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 service can last economically, and in Ben’s original frame, sustainably.

The asset is specific. A service blueprint used to die of its own detail: gorgeous, complete, and impossible for an organization to use. The useful version now comes in two fidelities. A compression humans can read and approve (finance, the business, the CEO with an A3 in a briefcase). A hydrated version agents can execute. Blend them and both audiences lose. Lavrans’s line: there is a design job and a build job, and when machines do more of the building, the blueprint becomes the system prompt.

Also in this episode:
Why people do not want seamless, they want the right friction (a UK student-loan team that refused to make the first big borrow feel fast;
an insurer that dropped “tell us what happened” and lost trust);
Why vanilla is a gift for public services and a nightmare for a brand;
A European telco whose sales director would not believe that 60 percent of store visits were service; why the CEO has to own the blueprint (including the one outside Brian Chesky’s office);
Why you start with nurses and frontline staff, not the customer poster;
A live simulation of Norway’s alcohol regulations, where removing the application saved thousands of hours and immediately billed the savings to police and healthcare.

LINKS:
Service Design: From Insight to Implementation

Service Design for Business: A Practical Guide to Optimizing the Customer Experience

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This episode is supported by OneReach.ai

Forged over a decade of RD and proven in 10,000+ deployments, OneReach.ai's GSX is the first complete AI agent runtime environment (circa 2019 — a hardened AI agent architecture for enterprise control and scale.

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

Reach out to OneReach

--------- The revised and significantly updated second edition of our bestselling book about succeeding with AI agents, Age of Invisible Machines, is available everywhere: Amazon

#ServiceDesign
#ServiceBlueprint
#AI
#AIAgents
#AgenticAI
#CustomerExperience
#DigitalTransformation
#InvisibleMachines

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 perfection or ignores the tool is making the same mistake; proximal empathy (you cannot be a tourist); San Francisco vs Topeka as scaffolding, not IQ; individuals using AI at the micro level while companies keep the wrong business model; furniture makers who should have become designers; you are the circumstances; toolmakers selling screwdrivers vs FedEx selling a whole solution; constraints as a gift (“you can’t think outside the box—it’s very dark out there”); false proxies like counting tokens (IBM already learned this with lines of code); empathy-based compromise vs the compromise of average; and a future of AI that is networked, not solo.

Guest: Seth Godin—The Knot: Problems Can Be Solved
Hosts: Josh Tyson, Robb Wilson—Invisible Machines

The Knot is available now!

Prior visit: S1E14 — Seth Godin on The Song of Significance

#SethGodin #TheKnot #InvisibleMachines #AI #AgenticAI #Leadership #FutureOfWork #Marketing

--------- Support our show by supporting our sponsors

This episode is supported by OneReach.ai

Forged over a decade of RD and proven in 10,000+ deployments, OneReach.ai's GSX is the first complete AI agent runtime environment (circa 2019 — a hardened AI agent architecture for enterprise control and scale.

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

Get in touch!

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 on-ramp is Jonathan Frankle’s smoothie: fusion-grade intelligence, no power lines. The existence proof is the 787. Seventy applications, twenty-plus suppliers, no manual option, an execution envelope that keeps the ride consistent long before the guardrails that keep the plane from crashing. You cannot trust the orchestratee to be the orchestrator. You cannot search a new recipe every time. And if you built it as a kitchen smoothie, then the organization started depending on it, you do not get to patch. You start over.

We cover: why mission-critical agentic orchestration only sounds like an oxymoron, the railroad / hovercraft / cars-on-roads hybrid, envelope versus guardrails, the five decision patterns every production system already contains, and the question that opens episode two—do we trust it?

Definition: Agentic orchestration is how you meet an objective with a hybrid of code and probabilistic systems—inside an envelope that stays consistent, even when the path through it is not on rails.

