AI in 2026: Reid Hoffman’s Predictions on Agents, Work, and Creation

From cofounding LinkedIn to backing OpenAI early, Reid Hoffman is in the habit of being right about the future, so we wanted to know what he saw coming in 2026. In his third appearance on AI & I, Hoffman lays out his predictions for where AI will go in the 12 months ahead. He talks to Dan Shipper about how agents will break out of coding into other domains and who’s winning the coding agent race. They also get into how Hoffman defines artificial general intelligence, the way he believes enterprises will use AI, and why public debate on AI might turn more negative, even as the technology becomes more empowering for individuals. Hoffman’s other bets on the future include cofounding AI drug discovery startup Manas AI, investing at venture capital firm Greylock Partners, writing books, and hosting the Masters of Scale podcast. He’s also an investor at Every. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Timestamps: 00:00:00 - Start 00:00:52 - Introduction 00:02:20 - The future of work is an entrepreneurial mindset 00:05:22 - Creation is addictive (and that’s okay) 00:09:22 - Why discourse around AI might get uglier this year 00:17:03 - AI agents will break out of coding in 2026 00:24:18 - What makes Anthropic’s Opus 4.5 such a good model 00:28:46 - Who will win the agentic coding race 00:36:13 - Why enterprise AI will finally land this year 00:43:16 - How Hoffman defines AGI 00:55:33 - The most underrated category to watch in AI right now Links to resources mentioned in the episode: Reid Hoffman: Reid Hoffman (@reidhoffman) The AI drug discovery startup Hoffman cofounded: Manas AI

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  What we will see more of in 26 is a combination of parallelization, longer workflows and orchestration. People will experience what it is to have their computer running separately from them, doing something productive for them as they're walking away to go get their coffee, whether it's a Mac Mini is running Claude Code or Codex. For a company to be a thriving, going and growing concern and evolving with the times, you will need to be recording every single meeting and using agents on it to amplify your work process.

• 0:52Dan Shipper?

  Reid, welcome to the show.

• 0:54Speaker 00

  It's great to be back. And as much as I try to avoid doing predictions, you're one of the few people that I will essay this with.

• 1:03Dan Shipper?

  That is, I feel very blessed. Thank you for taking the time to do it with me. You're, I think, so this is your third appearance on this podcast and that makes you the most frequent guest. So.

• 1:15Speaker 00

  I'm honored.

• 1:15Dan Shipper?

  Feeling is mutual.

• 1:16Speaker 00

  I'm honored.

• 1:16Dan Shipper?

  Yeah.

• 1:19Dan Shipper?

  Okay, so we're heading into 2026. By the time this podcast comes out, it will be 2026. So for all of our purposes is 2026. And I think this time of year is such a good time to look back and look forward. So I want to start with a couple of, you know, pre 2026 predictions that you made and reflect a little bit on how things went in 2025 and what might be different about how you're seeing things. So the first one is we dug up a quote from you in 2017 that said, you thought that the nine to five work model will be extinct by 2034. How has that view, where did that view come from?

• 2:04Dan Shipper?

  And how has that changed in 2025 as we've moved into agent, agentic territory?

• 2:11Speaker 00

  Well, let's see. So part of it was kind of an extension of a very old set of thoughts of mine, which is a startup of you, which is more and more of work and more and more of career will become entrepreneurial. It doesn't mean that everyone is going to start companies or everyone's going to launch new products or any of that sort of thing. But it does mean that the kind of old career ladder, career escalator is no longer the way to think about it. It's no longer to be thinking about like what colors your parachute, you know, kind of thing. It's actually be thinking about your, your, your, your kind of your economic life, your work life, your job life as kind of with the skills of an entrepreneur. And that's part of where that came from. And it wasn't meant to be nine to five is like,

• 2:55Speaker 00

  oh, everyone's going to be working, you know, nine, nine, six, or, you know, kind of equivalent.

