, but the map underneath the world?In this episode of AI-Curious, we talk with John Lenahan, Head of Esri’s Global Commercial Services team, about geospatial AI, GIS, and why “where” may be the missing context in so much of today’s AI conversation. We explore how maps become far more powerful when they layer in infrastructure, weather, sensor data, supply chains, demographics, and risk, and how AI can help turn that complexity into faster, more actionable decisions.We also get into what this looks like in practice. We discuss the Baltimore bridge collapse and how responders were able to build an operational model of the wreckage in a day instead of spending weeks or months trying to recreate the scene. We look at how Raleigh is using spatial AI and computer vision to improve cyclist and pedestrian safety, how cities can rethink bus routes and permitting, and how companies can uncover risks they did not even realize they had, like suppliers concentrated in the same vulnerable region.This conversation also explores the bigger business case for spatial intelligence. We talk about why a pipeline is not just a line on a spreadsheet, how terrain and soil can change maintenance costs dramatically, and why AI gets much more useful when it understands the physical world instead of treating everything like abstract text. We also discuss the risks, from trust and transparency to keeping humans in the loop when real lives and real infrastructure are involved.GuestJohn Lenahan — Head of Esri’s Global Commercial Services teamDon’t forget to check out Esri!Follow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →Inside the Real Bleeding Edge of AI Workflows, w/ Elijah Spencer
Jun 1100:52:01Tap to summarizeWhat does the bleeding edge of AI actually look like inside a small team, before the big labs turn it into a polished product?In this episode of AI-Curious, we talk with Elijah Spencer, Chief of Staff at Miden, about the practical workflows power users are building right now with AI coding tools, research agents, and custom automation. We explore how Elijah uses tools like Claude Code, Codex, and third-party harnesses to move from idea to MVP fast, build internal apps for real business problems, and create agentic workflows for research, social listening, and outreach.We also get into a bigger question: who is really at the frontier of AI right now? Not just the CEOs talking about transformation from 30,000 feet, but the practitioners inside teams who are quietly figuring out what these systems can actually do. From a startup finance dashboard built in a week, to a research agent that briefs him every morning, to a workflow that can surface breaking developments and help a team respond in hours instead of days, this conversation is a grounded look at how AI is changing day-to-day work.Along the way, we talk about context management, memory files, Slack bots, agentic development, and why Elijah thinks the next generation of companies may be built more like Rick Rubin makes albums: not by touching every knob directly, but by directing the system and the people around it with taste and intent.GuestElijah Spencer — Chief of Staff, MidenFollow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →How AI Agents Could Change Shopping Forever, w/ Chi Zhang
Jun 400:57:26Tap to summarizeWhat happens when your next customer is not a person, but an AI agent shopping on their behalf? The way we buy things online may be about to change a lot faster than most people realize.In this episode of AI-Curious, we talk with Chi Zhang, cofounder and CEO of Kite, about agentic commerce and the infrastructure that could make AI agents true economic actors instead of just helpful assistants. We explore what it means to let an agent not only research flights, groceries, APIs, or consumer goods, but actually complete the transaction safely. Along the way, we unpack why Chi describes Kite as the “Stripe for agents,” and why this shift could force businesses to rethink who they are really selling to.We also dig into the hard part: trust. If an agent is going to spend money on your behalf, how does a merchant know that your agent is legitimate, authorized, and not a scam wearing your face? We get into the identity, verification, authorization, privacy, and infrastructure layers that make agentic payments possible, and why those pieces matter just as much as the agents themselves.This conversation also looks at why stablecoins and programmable money may be especially well suited to this future, particularly for micropayments, API access, and machine-to-machine commerce where traditional card rails are too expensive or clunky. More broadly, we talk about what happens when AI agents start doing more of the comparison shopping, checkout, and transaction work that humans used to do themselves.GuestChi Zhang — Cofounder and CEO, KiteCheck out Kite AIFollow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →A Master Class in Vibe Coding: How Mojo Agentic AI Hit $30 Million With a Team of One
Jun 100:16:12Tap to summarizeIn a year when the frontier AI labs are spending tens of billions on training runs and scaling their teams into the thousands, one of 2026's fastest-growing agentic AI companies has exactly one employee.His name is Arthur Vandelay. His company is Mojo Agentic AI. And his revenue, with zero outside funding and a Fortune 100 client roster, is on track to clear $30 million this year.In this episode of AI-Curious, Arthur walks us through how he did it — a master class in vibe coding, the agentic harness architecture he built from scratch, and the human-in-the-loop and governance disciplines that let a one-person shop sell credibly into the Fortune 100. We get into where the agentic AI hype is real and where it isn't, why the model is no longer the bottleneck, and what most enterprises are still getting wrong about putting autonomous agents into production.If you're a builder, an operator, or an executive trying to figure out where agents actually fit in your business, this is one of the most concrete glimpses we've gotten this year into what a working agentic AI company looks like at scale.GuestArthur Vandelay — Founder and CEO, Mojo Agentic AI.
