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. Josh Tyson and Robb Wilson sit down with them at the moment that work stops being a specialty and starts being the bottleneck. Organizations accepted that they needed a better experience, then got stuck behind a backlog. AI takes the backlog away. Anyone can produce software. What they cannot produce, unless someone designs it, is a service worth running. Robb calls the failure mode vanity token burning: fun for the person at the keyboard, expensive for the company, and often pointless for the human on the other end. Service design was built, from the start, around whether a…

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. Josh and Robb press him on what that means when the change agent is AI. Seth’s first move is not “purpose” as a poster. It is a sharper pair of questions: what’s this work for, and who is it for? Fake mission statements are easy. Johnson & Johnson can engrave patients in granite ten feet tall and still get caught serving the bonus pool. A person will wink. A model will not. Lie to AI and it will believe you. Also in this episode: why Seth believes AI is the biggest change since electricity—and why the washing-machine demo was perfect while the real machines were killing people; why a CEO who demands…

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. That is the moment most “agentic” projects discover they were never orchestrated. They were demos. Josh Tyson and Robb Wilson take the word the market glued together—agentic orchestration—and refuse to treat it as a contradiction. Agentic has come to mean autonomous, probabilistic, experimental. Orchestration, in any domain that cannot afford a wrong answer, has always meant the opposite: consistency, an envelope, a decision you can certify. The collision is the point. Vendors map the first axis: how calls flow. Anthropic splits workflow from agent. LangChain draws a wiring diagram. Google ADK argues about execution order, sometimes with itself. Analysts named a layer above those vendors—an Agent Management Platform, six boxes of furniture. Useful. Incomplete. The missing axis is who is allowed to decide, and whether that decision is deterministic or probabilistic. The…

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. Josh and Robb press him on token maxing as a vanity flex. Don calls it a lazy metric, pointing to more interesting questions: where are you more productive, which processes were reinvented, what happened to talent, and what are you doing with the investment? 80% of CEOs see it as the #1 transformative tech and want disruption, but most are settling for efficiency theater and middle-manager cuts while boards ask for more tech-savvy leadership. In Don’s framing this comes with rolling up your sleeves, not mandating from above. Also in this episode: The hyper hype cycle (peak → trough →…

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. Evan J. Schwartz, Chief Innovation Officer at AMCS Group and an adjunct professor teaching AI stewardship, argues the real shift isn’t “AI does the work.” It’s that humans stop owning the full vertical of doing and start owning outcomes—while AI takes more of the output. That sounds abstract until he gets specific: if you ask a model for a feature before you describe actors, containment envelopes, and dependency policy, you’ll get something that passes the demo and fights you every time you try to change it. Josh Tyson and Robb Wilson push on the organizational version of the same mistake—automating…

Most organizations, and most conversations about AI, default to triangles: who's on top and who's below? Are we the boss of the machines or is it the other way around? Matthew Barzun argues the comfortable shape is a trap and that bottom-up is still a pyramid. The alternative is the constellation: stand out as yourself, connect to other stars, and build something none of you could alone. In this episode, Matthew Barzun joins Josh Tyson and Robb Wilson to connect diplomacy, design, and agentic AI through constellation thinking. Kentucky doesn't report to Washington. Berkeley doesn't report to Sacramento. Power isn't finite coal to lord, hoard, or divvy. It's something people make with and through one another when they stop ranking and start using differences as fuel. Josh and Robb press the AI angle hard. If Karen Hao's Empire of AI is a warning about centralized power, Barzun's book reads like the antidote: the boss-or-overlord trap collapses into a design question of how much agency, when, and with what…

Most enterprises are under board pressure to deploy AI agents. Sudhir Hasbe argues the harder shift is upstream: you cannot scale intelligence on missing context—and graph databases are how organizational data becomes knowledge agents can actually reason over. In this episode, Sudhir joins Josh Tyson and Robb Wilson to map the pathway to organizational AGI (bounded expertise, not omniscient AGI), leaning into feature reduction for token sanity, and explaining why eighty-plus percent of enterprise AI projects fail before the model messes anything up. Graphs emphasize relationships over isolated rows; virtual and native storage let you meet latency where it lives; ontologies plus data plus memory form the backboard for self-learning systems. Josh and Robb press on cost—when compute exceeds employee spend if agents spin without context—and on agent sprawl: without a shared semantic map, every bot maintains its own partial truth. Sudhir connects customer examples—Walmart's two-million-employee knowledge graph,…

Everyone wants to talk about agents and models. Jeff McMillan, starts where almost nobody else does: the foundation. In this episode, Jeff McMillan, founder of McMillanAI, former Head of Firmwide AI at Morgan Stanley, and advisor on enterprise AI, maps AI as a stack: high-quality accessible data → semantic layer (knowledge graphs, RAG) → control and governance → models → orchestration → applications. The heavy lifting is in the bottom layers. Organizations that skip them can fake it for a handful of agents, but at 150 or 15,000 agents, you need near-100% accessibility and 99%-plus quality, or you’re monitoring chaos you can’t see. Josh and Robb press him on why knowledge management feels unfundable, why tribal institutional knowledge breaks when machines execute without judgment, and why evaluation (golden datasets, custom org evals, regression when models upgrade) is the work builders hate and operators can’t skip. Robb names the trap CTOs are falling into: grinding tokens on feature backlogs that never…