• 3:00Dan Shipper?

  Which would have been a good prediction, maybe, for Silicon Valley.

• 3:03Speaker 00

  Yes, exactly. But it's, it's, and by the way, startups in Silicon Valley have always worked nine, nine, six, it even, you know, you know, frankly, nine, nine, seven for how they operate. And, but it's more the fact that, that actually, in fact, the way that you're going to be working isn't going to be this kind of, you know, clock, you know, hit your punch card at the door, you know, be there, take your lunch break, come out at five, but actually, in fact, going to be, you know, running, you know, Claude code on minis in, you know, parallel to what you're doing. You're going to be, you know, in a crunch where you're doing stuff and all of a sudden, you know, this week

• 3:46Speaker 00

  you're doing 120 hour week and the next week you might be doing, you know, 40, you know, kind of, or, you know, 10, as the case may be. And then, you know, the kind that this kind of entrepreneurial journey is actually more of what's going to be happening. And, and I think that we're still on track for, you know, I think, you know, here we are and, you know, 25 going to 26 is, you know, time of broadcast 26. You know, if anything, you know, when you begin to see what the impacts of the fact that that we are going to be, um, you know, kind of how like all of our work is going to be, uh, in enmeshed in agents, um, and in parallel and in management and in and

• 4:31Speaker 00

  all these, which we'll get into some depth on, uh, that actually I think is part and parcel of it's not just nine to five.

• 4:41Dan Shipper?

  Got it. So I think when I, when I read that quote, I was thinking it's not going to be nine to five, meaning we might not be working that much. But you're saying it's, it's more just like an entrepreneurial way of working where it's, it's suffused throughout your life.

• 4:54Speaker 00

  Exactly.

• 4:55Dan Shipper?

  And that actually makes me think.

• 4:56Speaker 00

  By the way, that also can be in some cases, you're just not working as much. I mean, it's, it's much higher range.

• 5:01Dan Shipper?

  If you're Tim Ferriss.

• 5:02Speaker 00

  Yes, yes.

• 5:05Speaker 00

  He's already been doing that already.

• 5:06Dan Shipper?

  I know, right? Yeah. He's got to do a new four hour work week.

• 5:09Speaker 00

  Yeah. The future's already here. It's just unevenly distributed, e.g.

• 5:15Dan Shipper?

  That actually makes me think of one of my hot takes for 2026. So I think we can, we can jump there real quick because I really want to know what you think. Um, we've been on this, uh, trajectory of talking about, um, technology and addicting technologies and social media and how social media breaks your brain. And, um, I think we've put up on this pedestal, the act of creating things as something that is like, can be inherently good and not necessarily addicting. And my experience with Claude Code right now is I'm addicted to it. It's like, I cannot stop. I just want one more prompt. And, um, I

• 5:55Dan Shipper?

  think, uh, shockingly, the most addictive technology of 2026 and the, the narrative that we might be talking about at the end of the year is how addicting it is to just make things. And what's interesting is there's a certain class of people that know that already, and it's CEOs of startups who, who have that experience already because they're, you're always looking at your, you know, your chat, your Discord, your Slack or whatever. And you're always like, oh my God, I need to do something else. But I think now that's like a broadly distributed thing where everyone's just going to be prompting Claude Code.

• 6:29Speaker 00

  So to one, I definitely believe it can be addicting. And I think it's actually addicting for a much broader range of people than normally think. And it's partially because most people just don't have the experience of succeeding at creating. And once you have that, like the dopamine hit is you succeed at creating. And part of the thing that Claude Code, actually AI more generally, generative AI more generally. But it suddenly goes, oh, my God, I can create something interesting. And I think that's the like, it's actually a healthy dopamine hit. I mean, one of the things that's weird about the word addiction is, you know, you say, well, I'm addicted to breathing.

