My outlook for 2026: orchestration, the human edge and the AI bubble

0:00Coming into 2026, things feel a little bit different. The moment is somewhat unusual. It's charged by, I think, a maturation of what we've seen from AI tools, a promise of the last seven or eight years. And so I wanted to start this year by grounding us in something different and something simple, the way in which AI is already showing up in my day today and how that's changed in the last two or three months and what that means for the year ahead. So let's get back to this sensation that I have felt and experienced over the last few weeks. It really feels that some of the AI tools crossed some part of the uncanny valley.

0:49And what it feels like right now for me is I have maybe 50, maybe 100 people working for me in addition to my brilliant team, not metaphorically, but it just in terms of actual velocity. And what has really driven that has been the ability for these systems to write really good code and become more and more reliable in the analysis they do. Things that have sat at the bottom of my to-do list for months are now done. They're done in an hour. They're done for a few dollars. And so what I wanted to do, it's been such a moment, maybe a realization or an epiphany about what that work style looks like just in the last few weeks.

1:32I want to suggest that 2026 could be a year for everyone where the way in which you use AI is going to change. It's going to be less about using tools and more about orchestrating your team of virtual workers alongside your real human colleagues. And I think one way of thinking about this is about moving from the to-do list to the done list. Now, I want to take you through six shifts. These are anchored around three particular principles. The first anchor is how we make things and why the act of building has fundamentally changed. The second anchor is what does meaning look like? Because when making gets much cheaper, we need to ask the question about what is still valuable.

2:26And the third is, what are the foundations that all of this sits on, the energy and the money and whether this entire edifice will hold together? So we'll end that conversation, right? The part of that third anchor is the question that I was asked the most in 2025, when will the AI bubble burst? Or indeed, is it a bubble at all? We've obviously done all of our evidence-based research and forecasting. We've got a solid understanding of the cycle. You can check the website at boom or bubble.ai, which is updated, I think, every single day or most days, perhaps not on the weekends. So with that, let's get to the first anchor, which is what's happening to making.

3:07The act of building has been transformed, not incrementally, but really, really categorically. it is really really remarkable what's happened in in the last six months three months in particular i'm going to get into some of those details the venture capitalist tom tungus came up with this really great phase and i keep coming back to it he called it the done list says we're out of the to-do list era we're into the done list and and that's the capability and and the capability that things like Claude Code are providing to all of us. And here's what it feels like to live within it. And I'll just give you one example.

3:55I've got about 4 ,000 music tracks on my computer and my SSDs. They're a real mess. They're the tracks that I use when I'm DJing and doing sets of different types. And needless to say, over the years, they've just got really messy, confused in all sorts of different places. I download them, I buy them, then I can never find them again. And they also all need to go through two post-processing steps so that the levels are good and so that they've got marked up with harmonics and so on. And then I can load them into the DJ software and put them on my decks and mix with them. Now, for months, actually much longer, I have planned to organize those 4 ,000 files and make sure they are all processed by those two steps and neatly catalogued and therefore accessible to me.

4:42Guess what? It has been on the bottom of my to-do list because there are a million other things that I need to do. Now, last week, actually, was it last week? Yeah, I think so. Last week or maybe just before New Year's, in about an hour, I built three apps on my Mac. One scoops all the files together, finds them all, finds duplicates, gets rid of duplicates, figures out whether they've been processed correctly and sends them to the right queue for processing. A second app, which I designed and built, addressed the specific need that I had, which was I felt that the metadata around the tracks was not rich enough to help me navigate when I'm putting a set together.

5:21So I built an app, it's called Psychic Octopus. You can see my state of mind at the time, which goes through all of those files and adds additional metadata markers around the degree of percussion there is, where the drops are, how much vocal there is beyond what the mainstream music systems are providing. And the third app was a playlist generator. So I could load up my tracks. I could say, this is where I want to start with this track. This is where I want to end in this genre over this length of time. And I want the mood to feel like this during the set. And it would go out and discover some paths that would work and present them back to me.