Most organizations treat a bigger context window like a cheat code: dump every document in, skip the data work, ship. Jonathan Frankle, Chief AI Scientist at Databricks, says that's still wrong. This is Jonathan's return visit to Invisible Machines — a conversation recorded last summer, released ahead of Databricks Data + AI Summit. His first appearance (season 2) was the MosaicML-era craft conversation: lottery tickets, mixology, mini-cupcakes. This one is the enterprise engineering thread: be a scientist, curate before you scale, and treat specification (what you actually want the system to do) as the bottleneck between raw model power and useful AI. Robb and Josh press him on the myths that still seduce enterprise teams: million-token windows as a substitute for real data work, hyperscaler résumés as a proxy for talent, and the fantasy that unlocking every PDF in the org automatically makes knowledge useful. Jonathan's answer is consistent: measure success, test your use case, climb the ladder of…

Mastercard's central AI team receives roughly a thousand requests a year from across the organization. A few years ago, most of them were for chatbots. Today, most are for AI agents. Federico Cohen Freue, Executive Vice President of AI & Data Operations at Mastercard, has watched this shift in real time and knows exactly what it reveals about how enterprises are (and aren't) thinking about AI. In this episode, Federico explains why the name people use for what they want matters less than whether they understand the conditions that make it work. “Ball bearings,” as Robb Wilson puts it: demos can't reveal the difference between a solution that will hold and one that will blow up the engine. What actually matters is training, fluency, and a clear framework for where to deploy AI with purpose. For Mastercard, that framework is deliberate: use AI to make commerce more secure, smarter, more personal, and to make the company itself stronger. Not everything. Those things. The simplicity is a feature, it gives a…

Most AI strategies are just a buying plan: literacy workshop → vendor shortlist → adoption scoreboard. Brian Evergreen (Founder of The Future Solving Company, author of Autonomous Transformation) argues that this sequence explains a lot of failure, and it isn’t strategy at all. In this episode, Brian reframes the job: set the technology aside long enough to name the new value you want to exist, in language vivid enough that people can feel the outcome. From there, no strategy without vision: you work backward through “what would have to be true,” turning invisible opinions into a visible map of bets before agents, data estates, or org charts get to pretend they’re the point. According to Brian, “10% more profitable” isn’t a vision, and a moonshot can still be concrete. Josh and Robb press him on the pressure to remove friction and flatten the middle of the org. Brian doesn’t dismiss friction work, he warns that friction can quickly pile up if you go hunting without a north star. Vision is the force with…

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…

Most organizations treat crisis as a failure state. Marina Nitze sees it as a window. Nitze served as Chief Technology Officer of the Department of Veterans Affairs (the largest civilian agency in the country) during the healthcare.gov collapse. She helped rescue it, helped stand up the US Digital Service, and came out the other side with a question she and her colleagues have been pursuing ever since: why is it that crisis makes otherwise impossible transformational change possible? That question became a firm, Layer Aleph, and now a book, Crisis Engineering, co-authored with her colleagues. In this conversation, she walks through what a "useful crisis" actually looks like, the five indicators that distinguish it from chronic problems masquerading as crises, and the practitioner toolkit for standing up a crisis engineering center when the window opens, because the window is usually hours, not days. We also get into two stories that hit harder than any framework: the California unemployment system's call…

There's a book about artificial intelligence that doesn't start with Sam Altman. It doesn't start with Elon Musk. It starts in 1994, at Cambridge, where a teenager named Demis Hassabis is reading Gödel, Escher, Bach and concluding, before most of his professors would have agreed, that first-order logic can't be the full answer to building intelligence. Sebastian Mallaby spent years inside that story. His new book, The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence, is the most serious attempt yet to explain not just what AI is, but why the people building it can't stop. His answer draws on a line Jeff Hinton borrowed from Robert Oppenheimer: invention is sweet. A scientist, given the chance to build something, simply cannot resist. The consequences come later. In this conversation, Mallaby joins Josh Tyson and Robb Wilson to explore the full sweep of the Demis Hassabis story — from game designer to neuroscientist to Nobel laureate to the man running Google's flagship AI lab.…

The IRS has roughly 60,000 fax machines, and nobody can get rid of them. Not because there’s a law that says you have to use them (there almost certainly isn’t), but because likely decades ago a memo got written, somebody interpreted fax machines as the most secure transmission method, and that memo calcified into what Jennifer Pahlka calls "folk law," a perceived rule that nobody can locate, nobody can challenge, and everybody treats as immutable. Folk law looms large in the American government right now. Cascades of rigidity built from outdated interpretations of rules that were flexible to begin with, administered by people who were never asked whether any of it was working. Jennifer Pahlka, who wrote Recoding America: Why Government Is Failing in the Digital Age and How We Can Do Better, is the founder and former executive director of Code for America, and was Deputy CTO for Government Innovation in the Obama White House. She’s working on the gap between what government is supposed to do and what it…

