Azeem Azhar's Exponential View
My outlook for 2026: orchestration, the human edge and the AI bubble
16 Jan 2026
Chapter 1: Why does AI feel different in 2026?
Coming 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-to-day.
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. And 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's just in terms of actual velocity. And what has really driven that has been the ability for these systems to write code. 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.
Chapter 2: What are the six shifts in AI that will impact the future?
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 that I want to suggests 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?
Chapter 3: How is the 'done list' era transforming productivity?
Because when making gets much cheaper, we need to ask the question about what is still valuable. And 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 boomorbubble.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 Maykink.
The act of building has been transformed, not incrementally, but really, really categorically.
Chapter 4: What is the agentic coding revolution and its implications?
It is really, really remarkable what's happened 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. He says, we're out of the to-do list era. We're into the done list era.
And that's the capability and the capability that things like Clawed 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. I've got about 4,000 music tracks on my computer and my SSDs. They're a real mess.
Chapter 5: What role does the Chief Question Officer play in AI development?
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, and 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 cataloged and therefore accessible. To me, guess 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 where 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. So I built an app. It's called Psychic Octopus. You could see my state of mind at the time.
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Chapter 6: How will authenticity and meaning become the new scarcity?
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 it 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 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. There 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, Andrej 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. What you do is you maintain a list of intents that become a set of done lists. And for teams like mine, which we're 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. I will give you one small example of this.
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Chapter 7: How does solar growth affect the future of AI?
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. And 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 2025 was largely about productivity boosts, in particular, say, for software engineers. In 2026, there is a notion that one of the things that 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. And 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 huge. 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. And one of the things I found really remarkable was that the lead developer of Claude Code, Claude Code is Anthropix's 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.
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Chapter 8: When will the AI bubble burst or is it a boom?
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? And 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 around 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 going to do lots of it. And what's happening is that we're building things that otherwise we simply wouldn't do. No one was going to build that DJ music workflow for me. And 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 going to pay $10,000 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.
I think for software companies, this could be quite challenging because right now I can build a tool faster than it takes to
communicate the 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 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
How are they 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? I 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 question, 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.
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