6:00It all works. And it all took me about an hour, maybe an hour and a half. To be honest, the taste of that playlist maker is pretty terrible. It is pretty terrible. It doesn't have great taste. But the point is, it's done and it works. And this is one of, I'd say, around 30 or 40 apps that I have built over the last couple of weeks that I'm using, some of which we may make available to members in coming months, which speaks specifically to needs that I have. And this is really, really radical. And I'm far and away not the only one experiencing this. I mean, I've been reading a lot of testimony over the last two or three weeks.

6:43There was one particular engineer. He said that his two-person team now supports thousands of users. And he described what he now does as moving from playing every instrument to conducting an orchestra. So this is what a year ago Andre Kapathy called vibe coding. The idea that you have a vibe, you can talk to your computer and it will start to build whatever you need. And I wrote a lot about vibe working and I'm sure many of us are doing that where we vibe our way through a speech we need or we vibe our way through a marketing plan or we vibe our way through analyzing customer data. You don't really maintain those outputs.

7:23What you do is you maintain a list of intents that become a set of done lists. And for teams like mine, which were small, as a small team, everyone is highly motivated, super capable. They can lean into this and they can do this really, really quickly. But I think for large companies, there is going to be molasses to put the best term to it. Their processes are designed for this linear approval-based sequential system. They, especially if they're public companies, have to worry a great deal about risk. They have to go through all of those layers of approvals. That's the to-do list era. Those of us who are moving into the done list era are in parallel, outcome-based, and immediate response.

8:14I will give you one small example of this. I'm sure like many of you have also been through this where you're looking for just the right note taker on your computer and you've moved from notes to notepad to Evernote to Notion to Roam and to the next thing. Well, I knew exactly what I wanted and it's very simple. It works in my browser. It syncs across to my phone and it took me 30 to 40 minutes to build quicker than it takes me to navigate around a complex notion. And it's exactly the thing that I want. So this is a really remarkable moment, like this revolution in building that we're starting to see through the capabilities of these agents.

8:59And that's the second part of this tentpole, which is this agentic coding revolution. we have moved across the line i think if 2024 and 25 was largely about productivity boosts in particular say for software engineers in 2026 there is a notion that one of the things in it a software engineer did which was that they translated real world needs into code that computers could turn into apps that met that real world need well it feels to me that that particular attribute is becoming obsolete, the translator attribute. And product managers who sit one level up closer to the end user would do some of that translation as well.

9:46And I think they still have an important role, but you can start to see that the gap between the user and the code that the user wants to get something done or the analysis the user wants is squeezing. I use the word smushing when I was writing my notes for this. It's smushing and smushing fast, if indeed that is a word. There was a really interesting story a few days ago that BCG, which is that strategy consultancy, had operationalized what they called the consultant as creator model. Their consultants have built over 36 ,000 custom tools using AI. So they're not buying the software, they're probably externalizing certain capabilities in these tools for themselves and for their customers.

10:31And one of the things I found really remarkable was that the lead developer of Claude Code, Claude Code is Anthropics coding tool, he revealed that in December, 100 % of his code contributions were written by the AI itself. And he wrote 40 ,000 lines of code. And he describes it as editing and directing rather than typing syntax. You know, it's the ultimate in the kind of leadership role that you might have. So one way that you might want to frame this as like the skill that's required in this world of building and making is the importance in being able to frame the right question, right, to direct the right intent.

11:10The economist, friend of Exponential View, Eric Brynjolfsson has called this the chief question officer. If the large parts of the execution phase of work, whether it's coding and calculation and certain classes of the doing, are increasingly commoditized and they happen quickly, value shifts to the complements. I mean, that's classic economist framing, right? The value shifts to the complements. And in this case, that would be the problem formulation, the question asking, the intention seeking, and the evaluation, right? Did I get what I needed? And so the bottleneck shifts from writing the code to, do you have a good enough backlog that you can articulate?