Most organizations are still implementing AI as point solutions, dropping new technology into existing workflows to do the same work, just slightly better. The real value lies in system solutions that completely transform how organizations operate. Avi Goldfarb, economist and co-author of Prediction Machines, joins Robb and Josh to explain why AI adoption follows predictable economic principles and why internal resistance, not technology limitations, is the primary barrier to transformation. This conversation, recorded back in 2023, reminds us that most organizations continue to struggle with the same issues surrounding systemic change in 2026. Goldfarb's core argument: AI is fundamentally cheap prediction. Just as the internet made search and copying cheap, AI makes prediction cheap. When something becomes a commodity, the complements, the things that work alongside it, become more valuable. This includes compute power (benefiting Microsoft, Amazon, Google), unique data, and crucially, human judgment. The…

Joshua Gans, economist and co-author of Prediction Machines (and holder of the Skoll Chair in Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto) joins Robb and Josh to reframe how enterprise leaders should think about AI. Rather than chasing the hype around artificial intelligence, Gans argues we should understand AI as an advance in computational statistics that drops the cost of prediction, reduces decision-making friction, and fundamentally reshapes organizational structure. Many organizations are full of people waiting for phones to ring, managing buffers, absorbing uncertainty. As AI makes prediction cheap, this middle-management friction layer flattens. His new book, The Microeconomics of Artificial Intelligence, examines the ways AI enhances and perhaps enables decision-making, and how that’s poised to affect organizations and industries. The trio discusses the "hidden secret" of AI adoption that the people who choose the systems used to automate work…

Before enterprises can deploy AI agents that actually work, they need something most organizations don't have: a single, authoritative source of truth. Joe DosSantos, Workday’s VP of Enterprise Data and Analytics, joins Robb and Josh for a wide-ranging conversation about canonical knowledge, the semantic layer, and why data governance, a concept from the 1990s, has suddenly become essential for AI deployment. Large language models are predictive engines modeled to anticipate what users probably likely mean. For B2C applications where multiple interpretations are acceptable, this works fine. But enterprises need deterministic truth, not probabilistic guesses. The trio outline a solution in three layers: establishing canonical knowledge, building a semantic layer to translate between human definitions and machine-readable formats like YAML, and using LLMs as an interface to deterministic back-end systems. For leaders evaluating AI investments, this episode clarifies what actually needs to be built before…

Ben Goertzel, the researcher who helped popularize the terms "AGI" and “singularity”, as one of the most influential modern champions and systematizers of AGI, returns to Invisible Machines to discuss the decentralization of AI and what's actually missing from today's most advanced systems with Robb Wilson and Josh Tyson. As enterprises rush to deploy AI agents and LLMs reshape workflows, a critical question emerges: who controls the infrastructure? Goertzel argues that while big tech dominates model development, a tension is building between centralized hegemony and decentralized, open systems — the same dynamic that shaped the internet itself. In this wide-ranging conversation, Goertzel discusses his current work on Hyperon (the successor to OpenCog) and the ASI Chain, systems designed to enable decentralized AGI development. He explains why the rapid cycles of AI hype and disappointment — the traditional "AI winters and summers" — no longer slow progress the way they once did. The speed of change has…

We’re in a moment when organizations are approaching agentic AI backwards, chasing flashy use cases instead of building the scaffolding that makes AI agents actually work at scale. Erika Flowers, who led NASA’s AI Readiness Initiative and has advised Meta, Google, Netflix, and Intuit, joins Robb and Josh for a frank and funny conversation about what's broken in enterprise AI adoption. She dismantles the myth of the "big sexy AI use case" and explains why most AI projects fail before they start. The trio makes the case that we're entering a post-software world, whether organizations are ready or not. Listen and learn why the scaffolding— or agent runtime — matters more than use cases, why organizational gaps kill AI projects, how to move projects from pilot to production, and what "post-software" actually means for enterprises. Check out Erika’s podcast, “Flower Power Hour”: https://open.spotify.com/show/15BTSl9fWiH3QTmVAYj6Fd Learn more about Erika at www.helloerikaflowers.com/ 0:09 - NASA AI Readiness…

As 2025 draws to a close, Robb and Josh look back on some of the conversations they had this year both on the podcast and advising major enterprises and government leaders to offer their predictions for agentic AI in 2026. With major disruptive forces like outbound AI in the hands of consumers and agent runtime environments allowing organizations to create scalable infrastructure for AI agents, next year could see seismic changes in the way investors look at companies, and the ways companies look at themselves. Featuring a look at the components of an agent runtime, as well as previews of upcoming episodes with returning guest Ben Goertzel of SingularityNET and Joshua Gans, co-author of Prediction Machines, this episode is required viewing for anyone charged with finding ROI with agentic AI. 00:00 – Introduction to 2026 Agentic AI Predictions 01:12 – Outbound AI Arrives 02:30 – Scaling vs. Inventing AI 04:55 – Ben Goertzel Preview 06:45 – Scrappy Innovation in AI 08:20 – Invisible Work Explained 10:00 –…