Gartner (map, not curriculum): https://www.gartner.com/reviews/market/ai-agent-management-platforms BOAT Magic Quadrant (15 Oct 2025) Emerging Tech (27 Jan 2026): Enterprise AI Will Fail to Scale Without Agentic Orchestration Platforms

Hosts: Josh Tyson and Robb Wilson, co-authors of Age of Invisible Machines

#AgenticOrchestration #AIAgents #InvisibleMachines #787 #MissionCritical #AgenticAI #UXDesign #Gartner #OneReach #Databricks

--------- Support our show by supporting our sponsors

This episode is supported by OneReach.ai

Forged over a decade of RD and proven in 10,000+ deployments, OneReach.ai's GSX is the first complete AI agent runtime environment (circa 2019 — a hardened AI agent architecture for enterprise control and scale.

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

Get in touch:
https://onereach.ai/contact/?utm_source=soundcloud&utm_medium=social&utm_campaign=s7e17&utm_content=1

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 → peak loops as the tech moves faster than before);
Organizational bullwhip vs organic individual use;
Fear as brakes on the system;
Crisis engineering and the plans that are lying around;
The risk that AI in the hands of people eliminates companies before AI in companies eliminates jobs;
Machine customers and retailers already blocking agent access while Amazon’s Buy for Me goes outside the walls;
Agents that work for you vs agents that work for the vendor;
Human brand vs machine brand;
Service design and customer effort score;
Frontline managers as the linchpin; and
The next research wave Don names at the close: implementation platforms, ethics, and safeguards.

When Machines Become Customers (book): https://www.gartner.com/en/publications/when-machines-become-customers
Customers Don’t Reject AI...They Reject Being Dehumanized: https://www.youtube.com/watch?v=x6ZqXVXRWIw

--------- Support our show by supporting our sponsors

This episode is supported by OneReach.ai

Forged over a decade of RD and proven in 10,000+ deployments, OneReach.ai's GSX is the first complete AI agent runtime environment (circa 2019 — a hardened AI agent architecture for enterprise control and scale.

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

Get in touch:
https://onereach.ai/contact/?utm_source=soundcloud&utm_medium=social&utm_campaign=s7e16&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

#GenerativeAI
#AIAdoption
#MachineCustomers
##AIInEcommerce
#AIAgents
#DigitalTransformation
#FutureOfWork
#BusinessStrategy
#InvisibleMachines

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 fifty-five use cases exactly as humans do them today, then acting surprised when nothing compounds. Evan’s answer is a two-step path that respects how messy humans actually are: first compress low-value work into AI for a confidence-building lift; then rethink the whole iterative cycle for asymmetric returns.

Also, learn why “no change without pain” isn’t cynicism, why POCs love moving goalposts, why big enterprises optimize one segment and break the connective tissue upstream, and why the scarcest resource won’t be another prompt library—it’ll be people who can think about constraints.

We cover: AI stewardship and the inverse-pyramid skill set, outcome vs output, structure-before-feature development, the two-step adoption path, risk-averse vs innovator cultures, SMB speed vs mid-market discipline vs enterprise battleships, critical vs non-critical systems, and why cutting headcount first is how you donate your newly trained stewards to your competitor.

Guest: Evan J. Schwartz, Chief Innovation Officer, AMCS Group; Adjunct Professor, Jacksonville University

Hosts: Josh Tyson, Robb Wilson

--------- Support our show by supporting our sponsors

This episode is supported by OneReach.ai

Forged over a decade of RD and proven in 10,000+ deployments, OneReach.ai's GSX is the first complete AI agent runtime environment (circa 2019 — a hardened AI agent architecture for enterprise control and scale.

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

Get in touch:
https://onereach.ai/contact/?utm_source=Soundcloud&utm_medium=social&utm_campaign=s7e15&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

#InvisibleMachines
#Podcast
#TechPodcast
#AIPodcast
#AI
#AgenticAI
#AIAgents
#AIAdoption
#Leadership
#OrganizationalDesign
#CoCreation
#FutureOfWork