11:49And can you formulate that problem? And can you evaluate it? I've gone through a year's backlog of stuff that I would just never get round to in just a day. And so that backlog moves to knowing what's possible, what you need, what to get right. It's no longer just an engineering mindset. It is really a creative mindset. it's an artist mindset. Now, a lot of this is classic Jevons paradox. So, you know, we're bringing down the cost of something so we're gonna do lots of it. And what's happening is that we're doing, building things that otherwise we simply wouldn't do. No one was gonna build that DJ music workflow for me.

12:29And I'd seen all the tools and I wasted more time searching the web for tools that could do it than it took me to build. And I certainly wasn't gonna pay 10 to$15 ,000 to a dev shop to build it for me. I was just never going to get it built. And now it is built, it is being used, and it is in existence. And this is happening. You can see that this is rippling through the engineering community if you go onto X. But you also look at Stack Overflow, which had been the place where a lot of engineering knowledge was stored, and Stack Overflow has really collapsed. People are not asking questions anymore because the AIs are really developing what they need to develop.

13:10I think for software companies, this could be quite challenging because right now I can build a tool faster than it takes to communicate the spec. So why would I start to accept the shortcomings of someone else's design unless they have some kind of deep lock-in, which might be that they are the so-called system of record within my enterprise? And of course, there are all sorts of things we have to consider, like are these systems going to be reliable? Are they going to be safe? and how they're going to interact with each other. Are we going to be able to maintain, keep our data or will they fail and the data has gone for good?

13:46I mean, these feel like they are problems that will get solved over the next year or two. Eric talks about that value going to the questioner and the insight. And I think that if I look at this from a business perspective, where does that value start to anchor? And I think that there are probably three areas. One area is the data. So it doesn't matter how good an app is. If it doesn't have the data that is relevant to make it good, it's going to be irrelevant. So I think that data becomes important. I think the second thing that starts to become important is distribution. It's going to be harder and harder to stand out.

14:25You have to be hyper, hyper viral in order to do that. So existing distribution, I think, may start to benefit people. and I think the third thing is what is the insight that you have the really specific take that speaks to something about the world that doesn't currently exist which is what you know building anything it is right you don't build something that's already there and the interesting thing is that all of those many of those things correlate to one thing which is customers right because customers can be a source of data they can be a source of of insight you know they understand They express what their problems are, and they are also your distribution angle.

15:03So one idea I'm noodling with is the importance of that customer centricity. And hopefully, you know, within the premium members of Exponential View over the year, you'll start to see the fruits of some of that. So when baking is trivial, the question is, what is still hard? What is still valuable in that context? So you can think back to the economist framework, which is you look for the complement. and and one of the ways i now i think about this and within this this anchor is the idea of orchestration you know if you are not building something directly yourself and it really feels to me that certainly for the class of code that we might have written and certainly within anthropic right the these these incredible developers of the class of code they are writing well you don't have to do that anymore so what are you doing and and the answer is that we are we're orchestrating.

15:59And as any conductor, I'm just going to say this, I realize I knew nothing about conducting except for watching that film, which had, I think, Cate Blanchett in it. But, you know, when you're conducting an orchestra, you sort of need to know the capabilities of the people who you are conducting. And one of the things I've noticed as I've started to move from sort of single agent coding to multi-agent systems and working parallel with six, eight, 10 of these things at a time is that you do need to understand those systems. And I've even discovered, and this is kind of curious, that the agents are starting to understand their own limitations.

16:36I was building something that's a kind of internal research tool a few days ago that involves a lot of different agents. And at one point, Claude said to me explicitly, don't use me for this. Go and use ChatGPT because it's tougher and more cynical than I am, which I thought was a really interesting bit of self-reflection. It's quite a strange moment. And that is evidence, I think, that we're not going to have that singleton AI, all-powerful AI. It is that society of AI that I wrote about a couple of years ago, or if you saw the recent essay about the world of spiky minds, that's also sort of reflective of that.

