Prefer audio? Listen anywhere
The railroad invented the modern management system 150 years ago. AI just made every assumption obsolete.
Every leader I talk to knows something has to change. They see AI coming. They understand the stakes.
But nobody's pulling the real trigger.
The playbook carved into org charts 150 years ago assumes your people can't make decisions, don't have context, can't think through consequences. That made sense with just a pocket watch and train schedule.
Now? AI plus your average AI-enabled employee outperforms most non-AI executives. Within five years, these technologies will be 30 times better. You'll have a thousand Einstein-level minds in your organization.
Would you tell Einstein what to do?
Jonathan Brill has spent his career studying why some organizations adapt and others go extinct. His message: we're in the middle of a meteoric event. Just like 66 million years ago when rigid creatures died and adaptable ones survived, companies clinging to industrial-age hierarchies won't make it.
World's leading futurist (Forbes). Currently Futurist-in-Residence at Amazon, Head of Invention at Deepinvent.ai, Executive Chairman of the Center for Radical Change. His teams built 350+ products generating tens of billions in revenue. He advises governments, multinationals, and frontier tech companies. His latest book, "AI and the Octopus Organization," opens with an extinction event - because the patterns repeat.
🚀 KEY INSIGHTS
✅ The railroad assumptions that run your company—and why they just broke
In the 1850s, railroads organized around three realities: no real-time feedback, no judgment calls, no visibility into systemic impacts. Top-down control was the only option. AI obliterates every assumption. Your people now have state-level simulation systems in their pockets. Yet we're organizing like it's 1855.
✅ The governance trap: when competitive advantage requires moving before the board meeting
When someone can do three days of work in 45 minutes, you can't wait for strategy approval. You have to execute first, figure out strategy later. Junior people spot opportunities. Senior leaders scale them up. The pyramid flips. But boards still expect quarterly planning, strategy approval, risk frameworks. The window to monetize innovation shrinks faster than governance adapts.
✅ What leadership traits win in transformational times?
Analysis of 2.7 million leadership surveys: only 1 in 7 managers outperformed during disruption. Not the smartest or most experienced. Those with specific behaviors. The LUCK framework: Leverage help from peers. Use diverse connections. Control chaos by going to first principles. Know what's missing by asking counterfactual questions. They didn't work harder. They changed how luck works.
✅ When a junior employee manages 1,000 AI agents—what happens to management?
A junior employee managing 5 AI agents is suddenly in as complex environment as a traditional team leader. At 50, department head level. At 1,000, GM-level. Middle managers become rapid-response specialists: bubbling up edge cases, distributing solutions, orchestrating exceptions. Senior management needs "octopus vision" - surgical precision on specific problems while other tentacles operate autonomously. The hierarchy inverts. Information flows bottom-up.
LinkedIn: linkedin.com/jgronstedt
ThinkRoom Podcast www.thinkroompodcast.com
GRAIL www.grail.works
Read the full transcript
By this point, I feel that we've all kind of figured out that the problem with AI implementation isn't really technical. It's more organizational. The hard part is getting your organization to actually unlock the real potential value in ai. And here I'm not talking about slapping AI onto some legacy process to get some 10% efficiency gain that will be just priced into the market in six months.
I'm talking about innovation. But in order to get there, we quickly realized that we need to rewire mostly everything we knew about leadership and organization, and that's difficult. Therefore, I'm really proud today to, welcome Jonathan Brill. He has a thing or two to say about this topic. He's been named the world's leading futurist by Forbes Magazine.
He's the futurist in resident at Amazon, has been the global futurist for hp, and he just released a new book called AI and the Octopus Organization. What I love with speaking to innovators like Jonathan is that they. Truly understand historical patterns. They understand technology and they understand the organizational resistance and all of the dynamics that are the more human facets of this change.
Today's episode is also sponsored by Grail, and if you want to implement the type of thinking that we are discussing here on today's podcast, then head over to Grail Works to find out how. Now let's move to the episode.
Jonathan Brill, welcome.
It's amazing to be here.
For those who don't know your work, can you kind of elaborate?
What is it, what is it that you do and why does that feel interesting and important?
So, my name is Jonathan Brill. I am a business futurist. I do a lot of keynote speaking. I write books, uh, and I advise C-Suites and, um, security services around the world. My job is to help you understand what is that world that you're gonna be operating in five years from now?
Where do you need to be positioned in the next three? What are the investments to make today, and what are the mindsets that make this all possible?
Your latest book, the Octopus Organization, you begin with an extinction event 66 million years ago, and, and you're not the first innovator that I've, uh, spoken to.
You all seem to be kind of obsessed with history, uh, finding, repeating patterns and so forth. Can you elaborate? What is that extinction event? How does that make sense in the age of ai? And what can we learn from, from kind of the repeating patterns of history?
So I recently wrote a book called the AI and the Octopus Organization with someone named Steve Wonker.
And what we look at is. What happens when the world changes? How do organizations work differently? We open the book talking about this moment, 66 million years ago when a meteor hits the earth and all of a sudden, every animal, every plant on the planet is in a new competitive environment. And, and why do some thrive and why do some fail?
And we, we look at the octopus and, and this is amazing creature that, that, well, many of the, the major sea creatures, the, the ammonite for instance, were decimated the octopus life because it was able to recode its RNA, it was able to redesign the way it worked. And in the world of artificial intelligence, we're moving into one of those meteoric events.
It's going to shift the nature of firms. It's going to shift the way we work. It's gonna shift the way we compete, and we can learn a whole lot from deep history, from the breadth of nature about what types of strategies, what types of organizational structures work. And the thing about the octopus that is unique or different from many animals is you and I, we have a centralized mind.
We've got a big brain up here that tells us what to do. The octopus has a distributed mind when you look at the tentacles, each one's going this way or that way, so on and so forth. And then all of a sudden it starts to coordinate and then all of a sudden, boom. It changes action. It goes somewhere else.
It's this crazy ballet from randomness to precision. And what goes on there is that the tentacles are actually thinking, looking, exploring separately. And when one finds something, the neural tissue pushes up information into what are called the shoulders of each tentacle of the octopus, each of arm of the octopus.
And they talk to each other and they coordinate. And then they tell the big brain what they've just done. Hmm. And so wh in the octopus is that instead of information, decisions going from the top down, they go from the bottom up. And it turns out to be an incredibly efficient way of innovating when it's impossible to tell.
Your people what to do because you have to innovate too quickly. And that's the world that AI is moving us into. It's dramatically accelerating the pace of innovation.
Yeah, that's interesting. And you can quite clearly see kind of the link to, to the industrial age organization being very much top down.
And I would assume that that's kind of the continuation of the argument. Can you elaborate? How does this impact the way that we organize work today?
Yeah, so we've been organizing businesses the same way since the 1850s. The first organizational chart was printed in 1855 by the New York and Erie Railroad, and there were several assumptions in 1855 that AI makes untrue.
