Chapter 1: What is the main topic discussed in this episode?
Hello, Adam. Hello, Brian. How are you? I am doing well. How are you? I'm good. And the hype has been building here. Everyone has been dropping in. So showing up four minutes late is like a totally pro move. I love it for the new year.
Yeah, yeah, listen, I was going to go full, like, Lauryn Hill and not, like, take the stage until 10 p.m., you know, really just, like, really get the crowd amped up. Actually, to the point of, like, anger. Like, what am I even here for?
One-year prediction. Brian finally joins the podcast.
That's right. And I am joined by Simon Wilson here with me in the litter box. Simon, it's so great to have you here.
Hey, it's really exciting to be here. We've just been nerding out about servers outside on the shop floor. It's been great.
Yeah, so Simon was just like, hey, before we get started, I'd love to look at the machines. I'm like, okay, I've got to do the world's fastest tour of the hardware. And Simon, I promise I'm going to make it up to you with a much more in-depth tour. But it is really great to have you here. Okay, Adam, I just like... I'll just do a little reality check with you.
It feels like this year is more... It's like there's more of a realm of possibility for this year than any year I can really remember.
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Chapter 2: What predictions are made for the next year in AI and technology?
It feels like... If you come back from even a year in the future – in fact, I actually struggled, Adam, in coming up with three- and six-year predictions this year. Yeah. Because I'm like, well, it's kind of three-year predictions or six-year predictions. That's going to be done in a year, this thing I'm thinking of. I know. I know.
It's like – Are you having that same – do you feel that same way?
Totally. Just like everything is possible. And in past years, we've had like a bag limit. That's like, you can only have one crypto prediction or one AI prediction. And I'm like, I struggled to come up with anything that isn't AI or AI adjacent. And you're right.
So let the record reflect that we only made the bag limit mistake once. We did that with Web 3 in 2022. We did a bag that you can only have in prediction. It was a huge mistake because everyone wanted to make three predictions around Web 3. And instead, everyone made one good Web3 prediction, namely this whole thing is going to disintegrate. And this is Simon.
Adam, in particular, made the prediction that is famous to us anyway, that Web3 would drop out of the lexicon in 2022, which ended up being dead to rights. I thought that was a bullseye. Let us not speak of your prediction last year, Adam, that Web3 would re-enter the lexicon.
Yeah. No, that was definitely a dark – I mean, last year was a dark moment, but – much like this year. But yeah, I thought Web3 was going to be back. I also thought a certain book was going to be on the bestseller list. And I did spend a decent amount of time validating that not only was this book not on the bestseller list –
But when it was on the bestseller list in 2024, ChatGPT hastened to point out that it was annotated with the dagger, the dagger which indicates mass bulk corporate purchases gaming the system.
Now, Adam, I know you're hesitating to name the book because you don't want to do it any favors, but you're really going to leave people confused. You're going to need to name the book. I assure you, if I promise you, it will lead to no additional sales. Can you name the book that you're referring to?
I feel bad that I've been hating on this book
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Chapter 3: How will AI impact the software engineering job market in the next three years?
Right, yeah. How do you feel about that one? I feel like that one was right on the money.
I feel pretty good about that one. I said that 2026-25 would not be the year of agents. That one I think I got wrong because it kind of was the year of agents. But I did specifically call out that human replacement agents weren't going to happen. Coding agents and research agents were. And that I nailed. Research agents, the first six months of this year was all about deep research.
And then coding agents... Oh, my goodness.
Oh, my goodness. And I think you absolutely nailed it. I mean, this is why, Adam, we've said this before, but we're glad that we record these sessions. So you're getting more than the prediction. You're getting the context around it.
And if you listen to your context around it, you were very clearly calling out, separating out coding and research agents, which you felt had... It was funny because you were like, these are kind of already here already. And you realize like, oh, my God, they weren't completely already there even only a year ago. They had exploded in the last year.
Yes. There is one thing I'll say, which is that coding agents are actually general-purpose agents.
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Chapter 4: What are the predictions for the future of open source projects?
Like, Cloud Code is not about code. Cloud Code is about anything you can automate by running bash commands, which is everything. So actually, if you know what you're doing, Cloud Code is a general-purpose agent that can solve any problem that you can attach to a bash script.