How did a Dutch company most people haven’t heard of come to hold the fate of AI? Marc Hijink, author of Focus — The ASML Way joins Josh and Robb to explore the insatiably precise process of producing the chips that power GPUs, and with them the AI taking shape all around us. Marc is a financial reporter and technology columnist for the Dutch daily newspaper NRC, and Focus is the result of decades of uncompromising, embedded reporting on ASML, which produces 90% of all chips worldwide.  Operating out of a quiet town in the Netherlands, their extreme ultraviolet (EUV) lithography machines produce a steady stream of chips working with an accuracy of within a few atoms. The trio explores how the EUV process is as much probabilistic as it is deterministic, as well as the impact that different cultures have on ASML’s partnerships and pipeline. Relying on lenses that have to be grown from crystals, lithography is a high-stakes endeavor that requires a delicate balance of tooling and advanced engineering. We…

Omar Santos is a Distinguished Engineer directing AI Security at Cisco. He’s here for a frank conversation about the realities of security in the agentic era. As more software is created on-the-fly by AI agents at the request of humans, security has to become an ever-present layer. Security will be built into complete agent runtime environments and will require constant human oversight and intervention, augmented by the ability to simulate outcomes to avoid risk. Omar is also the Co-Chair of the Coalition for Secure AI, and these are the things he’s thinking about on a daily basis. He sits down with Robb and Josh at the end of a travel blitz that included work surrounding OpenAI’s Stargate Project, a four-year $500b plan for new AI infrastructure in the United States. The trio discuss how the ongoing training of models and the rising demand for inference continue to push the demand for security across burgeoning technology ecosystems. ---------- Support our show by supporting our sponsors! This episode is…

As the CEO and Co-founder of Apollo GraphQL, Matt DeBergalis has a lot to say about the ways that organizations can confront their inherent complexity and build reliable systems for AI to flourish. He joins Robb and Josh to talk about how GraphQL has made it easier for developers to build meaningful, AI-powered solutions. As an open-source language for APIs, GraphQL makes data fetching more precise and flexible. When utilized within an agent runtime environment, GraphQL gives organizations the ability to build their own tools. As Matt explains, this gives orgs an enormous edge with agentic AI, and helping teams move light on their feet, experiment, and adjust quickly. The trio also reminisces about the early days of the internet and agrees that ChatGPT was the mother of all demos. Looking for the Agent runtime episode - https://youtu.be/CddjTUWSaHA?si=86dSwjyE3uZGYY8F Here is recent news Apollo announced at Summit last week…

Josh and Robb get together to share a short but deep dive into agent runtime environments. Agent runtimes are the missing piece in the many AI projects out in the world that never reach production. Robb explains how runtimes allow businesses to orchestrate AI agents so they can collaborate around business objectives and drive real ROI. Runtimes also give agents access to canonical “source-of-truth” knowledge bases and tools like MCP and A2A that allow them to pull the levers of existing software. Robb and Josh discuss the major investments in time and money required to build a runtime from scratch and why finding a complete agent runtime lets organizations make quick strides with the complex technologies associated with AI. ---------- Support our show by supporting our sponsors! This episode is supported through partnership with OneReach.ai. Experience the first complete runtime for AI agents - a turnkey private architecture and tools for building enterprise-grade agentic solutions. Use any AI models Create…

Brian Solis, is a digital anthropologist and futurist who serves as the Head of Global Innovation at ServiceNow and is the former Head of Global Innovation at Salesforce. Brian is a bestselling author of Lifescale, The End of Business as We Know It, and Mindshift, which helps leaders learn how to see emerging trends, harness disruptive forces, and use them to fuel growth. Brian joins Robb and Josh to talk with us about the importance of self-disruption in AI adoption. With so many genAI projects failing to reach production, this episode looks at approaches taken by IKEA and Airbnb that have induced the kind of mind shift that invites self-disruption. Brian, who's been called the CEO whisperer, also talks about the nuanced difference between “aha” and “uh-oh” moments and the pitfalls of hopeless optimism. Brian Solis’s works: https://briansolis.com/books/ Key Chapters 0:00 — Intro: Josh & Rob set the stage 0:34 — Guest intro: Brian Solis (ServiceNow futurist, author of Mindshift) 1:07 — Why AI adoption…

As Global Head of AI at PayPal, Prakhar Mehrotra is looking deeply at the ways agentic AI is affecting commerce — particularly timely given PayPal and Google’s recent announcement of a multiyear strategic partnership to advance various commerce solutions. He joins Josh and Robb for a layered conversation that speculates on the shape of future marketplaces, where machines are bidding and setting prices on behalf of individuals and businesses. The trio also discuss the ways that AI is reworking the plumbing of technology within organizations and how agent runtime environments hold the key to successful adoption of AI. As the world evolves into one with more AI agents than websites, digital interactions might become simplified for users in ways that add complexity for businesses. Prakahr shares his insights into how humans might interact with technology in the future and how technology will change commerce in ways that are hard to fathom but crucial to confront. ---------- Support our show by supporting our…