• 7:11Speaker 00

  You know, and so it's like, well, actually, in fact, that's a good thing. It's not, it's, you know, you know, and so, so addiction has this kind of negative overlay. But the fact that you, you, you get very committed to something, it's like, oh, is it unhealthy for you? And actually, in fact, in the creation thing, actually, in fact, it's not unhealthy. And if you're like, no, no, I'm actually going a little bit more obsessive. I'm going like, I want to finish this. I want to make this, I want to make this really great. That's actually, in fact, part of where we, you know, we get our, we explore our fuller potentials, our super agency, if you will. And it's, and it's that kind of thing that I think is actually really good.

• 7:48Speaker 00

  And I do think that it's part of the, the, the kind of generative AI revolution in ways that people go like, you know, I think the discourse is generally, you know, A, quite mixed and negative. And actually will be in more intensely negative next year because of the, of the transformations and changes. But it's part of the reason why it's so important for people to go, go, oh, wait a minute. I can be so much more human doing this and we can be collectively together. And so we need to sort out the fact that yes, it's going to be a turbulently created future. But like, we can do amazing things. And so I think that, that kind of creative addiction, you know, creative commitment, you know,

• 8:31Speaker 00

  creative exploration is actually in fact, you know, one of the actual really important things. And I think people have been discovering it, not just with Claude Code. But also like learning, you know, through, you know, prompting these agents, you know, creating images and, and, and, you know, that's part of the reason why Sora, you know, kind of went to the moon in a couple of weeks because it's like, oh, wait, I can, I can make something here.

• 8:57Dan Shipper?

  That, I think that makes sense. I, I kind of want to know, um, for like, one thing you said earlier is you think that there's going to be sort of a, I don't know if backlash is the right word, but negative, negative sentiment towards, towards tech will increase in 2026. Is that, is that one of your big hypotheses? So tell me about that.

• 9:15Speaker 00

  So, um, so we haven't, so while there's been a lot of discussion, um, the actual overall impacts of AI have been, you know, relatively more minimally felt. And most of the places where they're described as being felt are actually in fact, um, you know, kind of fictional, like for example, oh, AI is causing electricity prices to rise. And really actually, in fact, you mean a little bit here and there, maybe in like certain grids, you know, certain, you know, power stations, but really it's old grids, old power stations, increasing cost of energy, you know, net impact of tariffs and other

• 9:58Speaker 00

  kinds of things. Like if you actually kind of do an analytic map, say where are the data centers, that doesn't actually correlate to, oh, that's where the places where energy price, like, you know, electricity prices have gone up or not. But that's going to be the meme. And so the meme is like, oh, college students aren't going to be hired because of AI. Uh, the meme is going to be electricity prices are going up because of AI. The meme is going to be, uh, the price of eggs is going up because of AI. Like, and so, and because there's a lot of, of people who go, I'm looking around for something to blame for things being troubled, bad, different than I would like. And, you know, it is going to be a very turbulent year. And so AI, you know, it's, it's going to be almost like the, the farmer McDonald's song, you know, AI, AI, AI is going to be

• 10:43Speaker 00

  the, the, the, the, the, the way that this is going to play. And I think it's actually really important for people to understand, actually in fact, you know, AI hasn't had any of that impact yet. But it's actually gonna start like I think it's gonna like for example, it's suddenly it's gonna be like, hey, I used to be really competent at my marketing job, et cetera. You know, I think it'll be the hey, I only want to hire when it's part of an AI transformation. You know, I'll Shopify and that kind of thing for doing this. It isn't going to be what a lot of the employment is, is a reworking of the COVID disaster. And you know, kind of mis-hiring, misorganization, et cetera. You know, for doing this, but actually it is going to start, you know, kind of impacting.