The first is that people did not, in general, have skill at making executive decisions. AI plus. Your average employee are going to be a dramatically better decision maker than most executives today. Two, that they didn't have contexts. Uh, Alfred, I, I'm sorry. Um, Thomas Edison was involved in a train accident, early Anna's career as a telegraph operator because there was an engineer who had the schedule for the trains, but his pocket watch was off by four minutes.
Mm-hmm. That was all of the information they had to run, like, you know, interstate, like, you know, nation level systems, like a pocket watch and, and, and a calendar. Um, with the world of ai, everybody has access to all of the information in the organization at the same time. Context changes. And then the third piece is because historically you didn't know.
What was going on or how to make decisions. It was very hard to think through what would be the second and third or order impacts of the actions that you took. AI may or may not always give you the same answer, but it is excellent at helping you work through scenarios because that's what it does. It's a probability engine.
Hmm. And so every single person in your organization is going to have state level simulation systems in their pocket. And we aren't talking about it in 2040, we're talking about in the next two years. Wow.
Yeah.
It doesn't like, it's interesting. I, I do feel that we, we can all see this change on the horizon, personally and with the companies I work with, yet there's been no reorganization of, uh, a pivot towards aggressively more decentralized decision making, for example.
What do you think that is? What, why is the lag so big?
Well, we've been talking about it, right? We've been talking about it for 20 years in academia. We've been showing the potential of these things. We've been talking about how to build psychologically safe organizations so that everybody can be more innovative.
The problem is that leaders, you know, they, they don't have, you know, information in real time about what's going on. And so giving up control is very dangerous. Hmm. Uh, the amount of effort that goes into managing innovation is much higher than the amount of effort that goes into controlling, you know, rationalized organizations.
Um, and so there's a disinterest in doing it. The question to ask is, in a world where. Process after process, workflow after workflow starts to see automation in it. And that automation comes from junior people having an idea that we need to rethink the innovation process. Not because we need to be more innovative, but because the window in which you can monetize that innovation is about to shrink.
Why is
that?
We,
. If you go back 25 years, you know, we had strategy and then we had execution. We had freeze of thaw. Last 25 years, it's been about this idea of strategy execution. We do both at the same time. Hmm. In a world where your person can do what would be three days of work today in 45 minutes.
Ai, ai. And there are examples I can give you of things we're doing where that is true. All of a sudden you have to do execution before you have a coherent strategy. And that's increasingly going to be the case. And so the reason we need to make this shift is that in order to get ahead of competition, competition, in order to move at the speed of customers, we need to shift from strategy and then execution to strategy, execution to this world of execution.
And then strategy. It's a wild thing to be thinking about.
Is strategy obsolete or, or what? What is the definition of strategy in that world?
Well,
I think it's about organizational frame.
Okay. Capabilities,
almost the capabilities that you can reorganize. And how do you think through that ability to reorganize the structure?
Um. So I don't know that strategy goes away, but it becomes much more of a meta thing. Mm. Is what are my cluster of assets and processes? You know, what is my architecture as a firm? How do I build a culture that makes this all possible? Hmm.
How does this look in practice? I say that we fundamentally run a very fluid innovation focused distri distributed in decision power organization.
What does that look like? What, what roles are different? Are there managers? What do they do differently by that point?
So, uh, when you think about the middle manager today, the primary role is quality assurance, right? And process control. I think that continues, but it's a very different situation where it's not about so much designing the processes as dealing, uh, with the edge cases, right?
Like. If the processes are coherent, a lot of that's gonna get automated. Um, if the processes, you know, if you have an information based business, um, the, the question to ask is really about that, that second piece, how do you deal with the edge cases? How do you become aware of it? How do you make sure they're getting bubbled up?
How do you make sure that, that when people have a solution to it, that knowledge is distributed as quickly as possible? Hmm. Those, I think are, are things we're under imagining. Right? I don't think the role of the middle manager goes away, uh, or the objective. I think the way you achieve it changes pretty radically.
And how do you achieve it? What, what's the, what's the everyday work day of, um, middle manager of the future?
Sure. I, I think it is making, like I said, you know, making sure that those edge cases get bubbled up. I think they have a lot more, uh. They're dealing with a lot more process complexity, you know?
Mm-hmm. It's easy to imagine a world where, you know, you might have a junior person that's not managing a thousand people, but they're managing a thousand AI bots. Yep. You know, the, the process complexity, you know, of, of a junior manager, of a middle manager might be the, the same as, uh, a, a, a GM today.
Right. And that's what we've gotta be thinking about is like, how do we train these people to think, uh, at that level of complexity?
Yeah. It's fundamentally interesting. So if we assume that the employee level has to intelligence of a genius, that role changes a lot. Uh, and the capabilities of that role, and especially if you provide a lot of context as you said, I think one of the things that's interesting with strategy is, is how can we leverage our.
Unfair advantages. So, so that, that historically has been a lot about putting a lot of resources behind, a few big bets and, and coherently executing on, on those. Do you think that that won't be necessarily the way that strategy fundamentally works in the future? It's, it's more about a gazillion micro bets in a, in a distributed system, or how do you see that playing out?
I think it's probably different for, for every organization.
Yeah.
But what you know is that the architecture for making those micro bets, the corporate architecture is different, right? Mm-hmm. The corporate architecture for, uh, the, the processes for managing that, that range of, uh. Optionality is very different than, like you said, we're gonna make one big bet.
Uh, and and the culture in which you do that, where you have like, let's say a 70% failure rate, that's very, very different. Yeah, absolutely. And it looks a lot more like a research lab than it does, you know, a, a, a paper factory. Hmm. And gotta start thinking about, okay, how do we bring these things together, not just technically, right.
How do we do the transformation, but culturally, right. How do we build a culture where we, we, where we have that coherence, we have that consistency. Hmm. Right. But we're able, and we're willing to take dramatically more risk because we have new ways to manage it.
Yeah. You talked about a, a rapid sensing system in the book.
Uh, I would assume that that ties into the ability to see risk and manage risk. Can you lay out the, the, the argument.
One of the reasons why senior management holds on to control is because middle management doesn't pass the information through.
You get this game of telephone where one person says one thing and another says another. By the time, you know, you, you get from the bottom to the top. Black is white and, and red is blue. And, and so we need to have today that kind of process control, um, in our organizations. But in a world where you can look down into whatever's going on, you know, all of a sudden you don't, you don't, you can give up a lot of control because.
You don't need it to sustain, to maintain command. Hmm. When you look at the octopus, something really interesting happens, which is it's got the, the eight tentacles out there, but, and they're all operating individually. And, and, and occasionally one eye will go and look at a tentacle. We'll take control of that tentacle for a few moments, try and go and get the fish or whatever it's trying to do.
But the other seven are operating on their own. And so how do we think about an organization where you can drop in with that level of precision, that level of control, say it's something interesting over there. It's, it's focused on that. Um, it's a different way of thinking, right? But when you have access, you know, when your junior person has access to all this information and all this ability to innovate, that means that you.