Cassie Kozyrkov returns for a deep dive into the decision science behind a truly AI-first approach to technology adoption. Cassie was Google’s first Chief Decision Scientist and currently advises world leaders and executives on how to optimize their most critical decisions. In this episode she explains why AI is now our memory prosthesis and offers sage guidance on how individuals and organizations can become AI-first. This includes an urgent warning to business leaders to avoid the low-hanging fruit of using AI to automate processes there are already clear instructions for. Instead, Cassie explains how to begin looking in the attic and targeting the stuff that always seemed impossible to automate. Introduction to neural networks and deep learning (by Cassie) - https://bit.ly/mfml_113 Cassie also offers courses on Maven, including one with Pascal BORNET and Brian Evergreen (Agentic Artificial Intelligence for Leaders) - the next cohort is Sept 8-19, 2025:…

Bryan Catanzaro was instrumental in the adoption of GPUs for powering machine learning, which has effectively turned NVIDIA from a graphics processing hardware company into a $4T AI powerhouse. Bryan joins Robb and Josh to talk about his journey in AI and how the unique psychology and power structures at NVIDIA enables the company to continually meet the moment in surprising ways. They also discuss the impact of Bryan’s plea for help in categorizing data for emerging language models at a 2019 keynote he delivered to librarians at Stanford. Perhaps most importantly, Bryan shares thoughts on how hair was the first technology. ---------- Support our show by supporting our sponsors! This episode is supported through partnership with OneReach.ai. Experience the runtime for AI agents — a turnkey private architecture and tools for building enterprise-grade agentic solutions. Use any AI models Create guardrails for organizational alignment Equipped with enterprise grade security Avoid vendor lock-in OneReach.ai’s…

In her instant New York Times bestseller, Empire of AI, journalist Karen Hao distills more than a decade of in-depth research into a detailed account of OpenAI’s rise to power and why leadership at the company abandoned their promise to keep their research open. Karen joins Robb and Josh for a deep dive into murkiness surrounding what artificial general intelligence (AGI) actually represents and why AI colonialism and biased systems undercut efforts to create superintelligence that represents the vastness of human learning and experience. Drawing on the work of a nonprofit in New Zealand to preserve the Māori language, the trio also discuss why smaller, focused implementations that use better curated data might be more valuable to businesses trying to integrate AI into their operations. Buy Karen Hao’s book “Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI”: https://www.penguinrandomhouse.com/books/743569/empire-of-ai-by-karen-hao/ Learn more about Karen and here work: https://karendhao.com/…

Award-winning journalist Stephen Witt sits down with Josh and Robb to share insights from his latest book, The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip. There’s a deep connection between Nvidia’s GPU chips and the neural networks powering the LLMs at the center of agentic AI. Witt’s book provides a captivating biography of Huang that details his radical approach to business and innovation, which has made Nvidia the most valuable company in the world (recently reaching a record-breaking market cap of $4 trillion). This episode explores this history of AI as well as the coming Omniverse and what the power of simulation will mean to businesses. Buy Stephen Witt’s book! The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip ---------- Support our show by supporting our sponsors! This episode is supported through partnership with OneReach.ai Experience the runtime for AI agents - a turnkey private architecture and tools for building enterprise AI…

Product design sage Tim Wood returns to the podcast for a conversation about the deepening integrations between experience design and AI, including a dissection of the trending term “vibe coding.” Currently a design lead at Meta, Tim has hands-on experience leading AI-first design and this episode explores what that means on a tactical level. Having been the Principal Product Designer for AI Platforms at AWS, and Head of Design for Amazon Q Developer, Tim shares hot takes with Robb and Josh on what automated mainframe migration means for SaaS providers as well as the broader business community, which leads to the real-time birth of another new term: “placebo swipes.” ---------- Support our show by supporting our sponsors! This episode is brought to you in partnership with OneReach.ai — offering turnkey private architecture for building and orchestrating your team’s AI agents with guardrails. Use any AI models Trusted enterprise-grade security No vendor lock-in Discover more about the power of orchestrating…

What is the explosion of AI solutions in the marketplace doing to pillars of experience design? On this Ask Us Anything episode of Invisible Machines, Robb and Josh respond to a question from Dr. Irina Wagner, listener who works as a generative AI UX researcher at a massive US healthcare company. The answer to her question has connections to Robb’s time working in the sound department at Warner Bros., on films ranging from Galaxy Quest to The Thin Red Line. At its core, success in UX comes down to storytelling. People love stories—give them a compelling one, and they will follow you. As adoption increases, AI is likely to expose bad design by putting a premium on effective storytelling and good taste. This episode takes a deeper look at these elements, offering a fresh perspective and some hard truths about technology and design. ---------- Support our show by supporting our sponsors! This episode is brought to you in partnership with OneReach.ai—offering turnkey private architecture for building your team’s…