But I think the delineation that you had last year, which I thought was very good, was these things, anything to do with money. You are not going to let these things loose on anything to do with money. And I think we saw that with a proxy for money databases. And we saw these things deleting production databases, right?
And it's like, I know you said in the readme, you said in all caps, do not touch the production database. And I did it anyway. And you're right. This is a very serious issue. This is a 95 out of 100 in terms of its severity. I mean, it's just like, it's comical what some of these things would do.
Well, this is the thing I realized is that the reason coding agents work so well is that code is reversible. Like we have Git, we can undo our mistakes. The moment you use these things to something where you can't undo a mistake, everything goes to pieces.
I think you're right. Yeah. And I think when you, you said it earlier too, that the gullibility problem was a, was a real problem. And the, I don't know if you have listened to the, the shell game podcast with Evan Ratliff. Oh my God. And Adam, you've, you've listened to that. Yes. You listen to that. Oh my. And I mean, I, it delivered. I trust. Yeah.
It's excellent. I would also say as teaser to risk listeners, we invited Evan on the show. He got back to us and he says he has like a, uh some bah humbuggery around predictions like he doesn't make predictions he's a reporter he reports on on facts he doesn't try to anticipate them but uh we have penciled him in for the future so uh not a predictor but uh we'll get him on somehow
And so in particular, what Evan did is, is he, their shell game has got two seasons. And in the first season, he created a voice agent of himself and set it loose into the, into the universe with wild results. And then the second season is even crazier because he started a company called
with only AI agents and with predictably, actually, it's unpredictably hilarious results, actually, I would say. So that's a teaser for whatever, Adam, is our chime for a future episode. That's our future episode chime.
It's reminiscent of one of the most fun agent business things has been Anthropic. Keep on setting loose this vending machine. Yes. And then a few months ago, they put it in the Wall Street Journal. Oh, my God. Did you see this, Adam?
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Chapter 5: What does the future hold for Tesla and its business model?
They engineered a board revolt. They managed to get the CEO overthrown by the board through faking PDFs of board minutes. It was just amazing.
It's wild. It goes to kind of the gullibility problem. But I think to me, Simon, all that served to really sharpen your prediction from last year about the limited utility of where we're going to see agentic use and where we're not going to see agentic use. I feel that was right.
um and i guess adam did you give that snippet that you sent me was that chat gpt rating our predictions from last year who was that yes yes i had chat gpt rate predictions from last year and from three years ago which is fun ones but yes it it uh chat gpt gave me the the big stinker award for my web three prediction and uh simon and brian you won but i agree with you brian uh i don't really think you won particularly i don't think i
Well, I claimed last year – last year I said that 2025 was going to be the year of AI efficiency, and I don't really see any 2025 wrap-up that's calling it the year of AI efficiency. So I'm happy to – I think that –
I do want to, I want to call out my biggest miss, which is that I said that I think it was my three year prediction was somebody would win an Oscar for a film that had had some element of generative AI assistance in making the movie. And then I found out everything, everywhere, all the way at once used generative AI in the scene with the rocks.
Like, so they'd already gotten Oscar, like, two years ago.
Well, you know, I once gave a talk on predicting the present, Simon. So I think that there's something in that. It just shows how true your prediction was. You actually managed to predict the present. It was actually a six-year prediction, Simon. But yes. So, and Adam, did you, did you go back and listen to that snippet of yourself from three years ago?
Yes. Yes. I listened to in 2023 trying and failing to predict vibe coding, which I think at the time was like, it was not obvious.
No, no, no, no. It was more than obvious. First of all, this is amazing to me. It's like, Simon, when we first had you on two years ago, and the term prompt injection, which felt like it had been around forever, was, I mean, like the paint was still drying. You had coined prompt injection six months prior. So, yeah, exactly. I mean, Adam, vibe coding was coined in February of this year, of 2025.
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Chapter 6: How might AI influence the economic landscape in 2026?
And I think the second half looks very, very promising. Yeah.
In 2024, if you remember, I did the Apple VR will do well in a second version and then that has not happened at all. So that was a big miss.