17:18Lots of different models, lots of different capabilities and tones, and the need for us to be able to orchestrate and understand across them if we are actually to be more than individual contributors. So there's a reality check here, which is the usage gap. So at the end of 2025, ChatGPT, alongside everyone else, by the way, launched their sort of year in 2025. Everyone's aping, aping Spotify. They released their year in 2025. If you got one of those, why don't you share some of your highlights from that year in 2025 in the chat? Because that would be quite interesting, I think. When you look at that data, it was quite interesting to see what it took to get to the top 1 % of all chat GPT users.

18:01And I found on Reddit a post that showed that there was a user who'd only had 283 chats in the whole year and they got to the top 1%. Now, one query a day in my mind is not really using AI. That is not diffusion. That is experimentation. That is a bit like, you know, my home, I can tell you we have a fondue set, but it comes out every three or four years. So I know that in some, you know, technical way, we own a fondue set, but we don't really do fondue. And that gap between fondue set owning AI users and users who've figured out orchestration is now a chasm and is growing really fast. And I really think it's hard for it to close.

18:50We've started to see how within the mainstream, Gemini from Google is taking up, winning a lot of market share against ChatGPT, because that's where the kind of casual person who's going to dip their bread into melted cheese, use AI once or twice to improve some simple processes, it's going to end up going. And that casual usage is volatile. Whereas when you're in the orchestration space, that deep integration matters. So this observation is not about who's going to win the broad consumer. That's a commercial question, Google versus OpenAI. I'm sure that they will both have successful businesses here.

19:30But I'm really interested in who is really embedding this technology in their ways of working in order to really, really maximize and expand their capacity. If 99 % of chat GPT users are doing fewer than 283 queries in 2025 based on one Reddit post, maybe there's better data out there. The number of people who are going into orchestration is very, very small. And so the human job though exists. It's really, really fun. I'm super enjoying myself. It's about architecture. It's about establishing intent, asking what am I trying to do? It's verifying, have I got where I wanted to get to? What have I learned on that process about things that I can extend?

20:11And what is the expertise that I now need to know which agent to use which agent for which task? You know, I've gone from being an awful developer. Many of you know, I was such a bad developer. My development team begged me to stop writing code to being able to write quite good code and applying my judgment to it. And that takes us to the sort of second half of this second anchor, which is authenticity. So authenticity is going to become really important. I read on OnX something from an American venture capitalist, first name is Lulu, I forget the rest of her name. And she made a really important point, argument where she said, listen, authenticity is going to become really easy and accessible sort of pseudo authenticity because the tools are getting better and better.

20:57And it took me back to a speech I gave about 15 years ago where I said, look, in the age of AI, 15 years ago, before AlphaGo and all these other things, right? Conceptually, making stuff will become perfect because the AI systems, we weren't in the transformer architecture at that time, will make things to machine calibration. And in a world where everything becomes perfect, we will start to value the complement of perfection, which is the imperfect, the thing that has some meaning. and I describe it slightly tongue-in-cheek as the future being artisanal cheese you know we can all go out and get cheese and buy lots of cheese that's been made in a factory but there is still some pleasure in artisanal cheese or micro brewing and that's what I meant which is that the machines can produce perfection so the thing that's hard or the thing that's human the thing with texture with idiosyncrasy with interiority this the idea is that authenticity is proof of work.

21:57And I've discovered this because, you know, I'm writing my new book at the moment, and of course I'm using the LLN tools to help me with research and with being red teamers on the concepts. But if you try to get the LLNs to write anything, even a network of LLNs, what you get is incredibly mid-copy. It doesn't have that interiority. It doesn't have that idiosyncrasy. It doesn't have the details that come out from being a human who's lived through something and has experienced things and knows when to break the rules and when not to break the rules. And there's some empirical evidence around this.

22:34The ARC-AGI general intelligence benchmark, the ARC-AGI-2, showed that pure LLMs score 0 % on tasks requiring genuine fluid intelligence. They're good at being able to work their way through certain classes of crystallized problems. but I think that means that right now they're not very good at doing the thing that makes the writing good I say right now because the LLMs of course aren't just LLMs now there's lots of other things going on in these systems to to make them perform and make them you know be much much more reliable so you know we don't know if that frontier doesn't get crossed what I have learned of course is is that they can identify golden threads and they can analyze writing styles and they but they I can't write good quality paragraphs.

