Moonshots with Peter Diamandis
The Organizational Singularity: AI-Proof Your Company | EP #258
26 May 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: What is the organizational singularity and why is it important?
Is there a line of your business, a high margin line of your business that two guys with open claw could replicate in 60 to 90 days?
This is something across the board useful for everyone.
When we wrote the exponential organizations book, we didn't realize how prescient it would be. It turned out over 10, 12 years, we were dead on. Now that we see a genetic AI on the future of intelligence, what does the organization look like? We think we have a pretty interesting viewpoint and perspective on that.
If you don't retool your organization or don't restart your organization, you will be disrupted because someone doing it is going to just eat your lunch.
The central thing to think about is all of our organizational structures in the past were organized around hierarchy. And now they need to be AI native, a genetic workflow. And that's a totally different model. It needs to be architected around intelligence, not around hierarchy. The next question really becomes, how do you get there?
Now that's a moonshot, ladies and gentlemen.
I'm about to sit down with my dear brother, Salim Ismail, my Moonshot mate, talk about the organizational singularity. This is a conversation that I think is absolutely critical for every company to be looking at. We're in a period of rapid transition. Agents, AI,
AGI, ASI, it's going to restructure how every company, every industry is being run, not in five or 10 years, in the next one year, in the next two years at most. Salim's going to lay out his process that every company can follow to move from the old way of doing business as an organization, which is sort of top-down heavy, human-centric, to a digital AI-centric, AI-native company.
Please take a look at this. This is about your survival. It's about your thriving. It's happening. And you're either on the evolutionary tree or you're going extinct. It's that simple. All right, let's jump in. Everybody, welcome to Moonshot. It's a special episode with my dear brother from another mother, Salim Ismail. Salim, you're finally here. You're in our Moonshot studio.
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Chapter 2: How are traditional organizational structures being disrupted by AI?
And today is a special day. It's your birthday. It is my birthday. Yes. And so for those who don't know, Salim has just turned 16. It's his sweet 16th birthday. Flip the digits around and be a little more accurate. Okay, that's right. The dyslexia in me hits it.
So we're going to talk about something that we've been teasing on the Moonshots podcast for a while, something that I'm excited about, which you call the organizational singularity.
Yeah.
And I want to make sure that everyone listening realizes this is something across the board useful for everyone. It's not if you're the CEO of a large Fortune 500 company, though it's useful if you are. If you're an entrepreneur, if you're in a small company, if you're a parent trying to advise your kid where to go to work. Exactly.
Look, when we wrote the exponential organizations book, we didn't realize how prescient it would be. It turned out over 10, 12 years, we were dead on. And so we're kind of saying, okay, now that we see a gigantic AI on the future of intelligence, what does the organization look like? And so we have taken a crack at that with the help of my entire community all pitched in for this.
So we think we have a pretty interesting viewpoint and perspective on that.
And you've been saying for a bit now that AI has killed the modern company. Yes. The Fortune 500s out there. But I don't think they've gotten the memo yet.
They don't because there's a drag that goes effect, right? When the comet hit, the dinosaurs didn't go overnight. It took a few generations for them to die out and figure out what the hell's going on. So this is the same type of model.
All right. Well, let's dive in. And I want to make sure that folks... get where things are going to go? And again, how do you surf on top of this massive change that's coming?
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Chapter 3: What steps should companies take to become AI-native?
happens out in the wild. And when you can enable that with technology, you can scale, right? So we found ways of extending Kosa's law. And then Jack Dorsey did what he did with Block and with Roloff Botha or Werther's book. And we are now extending all that. We basically come to the conclusion is that the whole thing breaks in the face of agentic AI. Kosa's law no longer applies. Why?
Because if you have to build a website inside a company, You have to go through layers of meetings and approvals. Branding has to look at it. The privacy guys have to look at it. The IT guys will tell you they can't be done. Whereas today, you can step outside the company, use Vercel at home for five minutes and get it done for free.
And have it know your brand guidelines. Have it know your design taste. Yeah, that's right. And have it actually spin up a dozen different versions and have them try in the market.
Yeah, and this is a fantastic tweet that I've quoted, which I've forgotten the name of the fellow just now, but he said, building the feature is cheaper than having the meeting about the feature. So true.