As NASA’s longest-running Chief Administrator, Dan Goldin ushered in an era of “faster, better, cheaper” that prioritized safety while pushing the organization forward. He joins Robb and Josh to discuss his approach to innovation and kick some holes in fallacies like the iron triangle, which he calls “horsepuckey.” Goldin was at the helm of major projects, including a redesign of the International Space Station, and various Mars exploration programs. Robb and Josh dig into his profound 50/50 rule for finding team members who can move the needle on innovation without holding an organization back, which has a surprising connection to the work of Michaelangelo. In this episode: The 2nd edition of Robb and Josh’s bestselling book, Age of Invisible Machines: A Guide to Orchestrating AI Agents and Making Organizations More Self-Driving: http://bit.ly/4b7Rx7d Michelangelo’s sculptures: https://www.michelangelo.net/sculptures/ Ben R. Rich's book, Skunk Works: A Personal Memoir of My Years at Lockheed:…

Did the US Copyright office just declare that AI is the artist, not the tool? Does their new report raise more questions than it answers? Robb and Josh welcome back Ed Klaris, Managing Partner at Klaris Law and Columbia Law professor, for part two of their discussion on the office’s ongoing Copyright and Artificial Intelligence report, focusing on copyrightability. Klaris returns with critical insights into what these updates to copyright law mean with more and more people now using generative AI as part of their creative process. The report sets some useful guidelines for which aspects of AI-assisted creative projects are copyrightable, yet it also sparks new questions about the boundaries between human and machine-generated output. Find out more about Ed Klaris and his work here: https://www.klarislaw.com The revised and significantly updated second edition of our bestselling book, Age of Invisible Machines, is now available for preorder on Amazon! https://bit.ly/4hwX0a5 In this episode, we mention: US…

Blaise Agüera y Arcas, author and CTO of Technology & Society at Google, returns to the podcast to talk about his new work, What is Life?. This limited-edition, pocket-sized book is the first part of a larger print project with MIT Press and Antikythera titled What Is Intelligence?. What is Life? draws fascinating parallels between the life-building chemical reactions taking place in natural chimneys deep in our oceans and the work of Alan Turing and John von Neumann in the mid-twentieth century. Blaise joins Robb and Josh to explore how self-reproduction—and thus life—is inherently computational. This conversation delves into the nested nature of life on Earth and how technology is an extension of our evolution. You can buy Blaise’s books from Hat & Beard Press: Who Are We Now? https://hatandbeard.com/products/who-are-we-now-by-blaise-aguera-y-arcas Ubi Sunt https://hatandbeard.com/products/ubi-sunt-by-blaise-aguera-y-arcas In this episode, we mention: Blaise Agüera y Arcas’s work, “What is Life” — read for…

Anna Lembke, MD, author of the New York Times bestseller Dopamine Nation: Finding Balance in the Age of Indulgence, joins Robb and Josh for a discussion about the perils and promise of AI. As a psychiatrist and Chief of the Stanford Addiction Medicine Dual Diagnosis Clinic at Stanford University, Dr. Lembke shares critical insights into the power and nature of behavioral addiction, and how technology and digital media are impacting the dopamine systems in our brains. Drawing from her experience with patients, she shares the concept of radical honesty—a cornerstone of addiction recovery. Together, they explore how radically honest AI could pose less of a threat and help establish healthier boundaries around technology use. In this episode, we mention: Dr. Anna Lemble’s book “Dopamine Nation: Finding Balance in the Age of Indulgence”: https://www.amazon.com/Dopamine-Nation-Finding-Balance-Indulgence/dp/152474672X The forthcoming revised and updated 2nd edition of Robb Willson and Josh Tyson’s bestselling book,…

Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The free energy principle describes systems that pursue paths of least surprise, minimizing the difference between predictions based on their model of the world and their sense and associated perception. Dr. Thomas Parr is a practicing clinician and prominent researcher in the field of theoretical neuroscience and he currently works as an NIHR Academic Clinical Fellow in Neurology at the University of Oxford’s Nuffield Department of Clinical Neurosciences. He is also a co-author of Active Inference: The Free Energy Principle in Mind, Brain, and Behavior, written in collaboration with Giovanni Pezzulo and Karl J. Friston.  In this episode, we mention: Thomas Parr’s book “Active Inference: The Free Energy Principle in Mind, Brain, and Behavior (co-written with Giovanni Pezzulo and Karl J. Friston):…