And so we need these early, these rapid sensing systems that allow us to get ahead of the changes in the environment, right? That allow us to get ahead of, you know, crazy ideas. Um, and yet free people up to have them and execute against them.
If you've been listening to this podcast for some time, you know what I think about ai. I'm deeply excited about it, but I also see companies struggle with it, and you know that I think it's not primarily due to technical reasons compared to. Previous revolutions, let's call it the internet wave. Part of why we struggled initiative initially was that, well, the infrastructure wasn't built out.
We didn't have online credit card payments and whatnot. But the difference with AI is that the infrastructure is already here. The technology is so much more capable than we actually use it right now. And the problem for most C-suites that I talk to CEOs and senior managers is that they actually, they know about the importance of ai.
But they can't seem to get to that position where they truly understand how is make, how is AI making me fundamentally more competitive? I understand that it can save costs hours here and there increase some, some productivity number, but how do I distinguish myself on my market, like the ones that that truly survived?
The digitalization era wasn't a bookstore that got a website, it was the Amazons of the world. So where you truly find the transformation of what we do today and how can we unlock things, serve customers that we never could, do innovations that weren't ever before practical, that type of innovation. The primary problem that I see in all honesty is that the C-suite.
You don't really understand the technology and not understanding the technology for the sake of understanding the technology, but for the sake of having a strategic discussion. So that's why I started Grail. I stand right smack tab in the middle of I understand the technology. I understand strategy and execution and bringing these two together is what we do at Grail.
So if you understand that this is something that needs to happen, then we should talk. Thing is slots for this. Spring is already filling up. Grail has been in the work. For some time. So I've already had engagement for the spring. Well, what I'm looking for is that one CEO in each market that truly wants to make a dent in the universe.
So if you're that guy or that girl, please head over to Grail that works and let's talk.
What's the timeline, do you think, uh, where this will play out?
The winners and the losers will become apparent?
It's, it's a, it's a bit of a challenge to say, but, you know, I think there's this conversation about, well, AI hasn't paid out. Yeah, exactly. 95% of pilots, et cetera, et cetera. Yeah. Yeah. But, but like a, that study that we're talking about from MIT, there's, there's methodological issues with it.
Yeah. But the second thing is. This technology is evolving so quickly depending on how you calculate it. It's improving by about seven times a year, and there's every reason to think the next few years that will continue, and I think out to the next five, it's a pretty good bet. So we're talking about it like conservatively these technologies getting 30 times better than they're today.
32 times better than they're today. Right. And I don't think organizations are really considering, like you said, what happens with, with, you know, an employee plus ai. You've got a thousand Einsteins in your organization. Yeah, right. Like probably not a good idea to tell Einstein Invent.
It's also exciting because it makes, fundamentally what are, what are the problems that we could tackle? Because I see a lot of, of companies mostly slapping AI onto existing legacy processes and, and win some five, 10% productivity gain within a specific department. But you fundamentally do the same thing that you did yesterday, just more efficiently.
I think that will just, the, the market would factor that in. And then there's, uh, a new price floor that's just expected in, in the pricing and like, what did that actually get you? But what's more exciting to me is like all of the things that didn't make economic sense before, but suddenly they do. Right.
Yeah. And I, I think that's the, the, the fascinating thing that, you know. We're gonna see, I think at the back half of 20, 26, some, some economic value. There's gonna be, not, not like Klarna goes out there and has some edge case, like we're getting all ai, but, but like larger organizations start to see some success.
20 28, 20 29, you know, you start to see the measurable economic value. I think that's probably about what it looks like, you know, and maybe I'm off by a year, right? But I don't think anybody's who's serious is looking at it 2035 and thinking the world isn't fundamentally different, that the economy money system aren't fundamentally different.
So that, that's kind of maybe answers some of the question for you about how long, but the, the, the next question is about, you know, what, what would you do differently?
Yeah. You,
when I think about, you know, a company like Lovable, you know, a hundred million dollars a RR in eight months, you think they're operating their sales organization like you are yours.
Hmm.
I met them when I was in San Francisco when I was trying to have this conversation live with you when you ended up going to Mexico. But, uh, yeah, it's super exciting. They fundamentally play a different game, but it's also interesting because they've built it from the ground up in this new logic, like most of, at least this audience that we're speaking to are not in that position.
They have all of the legacy processes and all of the staff that are trained and scaled within that set of processes. Right.
And, and this is the challenge, right? Yeah. Is it's, is it's a, it's a heart transplant.
Yeah.
Uh, on, on, you know, on a live patient. And so the question really is how do we do this?
And I think that. If you, if you're serious about it and you think about shifting an architecture, you do an m and a, right? You wanna shift the corporate architecture, bring new people in. It's like a two year political process to do that, right? S will say it's 90 days, right? But it's like two years, right?
Just to get all the right people in the right place. If you wanna bring in SAP or Oracle, it shipped out a, a major business function. It's about a three year process, right? It's a year to plan a politic, a year to do it, year to fix everything you just broke. No one has ever disagreed with those numbers, by the way.
Nobody who's gone through the transformation of bringing on SAP
and they're like, you're being conservative. Um, the shift of a culture though, there are people like Benham Re who say, Hey, you can do this in 90 days or six months. My experience has been that you need to. Raise up or put out every single leader in the organization.
Right. And that's typically about a seven year process to churn an entire C-suite. Hmm. Um, that's the world that we're talking about. And so if you believe that in 2030 the world's fundamentally different in terms of how it operates, 2032, you pick your number, it doesn't really, the question, the question is when are you gonna start doing the culture change?
Because you have time to do the stuff, but you don't have time to do the culture shift if you wanna compete with the lovable in your industry.
Hmm. What's the first step? Say, say that you are the, the CEO of a, a mid-market company to billion dollar revenue. What are the, the steps that you actually begin with?
I, I think, like I said, it, it starts with the culture side and in the economy we've kind of come up with a number of things that, that innovative organizations tend to do more of. We did a study of 2.7 million managers, million about why some are more lucky and times have changed than others. Mm-hmm. It turns out it's not chance.
Right. We all know this. There's always somebody in our lives who always lands on their feet. Yeah. What, what are they doing differently? And if we want our people to be more innovative and think like senior leaders earlier in their career, how do we teach them how to do that? Yes. Right. And, and it comes down to four things.
They, they leverage help from their peers more than their peers. They make more unexpected connections. They are more economically, socioeconomically connected. To a range of, of, of people in, in economic strata. They're more connected across industry. This is really important because as a senior leader, you probably do some of this, right?
You ask for a lot more help from your peers. Maybe you're a mastermind, maybe you know, you, you're, you're at the golf club, but you're always listening and leveraging. Hmm. The second thing is that you're out at the golf club. You're always listening and leveraging, right? You're broadening that connectivity.
Today we've had our people focused on their computer screens working harder, harder, harder, harder, harder, harder, harder, harder. That's still important, but Well, one of the things we need to do is think about, okay, well how do we get our people out of the office? How do we get our people out, their context?