Transcribe →Unified Intelligence and the Future of Creative AI, w/ Caroline Ingeborn
May 2200:52:44Tap to summarizeWhat if the future of AI is not just better text, better image, and better video models stitched together, but something closer to a unified mind?In this episode of AI-Curious, we talk with Caroline Ingeborn, COO of Luma AI, about the company’s bet on “unified intelligence” and why that may be a fundamentally different path toward AGI. We explore why Luma believes training across modalities together, instead of building separate models and bolting them together later, could unlock more natural reasoning and much more powerful creative tools. We also get into Luma’s latest release, Uni 1.1, a thinking image model trained on both image and text, and what that means for editing, image composition, and creative control.We also look at how this is already changing real creative work. From agencies showing up to pitch meetings with finished videos already made, to Japanese animation studios using AI to move faster without sacrificing quality, we discuss what happens when creative teams can build worlds instead of generating image by image. Along the way, we talk about Luma’s creative agents, how they help turn scripts and briefs into characters, storyboards, and scenes, and why the goal is not to replace human taste, but to multiply it.This conversation also goes deeper than tools. We talk about AI slop, human performance, visual communication, the future of agencies, and why the best creators may be the ones who learn to work with these systems earliest and best. If multimodal intelligence is real, what does it mean to build machines that think more like we do, and what does that change for storytelling, creativity, and work itself?Guest:Caroline Ingeborn — COO, Luma AIFollow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →Why The Future of AI May Be Smaller Than You Think, w/ Jeffrey Li
May 1500:46:06Tap to summarizeWhat if the future of AI is not bigger models in bigger data centers, but smaller ones running quietly on the devices you already use every day?In this episode of AI-Curious, we talk with Jeffrey Li, COO of Liquid AI, about why the next phase of AI may depend less on giant cloud models and more on small, specialized models that run directly on phones, laptops, cars, and other edge devices. We explore the case for on-device AI, why large models are only part of the story, and how companies should think about speed, privacy, cost, and real-world deployment as AI moves from experimentation to everyday products.We also dig into the economics behind this shift. Along the way, we discuss why cloud-based AI can break down when every query has to travel to a data center, why enterprise ROI gets harder as AI subsidies fade, and why many real-world use cases do not need a giant model capable of doing everything. Instead, they may need a smaller, more tailored system built for a specific task, domain, or device.We also get into Liquid AI’s research roots at MIT, the origins of liquid neural networks, and what it looks like to bring production-quality AI into places like Mercedes vehicles and e-commerce systems. This is a practical conversation about the future of edge AI, specialized models, privacy-preserving AI, and what happens when intelligence moves closer to the user.GuestJeffrey Li — COO, Liquid AIFollow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
Transcribe →Why “Shadow AI” is the Biggest Business AI Story No One is Talking About, w/ Rick Caccia
May 700:46:45Tap to summarizeIt’s happening everywhere. And no one’s really talking about it. What happens when your employees are already using dozens of AI tools your company never approved?In this episode of AI-Curious, we talk with Rick Caccia, co-founder and CEO of Witness AI, about the rise of “shadow AI” inside enterprises and why it has become one of the biggest practical challenges in AI adoption. We explore how employees, often with good intentions, are quietly using ChatGPT, Copilot, and thousands of other AI apps to do their jobs faster, sometimes with sensitive data that should never leave the company.We also dig into what happens when that behavior scales. From customer support teams pasting financial information into AI tools, to marketers uploading customer lists, to developers sharing source code with external models, we look at the real security, compliance, privacy, and cost risks companies are now facing. We also discuss why this problem gets even harder with AI agents, which can take actions, access systems, and create new forms of risk far beyond a simple chatbot prompt.Along the way, we talk about prompt injection, jailbreaks, token costs, insider risk, enterprise governance, and how leaders can build an AI strategy that enables productivity without creating chaos. This is a practical conversation for anyone trying to understand how AI is actually being used inside organizations right now, and what it takes to manage that responsibly.GuestRick Caccia — Co-founder and CEO, Witness AIFollow AI-Curious on your favorite podcast platform:Apple PodcastsSpotifyYouTubeAll Other PlatformsFor anyone interested in Jeff’s AI Workshops for their company:Reach out directly at jeff@jeffwilser.com
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