Despite being a massive piece of the bigger AI puzzle, computer vision doesn’t always get the recognition it deserves. Robb and Josh welcome Dr. Jason Corso, Professor of Robotics at University of Michigan for an In Action episode that explores the complexity and power of machines that can see. Jason is the Co-Founder and Chief Science Officer of Voxel51, which is backed by Bessemer Venture Partners, and in this episode he demonstrates open-source tools available for working with massive datasets that include images and videos. The trio also discuss the border implication of adding the context that vision can afford to multi-agent systems. Explore Dr. Jason Corso’s Voxel51 platform: https://voxel51.com/ FiftyOne Open Source: Voxel51's open source toolkit for building high-quality datasets and computer vision models. FiftyOne Teams: Voxel51’s commercial offering based on open source FiftyOne. People can try FiftyOne at try.fiftyone.ai. Voxel51 on Github: https://github.com/voxel51/fiftyone A course on…

What’s it like to build an AI agent? Daniel Lametti, Associate Professor of Psycholinguistics at Acadia University, Visiting Fellow at the University of Oxford, and Senior Academic Advisor to OneReach.ai, returns to Invisible Machines to demonstrate how easy it can be to create and iterate on AI agents. Like other In Action episodes, you’ll watch as we walk through the practical realities of building these systems. This time, see how professor Daniel Lametti creates an objective-based AI agent that helps users craft and send emails. Though he’s hesitant to think of himself as one, conversational technologies have made Daniel a deft software developer. In this In Action episode, Daniel shares his experiences building AI agents with Robb and Josh. The trio discuss and show how coding languages are moving further into the background as machines become more adept at communicating in human language. Follow Daniel Lametti’s work: https://psychology.acadiau.ca/daniel-lametti.html Learn about orchestrating AI agents…

Robb and Josh are joined by Ed Klaris, Managing Partner at Klaris Law, Columbia Law professor, and CEO of KlarisIP, for a conversation about the fate of generative tools like LLMs and AI models that produce audio and video. From Ed’s viewpoint, giant tech companies used stolen content to train the powerful AI models that have quickly changed the world around us. The trio discuss the question of whether or not it’s lawful for us all to use generative AI tools and how IP and copyright law will impact, and be impacted by generative AI. As we wait for landmark decisions that will determine the fate of these tools, this conversation with Ed Klaris offers context and food for thought, and for some maybe even a sense of alarm. In this episode, we mention: The US Copyright Office: https://copyright.gov/ The Statute of Anne, also known as the Copyright Act 1710: https://en.wikipedia.org/wiki/Statute_of_Anne Google Books copyright case: https://en.wikipedia.org/wiki/Authors_Guild,_Inc._v._Google,_Inc. AIr Canada AI…

Jieun Kiaer is the Professor of Korean Linguistics at Oxford and her new book, The Future of Syntax: Asian Perspectives in an AI Age, explores the complexity within Chinese, Japanese, and Korean languages, arriving at insights that veer away from traditional approaches to formal syntax. The book also revisits Marc Prensky’s “digital native” concept, laying the groundwork for a new generation of technology users, “AI natives.” Jieun joins Robb and Josh for a conversation about the promise and peril of radical new technologies in classroom settings and how we might shift our focus to designing a positive future for AI natives. In this episode, we mention: Jieun Kiaer’s book “The Future of Syntax: Asian Perspectives in an AI Age”: https://www.bloomsbury.com/us/future-of-syntax-9781350258273/ Follow Jieun Kiaer’s work: https://www.ames.ox.ac.uk/people/jieun-kiaer Learn about orchestrating AI agents for your team:…

Marc Prensky is widely known for coining the terms “digital native” and “digital immigrant”—both now in the Oxford English Dictionary. In this episode, Marc joins Josh for a conversation about the shortcomings of our current education system and how AI might help inspire and enable a new generation of "AI natives" to design their own future. The two discuss the challenges that companies face in adjusting to this new technology paradigm, as well as the potential benefits and risks that conversant machines bring to society. As an eternal optimist, Marc shares his vision of how young people in the third millennium might view productivity and purpose. Marc and Josh also debate the role smartphones play in the classroom of the future, and agree that the world needs more love, empathy, gratitude, and optimism. In this episode, we mention: Marc Prensky’s book “Third Millennium Kids: A Hell Yes! Low Stress Guide For Everyone”: https://www.amazon.com/Third-Millennium-Kids-Stress-Everyone/dp/B0DC3J8XV6 Learn more…

With consumer use of AI technology outpacing enterprise adoption, the fear of companies using AI to get rid of employees has been flipped on its head into legitimate threat to the existence of companies as we know them. There’s nothing preventing consumers from using generative tools to disrupt large companies—for example, using a fleet of AI agents to flood and debilitate a call center to take advantage of a promotion. Harsha Gowda and Nitin Bhudia, respectively the CTO and Director of Innovation at Getronics, join Robb and Josh to discuss the risk organizations take by dragging their feet in the race for AI adoption. This conversation explores how organizations can embrace “artificial incompetence” as a necessary initial phase on the course to artificial intelligence, and seed the velocity that will transform their operations. By using AI agents to create an abstraction layer over existing solutions, organizations can take control of their futures. In this episode, we mention: The Invisible Machines…