How do we get our their people out of their comfort zone? Because that's where your potential increases. Not like 3% a year, but 3,300, right? Mm. It's those break moments that senior leaders are good at because they're in that broader context. The third thing is about controlling chaos. The standard operating procedures, statistical process controls, work in situations where there are processes that are consistent enough to manage statistically, yeah.
World I'm talking about and the world of senior leaders. Man, it's all edge cases all the time. Hmm. And the challenge is how do you enable more junior people to think from a first principal's perspective, right? About what is this risk? What is this challenge? How am I gonna innovate against it? How am I gonna manage that?
This downstream impacts? These are senior level ways of thinking.
Hmm.
We need to get that. If, if the people are more junior are gonna be dealing with more process complexity. We need to get that down into our organizations much earlier in career. And then the last piece is taking the time to know what's missing, right?
As a senior leader, having an instant opinion is often a terrible idea, right?
What you do, if you want to get breadth in the decision making is you do not say things until the end. Right, the time to listen, to diagnose, to think about what's not there, to think about what's missing. And so they take the time to know what's missing.
So they leverage help, unexpected connections, they control chaos and they know what's missing. That leads to a really convenient acronym block. Yeah. It also provides a really simple way to start thinking about, okay, well what's, how do I help this person think like a more senior leader today?
There's an interesting opportunity to develop if you're a, a leadership training kind or if you're a large company, to develop your own kind of training agents for this.
Uh, so I have this interesting, uh. Case that I'm building out now for, for, um, for one company. So you'd capture, so this would be for, it's a consultancy company, so it would be for their sales staff and for their, um, advisory staff. So we tra uh, capture transcripts. Um, and besides just making the follow ups and, and all of that stuff that, that the tools do outta the box, we also run the transcripts through a specific set of analysis looking for specifically that what would be the feedback of a manager, for example, and then we automatically ping the sales person or the advisor with, like, feedback afterwards.
So I think there's opportunity to kind of build these systems where we scale the training of these new second order or, or first principle thinking or whatever it might be. Yeah.
Yeah. I, I think it's the only way to do it because the reality, you know, the reason, one of the reasons why we don't superpower.
Staff is that, you know, if you're a middle manager and you're already working 40, 50 hours a week and you've got 50 people, well putting an hour a week into each of those people is your entire job. But putting three hours a week of AI into those people, yeah. That's one of the things we, we don't do today.
Right. Just because it, the economics don't make sense.
It's funny, this idea actually came from, I have a sales director friend, he came up with this original idea based on the concept. I want to be less in meetings, but how can I kind of provide the value that I would normally do in a meeting, but more automated?
Right. Well, when I was a middle manager, I was spending 65% of my time in alignment meetings. Yeah. And like that's, just think about that. It wasn't even my, my job description.
No. It was the majority of my work. It was absolutely insane. And when I would explain this to my boss, he'd be like, well, that's just the way it's,
Hmm.
I think I've read a study that said 74 in, in large companies, 74% of time goes to meetings and only 20% of those meetings are perceived as valuable. Like if we talk about the, the future of work and, and like, what do we need to fix and what does this brave new world look like with ai? Like, that's square in the middle of what I wanna stop doing as my job description, sitting on Zoom meetings and, and having boring, non-value creating meetings.
Absolutely.
What do you see the, the kind of big consultancy firms, obviously they're building up massive AI transformation offices and so forth, uh, the, the McKinsey and so forth, what are they doing right at this moment and, and what's kind of missing in the market?
I, I think it's about, you know, the first thing is the culture change, right? Yeah's, a piece that you can do yourself is the piece that requires someone to come in from the outside.
Um. I think that's gonna be really important. The second piece is that the way we've done digital transformation today is there's some person at the top who has an opinion and there's a whole bunch of people at the bottom who have to deal with the outcomes of, of that implementation. And you know, like this, this is the thing that blows me away, right?
Companies like Accenture say, Hey, there's 70, 85% failure rate on these things we do.
Yeah.
Think about that. Their job is to be like, we're gonna be successful. And they, they're saying that like the edge case is that these things are successful. Um, the reason I think is often that that top down transformation doesn't work at the end of the day.
It's the people at the bottom that need to use the tools.
Yeah, I think it's a continuing patterns. What we saw, I feel a lot around the digital transformations is that you approach it as a technical problem. Where it's fundamentally mostly a human problem, and it's just an amplified effect. Now with ai, I see the same thing.
Yeah. You, you try to hire a chief AI officer to delegate the problem, right. Not understand that fundamentally, your whole business, your whole culture, your whole organization needs to change.
Yeah. I, I think that's, that's absolutely, uh, absolutely right. This isn't a technological problem, it's a sociological problem.
Hmm. Uh, the, the within that the questions are, you know, about how we actually do that, right? How do we actually make this shift? And, and what do we insource, what do we outsource at the end of the day, you know what's interesting about. AI is because of the rate of change. It's the junior people who are going to find the opportunities if you let them, and as a senior leader, you can look down into the organization and see where the opportunities are in real time and help them scale up.
Hmm. Right. So we're, we're inverting the process pyramid, right. From one that's top down to one that's bottom up. And that's a, that's a shift, right? Because, you know, senior leaders don't wanna give up control. This is very scary. This is what I've been doing the last 20 years, is becoming a good decision maker.
Um, and the junior people are suddenly gonna be saying, but I can do it now. Yeah. I've got the skills. Why, why aren't you, why aren't you delegating me? Right. Is that, that sociological challenge of, of being willing to allow your people to innovate on your behalf? And accept the failure rates. Accept the, the, the challenges.
Uh, try and find ways to make people more comfortable with the uncertainty and the fear that comes with taking risk. And that, that's, that's your, that's your job as a leader today.
I completely agree. And if we assume it's correct, and I, I completely agree with that. I think it's correct. It's a human problem.
It's a sociological problem. Part of what I think we're under investing in as managers right now is we need the storytelling of not what are we building, but who are we becoming? That's like, what are we aiming for? That positive mental image of this is how it looks for you, the, the whatever level employee when you go to work in two, three years.
And getting that to an exciting, uh, place to wanna, uh, come towards. Right, right, right. And I see very little of that type of storytelling. I see the kind of six months storytelling. Right now, what I'm talking about is kind of the three year vision of, of where are we then.
Yeah. And I, I think it, and, and what, like you said, like what role do you play?
Um, I was talking with Amy Edmondson a while back, so she's the woman who coined the term psychological safety. Hmm. And she said, you know, here's the thing. People will do almost anything with you if they know that we're in this together. Hmm. And the challenge, the story that I hear is, Hey, you know, executive assistants are going away, customer support is going away, blah, blah, blah, blah, blah, blah, blah, blah, blah.
A I'm not sure they can completely believe it. There's not a lot of evidence that there's a lot of job reduction. There's, there's certainly gonna be a lot of task automation. Yeah. There's, you know, to, to automate a job, you need to automate all the tasks. There's not a lot of evidence that's gonna happen quickly.
