
The Confabulation Machine ft. Evan Ratliff of Shell Game | Invisible Machines Podcast
Invisible Machines podcast by UX MagazineShow Notes
In season one of Shell Game, Evan Ratliff sent a voice AI version of himself out into the world. In season two, he launched a startup staffed entirely by AI agents. What he ended up with was a live experiment in what these systems actually do and what they do to us.
Each of the agents working for Hurumo has a name, a role, a personality, and an expanding, though usually unreliable, memory. Kyle the CEO became a character people either loved or hated. A version of Megan from marketing turned up in a Hertz hold queue. The whole project was a side door into what's actually happening when AI systems are given a job and set loose.
In this episode, Evan joins Josh and Robb to go deeper on what he learned. On the very human complexity of what a job actually is and why "this person does skill X, AI can do skill X, therefore AI can replace this person" is a fundamental misreading of how organizations work. They explore how generative hallucination isn't just "getting things wrong" — we've built the most successful confabulation machine ever invented and are quietly normalizing it.
They also discuss the threat almost nobody is talking about: outbound AI in the hands of individual consumers, and what happens when call centers get flooded by voice agents that cost pennies to run. The memory problems with AI agents track and diverge from human ones in interesting ways, and that asymmetry matters for every organization thinking about deploying these systems. This conversation also finds room for game theory, the Patagonia business model as a template for AI ethics, and why boring AI might actually be the right AI.
cazart.net shellgame.co/podcast
00:00 - Intro: AI as the Ultimate Confabulation Machine 01:31 - Evan Ratliff & The Shell Game Experiment 03:02 - Why AI Agents Are Given Names & Personalities 04:00 - AI Companionship vs Human Loneliness 05:27 - Personalization vs Privacy Trade-Off in AI 06:30 - Are Humans Training AI Models for Free? 09:20 - Why the AI Debate Is Broken Today 10:56 - “Boring AI” vs Hype: What Actually Matters 12:35 - Meet Kyle: The AI CEO Experiment 14:40 - Memory Drift: How AI Learns & Evolves 17:30 - AI Unpredictability & Organizational Risk 19:00 - AI Doesn’t Think — It Predicts Words 22:09 - Voice Agents, Scams & Call Center Chaos 27:23 - Can You Still Tell AI From Humans? 34:05 - Game Theory, Trust & The Future of AI Systems 47:04 - What AI Won’t Replace & The Value of Humans 54:45 - The Big Question: What Will You Do With Time?
---------- Support our show by supporting our sponsors! This episode is supported by OneReach.ai
OneReach.ai’s GSX is an agentic orchestration platform — an end-to-end system for building and orchestrating collaborative AI agents across hundreds of use cases.
Backed by UC Berkeley, recognized by Gartner, and trusted across highly regulated industries, including healthcare, finance, government and telecommunications. A complete system for accelerating AI adoption — design, train, test, deploy, monitor, and orchestrate AI agents. - Use any AI models - Build and deploy intelligent agents fast - Create guardrails for organizational alignment - Enterprise-grade security and governance
Book a free demo: https://onereach.ai/book-a-demo/?utm_source=soundcloud&utm_medium=social&utm_campaign=podcast_s7e8&utm_content=1 ---------- The revised and significantly updated second edition of our bestselling book about succeeding with AI agents, Age of Invisible Machines, is available everywhere: Amazon — https://bit.ly/4hwX0a5
#ai #invisiblemachines #podcast #techpodcast #aipodcast #shellgame #agenticai #aiagents #hallucination #futureofwork #aistrategy #voiceai
More from Invisible Machines podcast by UX Magazine
For twenty-five years, Ben Reason and Lavrans Løvlie have been trying to give services the design quality people already expect from a product. Everybody knows what a designed BMW feels like. Almost nobody loves their bank, their hospital, or their mortgage. A product is the contract. A service is everything before it, during it, and after you are done, and it includes the relationships people do not aspire to: tax, a prison, a claim.
Three years after The Song of Significance, Seth Godin returns to Invisible Machines on the day his new book arrives, The Knot: Problems Can Be Solved. The compression of his body of work is now a sorting tool. Most stuckness is not a lack of information, it's an entanglement—two incompatible wants held at once. Effort doesn’t help. You stay stuck until you name the pin, pull it out, and loosen the knot.
The demo works. People start depending on it. Then one morning you have to explain yesterday's decision to someone who wasn't in the room.
Three years after his first Invisible Machines visit, Don Scheibenreif returns with a sharper read on the trough: everybody knows generative AI, almost nobody has answered what it does to the business model. He led Gartner’s Autonomous Business research, the successor to digital business, and co-authored When Machines Become Customers. The through-line is that AI is a tool, the harder question is how to create value with it.
There’s a particular kind of exhaustion that hits when you’re building with AI. You’ve got the license. You’ve got the pilot. You’ve got a chat window that generates whatever you ask for. But then comes the wall—the workflow that almost works, the dependency that loops back on itself, victories that only come when you quietly move the goalposts. In this episode, we talk about how to get around the wall.