And that's such a great way of framing it, because that means that coordination, the act of coordination is more expensive than just execution today, especially as AI is driving down the cost of execution.
And I want to make sure we get, as we discuss this, we understand what is the role of people in this, right?
Let's get to that, because I want to just first make the case that this breaks. Now, you could ask the question, do we need an organization at all? And it turns out we do. And we have a term called the fiduciary wedge, where, okay, coordination costs and execution costs become low, which was primarily the reason for organizations the last 100 years.
But you still need it as a purpose container, a fiduciary, a legal container, a liability container, a legal container. So think SPVs for investments or just containers. They hold legal and fiduciary liability. Essentially, companies become more and more like that. And there's a gap between human judgment and liability versus what the AI can do. And that gap we call the fiduciary wedge.
So you still need an organizational structure and the legal entity.
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Chapter 4: What is the role of human oversight in AI-driven organizations?
Agents will do that. You basically hit, yes, I like the evaluation or not.
So basically you're using your wisdom and experience to decide whether the agent's action is in line. That's right.
Now this opens up a whole other question, which we'll get to in a second. So C-level is guiding and holding accountability and watching what the agents are doing and then deciding yes, no, do this, do that, whatever. Middle management is where the biggest change happens because middle management in existing companies is almost completely doing coordination.
They take data from the co-phase, they repackage it for proper absorption by the C-suite. That function drops about 90%. Now then you need to lift up the human beings there and have them doing exception handling, problem solving, et cetera, of which there's a ton. We just don't do it because most people don't have time. Now you'll have more time to do those things.
The bottom 20% are doing much more enabled work because they're agents doing almost everything, and they're also doing oversight and watching.
Now, we've talked about on Moonshots a number of times the idea that we're going to see a reduction in the size of firms from 100% down to 20%, 80% reduction.
Our calculation is you'll be able to run an average company with about 20% or 25% of the workforce that you had before. Now, you can go down the negative side there, media side, and go, oh, my God, 75% unemployment. Or our moonshot view would be we'll have five, 10 more companies being created, and there'll be that much money more.
The blossoming of entrepreneurship. That's right.
And we're seeing the Cambrian explosion of startups already. We're seeing actually hiring go up right now for entry-level jobs, which is really pretty interesting to spot. So, those are the three things that happen to the three layers of the business. Now, the question then becomes, how do you turn into one of these?
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Chapter 5: How can companies avoid the pitfalls of legacy systems when implementing AI?
But you know, everybody's having so much fun now. It doesn't feel like work. No, it's play. Because we're getting so much done. I mean, it took three years of hell to write the first book. It took us two and a half years of hell to write the second book, mostly because we had to rewrite it.
Because you had to deal with me. No, no, no, no, no.
Because we had to rewrite it because generative AI came out towards the end. But this third book was three months, right? And because there was so much, every contributor could use an AI, add more data to it, more help to it, add their methodology to it, and then boom, you're off to the races.
So the second domain where this has fully happened, by the way, is marketing and content generation, right? We used to have, it was agency heavy, then it was AI assisted, and now it's AI native. Right, and so we can see certain verticals hitting this spot in a particular way. So let me go into the rewriting methodology. We call this methodology rewrite. Okay.
And I wanna go into a little bit of detail so people understand the specific steps that are involved in this. So you have a workflow like invoice processing and you're gonna start moving workflow over. Before you do any of that, you have to do a backcasting exercise.
Okay. What's that mean?
Backcasting is a methodology in future studies and forecasting where you pick what the vision looks like. Say Elon wants to get to Mars, you could say, okay, I want to get to Mars in seven years. In order to get to Mars in seven years, where do I have to be in five years? Where do I have to be in three years? And now you have your roadmap.
If you start from the starting point and go, I want to get to Mars, you've no idea what you're doing, how you're going to get there, et cetera. Backcasting has turned into a very powerful methodology.
So step one is take your company, so let's say it's that trucking company or retail company that I used earlier, and say, okay, in this future world, what does that company look like, fulfilling its MTP and its architecture in an AI native-centric way, and you paint that picture.
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