So, you know, we're gonna figure out where the value is in the people we have from the jobs we do, but we're gonna be reallocating time. Hmm. For the next several years. And so, and so, like the story about, okay, well what does that look like? How do you do more, how do you do more effective? How do we create a world where you're getting out of the office Hmm.
Instead being stuck in the cubicle. Right. How do we create a world where, uh, people are. More collaborative, you know, like, and, and people are having more fun together. Um, how do we create a world where you have more autonomy? Hmm. You know, and these are things that I personally happen to value a lot, um, is gonna be challenged, oftentimes convincing other people to value them.
But we do need to tell that story of there's a place for you if you wanna play the game.
Yeah. I, I've talked to innovators in the past that, that has brought up an interesting kind of intersection between the value of play and innovation. Have you looked at this?
Tell, tell me more.
So, uh, the, the core idea is that.
If you think about it from the perspective of, um, um, improv theater for example, uh, there, there's this very playful but also extremely creative and innovative way of, of kind of telling that story and building something together. But it only works if we're fundamentally collaborating in, in the kind of playful, playful environment.
And what happens when companies go through a lot of change is that they don't feel that they have the resources or the time to be kind of playful with it. Everything feels life and death. So you start to decrease the amount of playfulness that you have in your kind of in culture, which is the exact opposite of, of what you probably should do.
And I think this connects probably to your being fine with that. Many of the experiments that will run would probably not lead anywhere, but the few that do will be game changing. And, and it's coming back to this idea of. The culture change is at the kind of epicenter of being successful or not.
I, I, I completely agree with everything you're saying, and it, it's, as a manager, it's really easy to, to look at like, okay, well how do we make sure that all of this experimentation rolls up into anything bigger?
Right? How do we make sure that all of this in this innovation, you know, and all of these different business groups roll up to something bigger, right? That's part of your job is, you know, to make sure you have visibility into what's happening so that you can give up control, because at the end of it, you still are responsible for that.
That's your core responsibility is make sure that these small pieces turn into a bigger hole. It's just a lot less telling people what those pieces should be. Hmm. That's, that's the shift. So, so I think the first thing is, yes, a lot more play, a lot more experimentation, you know, a lot more creativity.
We've talked before about this concept called rizz. This is a weird germ, uh, Russian. Love that.
It was so Russian. Interesting. Russian,
yeah. Go for it.
So this, there's this, uh, Russian, um, Russian, uh, engineer, I think mathematician engineer who came up with this, that he, he basically came up with every way to have a new idea and, and like every pattern for solving problems.
And the problem is you have to be a very, very, on the spectrum, uh, Russian mathematician engineer to use this thing. The thing is that AI makes it really easy. It's called Tris, TRIZ. And you ask it to be an expert at Tris and, and help me innovate, think through this problem. What, what are the challenges?
How, what do you think through it? What are the workflows? And it turns out that it's incredibly good creative partner, play partner that helps almost anybody be dramatically more effective. And it's just, it's just sitting there and inside of Open AI or inside of Claude from philanthropic or any of these tools to, to, to be there, to be that partner with you.
And it's that, that experimentation with these tools about not how do they answer questions for us, but how do they help us ask better ones? How do they help us structure our questions so that they're more creative and useful.
Yeah. And that's, and that's so interesting. I, I read that in your book and I, I highlighted it when I read it through, because that's really at the epicenter, what I tend to do with my AI anyway, help me work, work through problems and so forth.
But I've never fundamentally felt that AI has come up with their own ideas. It's, it's been, and I've heard so many people say the same thing, that AI isn't fundamentally creative. And this framework was the first time. So I tried it a week and a half ago. Uh, so I walked through, uh, this was in Claude. I felt it worked a lot better in Claude than in Chatty five, um, the sonnet 4.5 model.
So I, I kind of prompted the model to really understand the ecosystem of the problem that I was trying to solve, and then asked it to, to apply the Tris framework. And it was the first time that I genuinely felt that I get new things that I haven't read about somewhere else, that I, uh, haven't thought about myself.
That was a game changer for me. It was so valuable.
For, for me, that's been really powerful. The other thing is to ask it to look for metaphors or similar things in deep history, right? Mm-hmm. I want, how, how is this, how, how is situations like this played out, uh, in the Ottoman Empire, right? Like, because there's, there's all of that knowledge is there.
You just need to look at it from a different context. Hmm.
And that's the human element at this point. You know, I think the other piece, you know, in terms of these tools, 'cause we're talking about, about the tools, is if you are using the free version of these tools and they're improving it like seven times a year, you're probably using a 2-year-old technology.
Yes. The better stuff, like, it's like an order of magnitude better. And so you have this world where people are having very different experiences of what they are. The same thing. Right one. One's having, you know, uh, you know, a Wagyu steak and one's having gr and they're like, they're both, they're both having snake.
It's like, that's not true.
Yeah, I agree. Uh, who are do you think gonna be the real winners from a financial perspective of within the coming five years, let's say, is it gonna be the opening eyes and the, and the Claudes and or philanthropics, or is it more the, your average company?
Or aren't there gonna be real winners here?
So I think everyone's gonna have to play the game and I don't know, because the transformation's gonna be so quick that you gain massive strategic advantage. Right? I think it'll be highly tactical advantage in many cases. Um, the. In terms of like, does open AI ever make money?
The, the, the foundational challenge is that the value of frontier models the most, the most advanced models are dropping at about 90% a year. So, you know, move that out two years, 99% price, drop, price, performance drop. Well, that name an industry that has been able to sustain a 99% price performance drop in 24 months.
Mm-hmm. Like, it's gonna be very hard.
To the models that said, they may be very sticky, they may lock you into all sorts of other things. And that's where it gets really interesting is, is can they lock you into services? Can they lock you into data centers? Can they lock you into, uh, specific silicon? Can they lock you into, uh, long-term service agreements?
Right? Like, these are things that companies like Oracle, sap Hmm, they're really good at. Mm-hmm. Um, and, uh, are those agreements in your interest? So I think that's challenge number one, is I'm not sure that the models are where the money is. The second question that you were asking is, do I, as you know, a small mid cap business benefit?
I think that there's the short term of I can cost reduce, I can get rid of some labor, so on and so forth. Um, but at the end of the day, it's your people that are going to be doing the innovation. And I don't know that drop the people gets you more innovation. And not saying it doesn't, but the question is, you know, in a world where we're executing faster than strategy, how, how do you do that?
How do you put the governance processes in place that allow that to happen? How do you operate much more like a research lab than like a paper factory?
I think the research lab analogy, because one thing that's really interesting is that we have started to see junior roles not necessarily disappearing, but not being recruited that much because that's the first level stuff that's easy to automate.
Right?
Well, look, the people think is easy to automate. We'll see if it's.
It's easy to automate the, the what, 80% of, of the time where you don't have an exception and the other staff can do the exceptions. I think it's the primary bet, and you still do the exceptions through some type of human in the loop, uh, uh, design.