Digital twins are critical to the orchestration of AI agents, providing the context they need to create meaningful experiences quickly and efficiently. Robb and Josh welcome Dr. Michael Grieves for a conversation about the origins of the concept, which he developed while working with NASA in the 2010s. The architecture required for orchestrating AI agents relies on different types of digital twins that may emerge within an organization, touching on physical elements, temporal data, and collections of unstructured data. Dr. Grieves joins the podcast to explore these connections, drawing from his book Product Lifecycle Management as well as his numerous scientific publications. The trio also discusses how something Michael calls “retirementitus” prevents organizations from embracing the sweeping technologies surrounding AI and digital twins. In this episode, we mention: Dr. Michael Grieves’ book “Product Lifecycle Management: Driving the Next Generation of Lean Thinking”:…

As AI agents continue to alter the way people interface with technology, Robb and Josh were eager to speak with journalist Matt Alston about his popular Business Insider article “Everyone hates Workday.” In this deep exploration of our multifaceted interactions with machines, Matt reminds us that Workday’s UX is different across a whole spectrum of users, and that generally speaking, people don’t like using software. The patterns we follow when operating software end up shaping our thinking, and as we move into a world dominated by conversational interfaces, it’s important to consider the way these systems are intertwined with our minds. Don’t miss this eye-opening episode about the future of project management. Learn more about creating and orchestrating AI agents to streamline your business operations: https://onereach.ai/ai-agents/?utm_source=soundcloud&utm_medium=social&utm_campaign=matt_alston_episode&utm_content=1 Article, “Everybody hates Workday”:…

As AI agents continue to remake the way we communicate with machines, what will become of SaaS companies? In this episode, Robb and Josh are joined by Janelle Teng, Vice President at Bessemer Venture Partners’ San Francisco office, who recently noted that “2024 has not been kind to SaaS companies” on her Next Big Teng blog. A Stanford scientist and former product manager at Salesforce, Janelle explains why she is bullish on the multi-agent approach to automation. The trio also discuss the ramification of consumer adoption of AI outpacing enterprises and why startups have a clear advantage in this moment. Discover how to design and orchestrate conversational AI agents for your employees and customers: https://onereach.ai/ai-agents/?utm_source=soundcloud&utm_medium=social&utm_campaign=janelle_teng_episode&utm_content=1 Read Jenelle’s insights at nextbigteng.substack.com. #AIPodcast #InvisibleMachines #AI #ArtificialIntelligence #ConversationalAI #AIAgents #SaaS #Automation #TechTrends #Innovation…

Sophie Bushwick is a regular contributor to Science Friday on NPR and has previously worked for Scientific American and Popular Science. As the Senior News Editor at New Scientist, she joined Robb and Josh in exploring anthropomorphism and AI. Sophie’s work reminds us that our introduction to pocket computers came with the heavily anthropomorphized Tamagotchi pets of the late '90s. As we head into the era of conversational machines, Sophie brings her insights to a conversation about the pros and cons of making them human-like across a whole range of scenarios, including those geared toward productivity and entertainment. The correlations and similarities between corporations and AI pose both ethical considerations as well as design challenges, and this discussion draws on Sophie’s extensive background in technology reporting to look for answers. Learn about orchestrating conversational AI agents for your team:…

Micro UIs are powerful interfaces built on-the-fly by. We've talked about micro UIs a lot on this podcast, as they are a critical component of AI agents, adding graphical functionalities to an automated conversational experience. Micro UIs let AI agents show users interactive elements—like maps, secure payment interfaces, dynamic graphs, and explainer videos—rather than just describing them. In this episode, we're joined by Cole Gentile, Solutions Designer at OneReach.ai, to demonstrate micro UIs in action. Create and orchestrate conversational AI agents: https://onereach.ai/ai-agents/?utm_source=soundcloud&utm_medium=social&utm_campaign=micro_uis_episode&utm_content=1 Number of monthly active WeChat users from 1st quarter 2014 to 1st quarter 2024: https://www.statista.com/statistics/255778/number-of-active-wechat-messenger-accounts "Organizational AGI is Coming — Most Companies Aren’t Prepared," an article by Robb Wilson, Co-Founder and CEO of OneReach.ai and Co-Author of the WSJ bestseller “Age of…

There are many lenses through which we can view the world, and that's especially true when considering the technologies associated with artificial intelligence. In this episode, James Bridle, author of Ways of Being, joins to explore a multitude of perspectives relating to our ongoing relationship with technology. James’ book explores the interplay between animals, plants, and machines in the search for planetary intelligence. James offers a broad vision of "thinking" systems that draws from biology, physics, and computation and spurs an investigation of what a corporation is and could become. Robb, Josh, and James have a dynamic discussion, trying on various lenses for viewing intelligence and uncovering new ideas about technology along the way. Learn about orchestrating conversational AI agents for your team: https://onereach.ai/ai-agents?utm_source=soundcloud&utm_medium=social&utm_campaign=intelligence_around_us_episode&utm_content=1 Get James' book, Ways of Being (Farrar, Straus and Giroux, 2022):…