Yeah. Well, we don't talk about the Mrs. Steve because there are too many of them.
Okay. I'm really proud of my one year from last year, though, because I said congestion pricing in NYC will be an unambiguous success. It will still exist and sentiment will be positive. And the mayor did a press announcement like 45 minutes ago about how awesome congestion pricing is and how much everybody loves it. So I got that one like exactly nailed.
Nice.
There you go. Well, you know, as Tip O'Neill might have said, all good predictions are local. So there you go. You keep that one. Did you catch Tom, I think it was three years ago, predicted that frivolous use of LLMs would be in decline?
Yes. Yes.
Uh, and then also predicted that like LLMs would make cheating rampant. So there is a definitely, uh, but I, that was because 2023 was interesting because in 2022, we've got this kind of crypto. We're all in like web three, the height of web three and 2023 is really the first year that people are kind of talking about the budding power of these things.
Um, but then with, I mean, it's amazing kind of where we are now, three years later.
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Chapter 7: What is the significance of the Jevons Paradox in AI development?
No, I mean, the one purity that we had. Exactly. The foundation upon which we built this internet, goddammit, is cat videos. And you're taking it away from us. And I think it's interesting that the youngs have a keen eye for it, Adam, as you point out.
The other thing that I would like to, just one other past prediction I'd like to revisit is two years ago, I predicted that the LLMs would replace search engines, that search engines would feel, search engines from what is now a year from now would feel quaint. I'm definitely standing by that one.
Considering that my daughter needed to hop a BART train and she was using GPT to determine when the next, chat GPT to determine when the next BART train was. I'm like, are you, like, there's an actual like website you can go to, but you know what, nevermind. But I think that what I'm feeling, I'm feeling pretty good about it.
Actually, she would like to point out that it was her friend that was using ChatGP to teach like that. I, of course, would go to Bart.gov. I'm like, all right, yeah, sure.
There you go. A couple other things listening to previous episodes from 2025 and 2023. In 2025, I predicted – my three-year prediction was a chips crisis, which I don't feel like we're there yet. But I feel like I'm going to keep an eye on that one. I feel like that was not obvious at the time, and I feel like it's gaining momentum.
Are you taking credit for DDR5?
No, no, no, not yet. I think early days are positive, is all I'm saying. The other thing I noticed, and this is more of an apology. Brian, I realize every time Rust Analyzer comes up, I always say that it is not an intervention, which does raise questions.
Are you apologizing because it actually has been an intervention every time you bring it up?
I just feel like the more I claim it's not an intervention, the more it seems like an intervention is what I realize.
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Chapter 8: How will LLMs change the way we perceive coding and software?
But that said... Non-AI predictions, definitely welcome. I just don't know that. So should we start off with one years? Yes, let's do it. As our guest of honor here, do you have some one-year predictions for us? I've got the easiest one ever.
Okay. I think that there are still people out there who are convinced that LLMs cannot write good code. Oh, boy, yeah. Those people are in for a very nasty shock in 2026.
I do not think it will be possible to get to the end of even the next three months while still holding on to that idea that the code they write is all junk and it's like any decent human programmer will write better code than they will.
Yeah, it not only will be mainstream, the idea that LLMs can write effective code, it will effectively become a fringe belief that this can't happen.
That's exactly what I'm saying, yeah. And honestly, that's a gimme. I could say that one today. I think here's one that's AI adjacent. Okay, yeah. I think this year is the year we're going to solve sandboxing, right? The challenge we need, like I want to run code other people have written on my computing devices without it destroying my computing devices if it's malicious or has bugs.
We have so many technologies for this right now that are almost, almost something you can use by default. Like WebAssembly solves this kind of thing. There's containers and all of that sort of stuff as well. I think we have to solve it. It's crazy that it's 2026 and I will pip install random code and then execute it the way
Because it could steal all of my data and delete all of my files. Yeah, yeah, yeah. Interesting. Interesting. So you think that we are going to have to, the presence, or maybe this is not an AI-related prediction, but we have to actually meaningfully solve the sandboxing problem.
I don't want to run a piece of code on any of my devices that somebody else wrote outside of a sandbox ever again.
Yeah, interesting.
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