Uh, but in a research lab, if, if you kind of play it out, what if you don't hire junior employees over a period of years? You won't have any like mid-level people there. There's, there's no growth from underneath. So I'd be interested in how do you deal with junior research lab assistants and what kind of role do they fill in a research lab and can we learn anything from that?
Perhaps
they, they fill a creative role, right? So they're, they're, they're having new and different ideas in a lot of cases. It depends on the type of laboratory. Um, but you know, a lot of times their job is to, to have the crazy ideas because they don't understand what won't work.
Oh, okay.
And that's highly valuable in a world where new things will work every week because new technology Yeah.
Exactly. Is possible. Mm. And so, you know, it's gonna be incredibly important. You know, the Mark Zuckerberg, you know, famously said at some point, I don't hire anyone over 27. You, Andy is like snotty 27-year-old. Right. He's hiring a lot more people over 27 now. Um, but there, there's a, there's some insight in that, that, that it's actually that regeneration and the friction that comes with people not knowing what they're doing that makes, makes new things possible.
Yeah. That's super interesting. And if we go to the other side of the spectrum, could we argue that the, the old Grisled experienced, uh, executives that we expect them more to, to. Move towards almost like being the guardians of the wisdom, being guardians of values and long-term thinking and so forth. Or is that not a, a argument to make?
They need to be as innovative as, as the young ones?
I think that they need to open up the innovation, you know, they need to make possible. Um, I, I, I do think that I, you know, I'm certainly starting to be of an age where I'm the, the gristle one. So I, I have, uh, I have an interest in this argument. Uh, but, you know, I think that the, the most effective innovation executives, right there are people like Mickey McManus, who, who I really enjoy.
Um, he, he, he talked about this idea of, uh, reverse internships.
Hmm.
So he would a junior employee and he'd say, okay. Here's the deal, here's the, here's, here's the pro. What, what do we need to do? And let me help you do it. I'm not gonna tell you what to do or how it'll work, but I can unlock things for you.
And you lead,
have
you tried that? It sounds interesting.
So, so make Mickey's done this. And, and, and what he said was, you know, I didn't think the project was gonna work and it did. Hmm. You know, like, you can't discover that there's this highly new ways of looking and thinking and working. Hmm. Um, that are not intuitive.
Of how we grew up. I grew up in a world where you had a pen and paper and you made a list. And if you got that list wrong, you got to rewrite the entire list, you know? And we're now moving it, you know, out of the cut and pastes, you know, and, you know, computer world into, I don't even write the list. I just get a list.
And I'm like, I don't like that one. Give me, bring me another one. Bring me another one. Right? Like different cognitive world than the one we grew up in. And so we need to just kind of like assume that, that there are, there are strengths in what we know how to do, but there are also weaknesses because we spent so much time getting good at those things.
So how do we allow our people to lead?
How do you personally work with your, uh, shots? Like, what are the things that you find yourself coming back to? A lot.
there, there are a couple of things, right? One, one, we have this tool called Deep Invent that, uh, helps it's, we're automating the research lab. And what we, what it does is it has a conversation with you. It helps you identify the, the, the shape of that invention that you're interested in. Market opportunities, collaborators looks at all of the, the intellectual property that's ever been filed, all the scientific literature that's been written, and then says, Hey, here are 10 ideas.
I dunno if they're good inventions or not, but why don't you dig into one And will our, our, our tool will, our agent will have a conversation with you, help you shape it up, and then press a button and all of a sudden it's written a patent filing for you.
Hmm.
Um, what's interesting to me is that was a six month process before, and now it's a.
45 minute process and it was a half million dollar problem before, and now it's a $1 problem. And like in that is, I think how we need start thinking about these tools is, is that they aren't, might do things for us, but they help us be dramatically more innovative. Hmm. And they remove hearts of the process that were so expensive that we often didn't do it before.
Right. Yeah. We didn't file in IP as, as midcap companies before. I know that software companies especially because it was just too time consuming. It, it distracted people. And now, now if it's easy, it doesn't necessarily have to be good. There just needs to be enough of it that you're defended.
What's the role of patents moving forward?
Like that rules, that seems a little bit built for a world where innovation was both more expensive. So like if, if you spent half a year and $2 million innovating something, I, I think everybody would be fine with you getting some exclusivity on it if you spent 45 minutes on it and you have some type of worldwide or us patent on it.
I don't know if that kind of system still makes sense. It's the first time I'm thinking about it. I think you've thought more about it.
The, in the US you know, the concepts, you know, and this is where, where things break down, right? The concept is that it's not about sweat of the brow, it's about, it's about the quality of the, and that's what we, what we patent for.
And so. Actually from a legal perspective, the fact that you spent $2 million in six months is completely irrelevant to the value of the intellectual property. Um, so that's the first thing to be thinking about here. The second is, um, how do you use it? Because they're so expensive. We tend to use patents defensively.
What is really interesting is if for $50,000 I can file a whole suite of IP that acts as a mode against your competition, just completely blocks them in. That's really interesting. And no one did that before. Basically everybody's a patent control.
Yeah.
Um, that's a weird world, right? That's a weird world.
Yeah.
You would assume that there's, I'm, I'm almost exclusively speaking about like moral issues here. Not really the practicality, but you would then. Almost want to force you to do something about it, because we don't want to create pockets of innovation that are protected by patents, but are not realized because we have so many ideas and we can patent so easily.
Right?
Hmm. Well, it is still effort that goes into realizing it, that the issue is, we, we have a concept called first to file. Okay? So the first person to file intellectual property has priority on it. That doesn't mean you pursue it later stages in the patent process, get more expenses. Um, but it gives you, it gives you something to, to, to, to stake a claim in if you wanna go further.
Mm-hmm. And I think that's really important. Um, the, the second piece is that, and this is what concerns me, is that. Part of the reason that the patent office isn't completely overwhelmed and, and they're, they're stunningly overwhelmed, um, is because it is an expensive pain in the neck process. Um, what happens when the patent office gets completely overwhelmed and all of a sudden we go from a three year or five year window for, for, you know, receiving a patent grant to a 10 year window or, you know, on, on a year window on a, or on a 20 year piece of ip.
Right. That, that's, so that's a very realistic situation we could find ourselves in. Um, the second thing that we could find ourselves in is that something like three quarters of patents, and I'm making that number up, but it's, it's in that range, uh, turned out to not be defensible. Hmm.
But I would assume that the patent offenses would be really good customers for deep invent as well, but just from applied from, from the other direction.
Ah, yes, indeed.
That's fantastic. Part of the, absolutely. Part of the game plan. What excites you the most if you're looking into the next, let's say two years? Let,
I, I think this is a slightly different shift, but I think it's what's happening around AI, across Asia. Okay. That, you know, US and Europe, we have this US Europe perspective, right? But what's actually happening on the. Size of the US European middle class is like increasing by 50% in the next decade or so, and that's not happening in Italy and it's not happening in California.