23:23And one of the challenges, of course, if you are someone who is delivering what I'm doing now, which is like an expensive authentic experience, I'm spending an hour of my time, you are all graciously giving me an hour of your time. You know, we have to work with LLMs. We have to work with the best tools available. Otherwise, we just can't cope with the demands of the work. But it's that hard human work, the work with your pen. Where's my pen gone? I hear it is. You all know my lovely bronze fountain pen that doesn't have the ink reservoir in it. That work without the pen, the work of observing the world around you, of reading different things, the effort that you put in, that becomes a differentiator.

24:03And I think the funny thing that's the funny parallel is that that's also what made Bitcoin valuable, right? It was the proof of work that made Bitcoin valuable. It's a proof of work that makes the authenticity valuable because we did the thing that John Kennedy called the hard thing. And what I'm doing is I'm putting my attention and my taste and my experience into the output. So where do I think value goes in that world? And I think this creates an opportunity for community builders, for people who develop a sense of taste, a sense of perspective, an experience that they can bring together, things that are difficult because difficulty plus authenticity will turn into scarcity and value.

24:45And Ben Thompson at Stratechery has written a piece just in the last few days that sort of reflects on this as well. The idea that imperfection becomes the premium, the rambling podcast, the slightly rambling sub-stack lives, the things that could only come from that person. A quick note, if you want to support us in bringing more of these conversations to the world, please consider subscribing to the show. So let's get to part three. So here are the foundations. What's underpinning all of this? Well, energy and it's whether the capital, whether the economics can hold. First part of this anchor is about what's happening with solar power.

25:24This is super important, you know, because all of these things I've talked about require energy and there is a crunch in the US, which is why we're seeing a lot of gas turbines being reused and moved from the aeronautical industry to power data centers. This will be a short-term thing. The reason is that a gigawatt data center is probably worth tens of billions of dollars or$10 billion of revenue, reckons semi-analysis over its lifetime. So you don't really want to sit around waiting for a grid connection and you're happy to pay for natural gas, which is more expensive now than solar in most parts of the world.

26:04But it's a blip against the overall paradigm, which is that electricity is turning into a manufactured technology because of the learning curve that attaches to solar and why we are seeing this dramatic growth in solar deployment, not just in the rich parts of the

26:28Coal consumption in 2025 was lower than in 2024, in large part because of the growth of solar. And we've obviously know the story in Pakistan and we see what's happening in sub-Saharan Africa. What will continue to happen year in, year out will be the doubling of cumulative production will continue to apply that learning rate on solar. And production is growing rapidly. Pakistan imported 17 gigawatts of solar modules in 2024. That was more than all but four countries. Africa imported, sub-Saharan Africa, two gigawatts of panels in one month last year. This is people-led, market-led, and it's policy-led.

27:12But all of those panels increased production volumes and the learning rate applies. Historical learning rates have been 20 % per doubling of cumulative production, which means that the panels get 20 % cheaper, new analysis suggests we might be in a regime change. And then that learning rate might be as high as 40%, maybe even higher. I'm a bit skeptical, frankly, about it being 40%. But what it means is that the reduction in cost will get even faster. Now, of course, there are other questions like balance of systems costs and how do you build out a utility scale solar cheaply. Those things are also being addressed through robotics.

27:53I'm an investor in a robotics company that has tracked robots that do solar field installations. And a lot of this doesn't actually run into balance of systems costs because it's decentralized and it's sort of absorbed by a small business. And that will fundamentally transform how we produce our electricity. And 26 is going to be another important year for that. And we will be surprised. I will wage at the end of the year, my only forecast really, that 26 solar deployment will be higher than ever before. And look at something, seven of the big major, six of the major oil nations, producing nations are in conflict at the moment and oil is trading at$56 a barrel.