That's happening across China, Indonesia, India, Thailand. And that, that's the most exciting thing to me in human history. Um, how are we gonna use AI to make all of that possible? How are we gonna use it to decrease resource use? How are we going to use it to increase efficiency so that people are freeing their time to be more useful and productive to our species?
The way we do that is gonna be defined in the next couple of years. Mm. Um. Big conversation. It's a positive conversation that we're not having yet.
Hmm. I know that Mo Gda, the, uh, the ex-chief Google X officers wrote a lot about AI as well. He, he has this mental image of, in a few years time, where we're, uh, at a beach somewhere, uh, either hiding from the robots or, or completely set free by the robots.
Where are you on, on the, what's your take on how this will play out for civilization?
Slower than everybody says and faster than we can imagine. Hmm. Um, I think, you know, foundationally
we need to get dramatically more efficient, like orders of magnitude more efficient if billions of people are going to live the lifestyle that you and I have been gifted.
Yeah.
I think that is our moral obligation as a species. Uh, and AI is the single best tool we have to find efficiencies in every business process, every production process, every service process on the planet.
And unleashing that
is transformational to history.
Mm.
In the biggest, it's the, it's the biggest meteor. It's certainly hit the earth in my lifetime, maybe ever.
It's interesting 'cause we're only really talking about AI a lot right now, but we also have this convergence of a lot of other technologies that are equally potentially impactful if we talk about new sources of energy.
If we talk about quantum computing, if we talk about biomedicine and precision medicine and gene folding and whatnot, there's, there's a lot of things happening. Robotics, let's not forget, uh, there's a lot of things converging in a 10 year period that has Yeah. Huge potential impact. How do you see kind of these things playing out together also?
Yeah, that's a big question. Um, I mean, I, I think there are two questions within that. One is, what are the rich world problems? And, you know, precision medicine, blah, blah, blah, blah, blah. Very exciting. On the other hand, I think it's, there's one brain surgeon for every 400,000 Indians, 4 million Indians like that.
I think there are much more basic things that are less sexy. Like how do people not die of brain aneurysms? Hmm. That we need to figure out how to solve. And so there are these two sides of this coin, right? This the cool VC thing, right? VC fundable thing. And then there's the thing that actually changes millions or billions of lives.
And I think we're under calculating that. We're under investing that, um, how do we dramatically shift with robotics, for instance, the fact that, so there's a lack of brain surgeons. Hmm. And how do we make those robots not a million dollars? How do we make them 10,000? Do we make them a hundred thousand?
Right. Those are, those are the really interesting things to me. Um, when we talk about, you know, foundationally precision medicine and quantum computing, what, what we're talking about is an ability to simulate what happens next. Right. The thing that's scary today, the thing that's terrifying today, whether it's climate, whether it's geopolitics, whether it's looking at potential disruptions in the financial system, the thing that's terrifying today is that this is the first time in human history that we have had any tools to look into the future and look in a meaningful way at the range of what's happened.
Hmm.
What's gonna happen and make decisions. What's terrifying is we now have a responsibility for the future that we never did, which means we have so much more potential that so much more is plausible, that we can dream bigger for the first time in human history. And that's what quantum computing, that's what ai, that's what the ability to simulate so that we can do things like precision medicine are all about.
It's a different way of thinking. It's about thinking not as, uh, vass of fate. Mm. But the creators of it.
Yeah. I had an interesting conversation with, um, uh, an AI professor here in Sweden talking about AI doesn't work that well yet in, uh. Research settings because it's a lot about correlations, but you're looking for causations.
Uh, but it's coming up as well. Have, have you been looking at this at all?
So we've been working on artificial intelligence tools for 75 years now, something like that, right? 1956, um, was I think whether we coined the term, uh, my point being that there's a whole range of what's called symbolic reasoning, which is kinda left brain ai. So this is stuff where A always goes to B, B always goes to C If you were around in the nineties, we call them expert systems.
Uh, if you've used TurboTax, that's what we're talking about, right? You don't want your accountant to sometimes think it's a dollar sometimes, like, but when a thousand times it's a billion, right? Like, so we've built a lot of those tools. Symbolic reasons, reasoning tools. And then we've had these neural networks that we've been building for the last 15 years.
This is what Jeff hinting got his, uh, his Nobel prize for. This is what open AI is built on top of. And you know, sometimes things are one, sometimes they're two. Hmm. Very occasionally they're 367. Good for correlation, not so good for causation and the big project. So I think of it as like kinda left brain, uh, and right brain thinking.
Uh, the big challenge in computer science for the next five years is bringing those together to kind of a whole mind way of thinking so that you are looking at correlation, right? Creative stuff. You're also looking at causation. A always goes to B, always goes to C. Hmm. And what we're is, we're getting much better at this with things like reasoning models, right?
With things, um. With reinforcement learning tools and like we're getting much better at it. And foundationally what's happening is we're building out work plans that are much more granular. Let's look at this little million times, let's look at this little piece a million times. Let's look at this little piece a million times and what are the answers that we see most consistently?
And so you're getting those two things right. A always goes to B. B always goes to C. And then you're testing, it's called best of in a whole bunch of times to see what is the most true thing here. Right? And so the, the question isn't really correlation and causation. It's how do you get granular enough and how do you test things enough that it doesn't actually matter?
Yeah. How can you actually start simulating outcomes That's really interesting and getting high precision in simulation work. Uh, I don't think people really understand the concept of let's do that a million times. Just in a a, I heard like half a year ago or something like that. Just in a marketing example, what if you fundamentally could ask every single one of your customer, but they're just simulated when you're building up your new marketing campaign?
Uh, we, we, like, we don't design, or I haven't designed processes for that type of like, let's run that specific single barrier things, uh, thing a million times. That's so exciting. What you can do.
And, and this comes down to that conversation we were having at the beginning about like, what would you do if you had, you know, we, we were, I think we were talking about this before, like what would you do if you had an infinite amount of labor or an infinite amount of choices, or an infinite amount of time?
These are the questions. Those are bizarre questions. What are the questions we need to be asking?
Right. I think it's such a fundamentally great way of looking at this. So I have conversations very much more practical than, than this conversation that we're having today. Like what's the first, uh, custom DPTs that I should build, like that, that type of entry level into DPT.
I think that's a great way to start. Like imagine you had unlimited support staff around you. What would they do? What could they do that would fundamentally delight your customers in, in ways that you couldn't possibly do today? Just because of time constraints. Awesome place for, for like simple innovation.
I actually built a couple of those types of, of like deep research flows just around that idea.
Mm-hmm. Mm-hmm. What did you discover?
So for me, um, so I was looking at my role as a leader. So what would be the support staff that I would love as a leader? So I found that I would love a management consultant around me that was constantly monitoring the external environment that was quality and improver of plans that I laid.
So how does this actually connect, align, stuff like that. There's a lot around just executive assistant stuff, summarize, yada, yada. A lot about what we talked about before, the, the kind of one-to-one coachings prepare, uh, be there when, when I'm not, give feedback, even though I never really touched it. Um mm-hmm.
So, so there were a bunch of, I, I think the framework of breaking. A role down to the individual tasks is really helpful in the practical sense because the reality of, of most leaders is that you're a leader, but that's not everything that you do. Uh, a hundred percent. You're also a sales guy or a IT guy or whatever it is, but just break the, the it part of your role down into individual tasks.
How can we improve the speed of, of UX discoveries or whatever it might be, break it down to tasks, break it down to tasks, automates that stuff. But also I think what fascinated me most with that work was also thinking through what do I fundamentally enjoy doing? And rig me up so that I'm better positioned to do that with better quality.
So generating awesome pre-reads, for example, going in and, and have them automatically pop up in my slack five minutes before the meeting. This is who you're meeting, this is what you talked about last time. These are things that you could bring that that person probably would find valuable. And just have it always just pop up five minutes before
I want that.
Yeah. And it's not that difficult either, uh, to be that, that that's what's interesting right now. Again, the problem is not technological at this point.
No, it's not. It's, it's having the idea that I don't need to do that work anymore.
Yeah, exactly. And I think compared to when the internet wave came, like, I think part of the reason why we saw that play out and we had a, a few bubbles and so forth along the way, was there, there was so much infrastructure that wasn't fundamentally in place for an Amazon to work in the early stages of the internet revolution, because we didn't have smooth online payments, for example.
We had to build that first. What I feel now with AI is that the infrastructure works so much better than the organization works around the infrastructure. So we can grow so much without really being constrained by the technical issues.
It's just we're moving into such a wild time, you know?
Yeah. It's just, we just, yeah. I remember how many years it took me to remember to ask Google first.
Hmm.
Before I thought about a problem, like you, you should just ask Google someone thought about the problem. Yeah. And you know, and, and then it was like, how do I ask the right question? How do I ask the question that will get the answer now?
Like, you don't really need to have the question or the answer and it'll get you like 80% of the way there. We're now moving into a world where, where it's like you don't even need that. Right? Like something will actually think about the problem in your context for you. Yeah. How do we, do we remember to do that and how do we, you know, in a world where we outsource our thinking right, not get rolled by the system.
Yeah. A hundred percent. So interesting. One of the things that I've found is that when we talk about I want to optimize for things that I enjoy. I really enjoy asking questions and being curious. So that was part of the design. Like, I really love iterating with my ais or, or whatnots, and I think it's super dangerous if you're walking down the path of, of trying to automate your own thinking.
Like the second order consequences of that are poor. And we're starting to see brain studies coming out. So how do, how do youth specifically think about the idea of having mental friction as a important part of you being continuously creative?
I, I, I think that there's this idea, like the thing that strikes me, and you may be in a slightly younger generation, but the thing that strikes me is as an inventor growing up, probably the most critical component was boredom.
Yeah. I'd be bored and I'd have to come up with something to do. And it was typically like blowing something up. Like, you know, I'm not saying that my parents were into this, but like it was typically a bad idea. And, and, but in that boredom was the moment where something new happened. The concern for me about friction and creative friction is we are so overstimulated in every moment of the day and we never, ever, ever aboard, ever.
And so how do you in fact, create that space where innovation happens?
Yep.
As opposed to. Structural innovation happens as opposed to just process like, we're gonna do this 4% better this new way, this a new button. How do we step back and how do we encourage people who we've been just running harder and harder and harder on the hamster wheel to, to be comfortable doing that?
Yeah. A hundred percent critical thing is like in a world where technology makes new things possible every day. Like, are we even solving the right problem any longer? Hmm.
Yeah. And the ways that we look at productivity and measure productivity is also pretty part of the problem. You measure it by, you can see that people are online on Slack, which is probably the worst way of looking at productivity, but I see a lot of companies being very stingy about that.
Yeah. And, and I think it's, it's also, you know, are you looking for base hits or home runs?
Hmm.
Right. Are you hitting, are you looking for, for, you know, to, to. To score a goal or to win the game. And there are different ways of thinking. Hmm. Right. There are different types of thinkers and what we're looking for increasingly is we empower our people are new ways to win the game, not new ways to score goals.
Hmm. Like how do you change the rules? Yeah. Reinvent. Right. As a, as a speaker, you know, it's been really interesting for me in the last year or so that a year, two years ago, 80%, 70% of my work would come through agents. Now it's just coming direct. People are like, yeah, I don't have time for that. It's gonna call Jonathan, see if he can be in Brazil on Tuesday.
Mm-hmm. Which is, which is just wild. Right. But it, it's changed the game. Right. If I was spending all of my time marketing to service, uh, yeah. Speakers bureaus. As opposed to being out there and being useful and having useful conversations. Hmm. Like I wouldn't be hitting my new customer.
Yeah. Do you reflect on, coming back to the point that we were talking about before with mental friction, do you design and optimize your life for those periods of boredom?
Yeah. I mean, I, I, I have a, I'm, I'm today on, on a workation in, in Spain and yeah. Just making, you know, I'm hanging out with a buddy and making, you know, making time to really think about my business and think about what, what I need to do in the next year. Like, why in, in a world of such rapid growth, we, that's the most important thing Yeah, that's right.
Is to, to where we're to, to know where we're going instead of just running, I.
Yeah. Taking that step back. I completely agree. And so can be, were very difficult to, to get there in, in the kind of business of all things. Right. You need to, to consciously make those choices.
Yeah. You, you can't, like you, you were saying earlier, you know, this strategy go away.
Mm-hmm.
Strategy becomes dramatically more important.
No, that's fascinating. Thank you so much, Jonathan, for, for taking the time. This has been a really interesting conversation to me.
The same to me. Thank you very much,
There we're at the end of the episode. I think it's so amazing that almost 70% of you actually listen to the end of the episodes, especially for long format. I'm, I'm so thankful for that. Like the engagement numbers is fantastic. Before we leave each other, two things, first off. This episode was sponsored by Grail and I'll make no secret about Grail is the company that I'm starting.
So it's the future of AI and how can we unlock value that's not just automation, but actually building towards a future that we want to live in, like a future where I want to work augmentation. So head over to Grail Works to know more. Secondly, I'd appreciate so much that you listened to this podcast.
Even though 70% listen to the end, almost 70% are not subscribed either. So if you can give, uh, a like button a subscribe to all my channels. We're on LinkedIn, we're on Instagram, we're on TikTok. Apparently, uh, we have an awesome webpage and. There's so much more content, like yes, the reels and so forth. But what, what I really would like to push for is that every week I publish a long format article, which is the pinnacle of my thinking.
So it's the most interesting thing that I come across that week, either in podcasts or in other endeavors. I try to write about it towards you, a senior leader, like what is the crucial takeaway from the most important part of my week, let's say. I published that on LinkedIn and on my webpage Think Room podcast.
Thank you so much and see you next time.
That was Jonathan Brill on ThinkRoom — where exceptional minds think out loud.