• 11:28Speaker 00

  And then so it moves from from call it 98, 99% fictional to 90% fictional. But that will intensify the desire to kind of say a whole bunch of negative things like, you know, for example, I've been surprised so far at, and I think it's just because people don't pay any attention online. You know, the creation of a, you know, kind of a Christmas record for my friends using AI. I haven't gotten a whole bunch of negative blowback of, oh, this is going to be terrible for artists and terrible for creatives and so forth. I think that will happen like, you know, I'm going to create some more records and I think that will be the case. And I actually think it's not the case. I just think you need to adjust to using it and and creating that as a, as a, as a kind of a,

• 12:14Speaker 00

  you know, kind of as a new basis for your creativity, for your industry, for your work. And, and, and that transition is going to be what's difficult. But I think you're going to have, I think next year is going to be much more negative and AI than actually this year in general popular discourse.

• 12:31Dan Shipper?

  So to repeat that back, I think you're saying so far it's, it's kind of a meme like AI is bad. And the meme and to a lot, to a large extent is making AI a little bit of a scapegoat for just anything bad. If you're laying people off, it's easy to say like because of AI.

• 12:51Dan Shipper?

  And that that will probably continue. I do think that that's true. That's just going to continue. And there's like, there will be increasing real negative impacts that people are going to have to deal with. So you're a programmer and you're coming into work and you're like, oh, man, my job just totally changed. It's like, I'm not in the code anymore. And that's going to be upsetting to people and that's going to lead to changes in the way organizations are run and who gets hired and all that kind of stuff. And that's going to, that's going to make people upset.

• 13:18Dan Shipper?

  What do you think is the right move for big AI companies in an environment like that? And and how they should be talking about it? How they should be positioning? And, you know, to some extent, it's it's probably not even desirable to prevent any kind of backlash. Like, it's normal for people to have like, bad feelings about new things. But yeah, how do you? How do you think? What's the right way to deal with that strategically?

• 13:43Speaker 00

  Well, the most substantive way is to make it pragmatically helpful

• 13:53Speaker 00

  to as many people and as many people. As again, it's part of the reason why, you know, podcasts you and I are doing and other things to say, hey, uh, explore it, get a chance, use it. You can use it for personal things, like if you have a, you know, kind of any kind of serious medical question, you know, if you're not getting a second opinion from, you know, chat GPT or favorite frontier model, you know, you and your doctor are both making mistakes. And, uh, you know, and then, you know, similarly to, okay, how do I use it to help me with my work? How do I use it to help me learn things? How do I help it? You know, help me be creative? And and if you can't in each of those areas, find something

• 14:38Speaker 00

  where it's actually, in fact, seriously, hopefully, you're not, you're not trying hard enough. You're not looking, it doesn't mean it's everything. It's not the Swiss army knife for everything yet. There's many, many limitations. But it is norm, it is enormously kind of amplified. And so I think that's the, and that's part of the reason why, you know, everything from, you know, not just writing super agency, but creating, you know, holiday Christmas gift records is kind of like showing, hey, that's a, that's, this is the kind of thing we can do now. Like, everyone can do this, this not using any, not using any tools that do this. And by the way, not only can everyone do it, but by the way, as the the people who get more expert, like people who are much better at music than I am, which is, you know, cool, 95% of the human race,

• 15:23Speaker 00

  you know, can then do much better. Right, it's it's an amplifier for everybody. And I think that's the the kind of most substantive thing. And then I think. The question, that's the substantive thing. And then on the communications thing, you know, I think one of the thing that, um, you know, various, uh, very well meaning AI creators are kind of saying is like, oh my God, it's going to be a, you know, white collar, bloodbath, etc. And you're like, well,

• 15:52Dan Shipper?

  I think I know one, one, I have one person in mind that you're talking about.

• 15:56Speaker 00

  Yeah. And it's, and it's like, look, it, like, I get it. You're trying to say, hey, guys, things are going to change a whole lot. Really pay attention. I'm, I'm ringing a bell to start adjusting to this. But that kind of ringing the bell is like, you know, kind of a yelling fire in the movie theater. It's like, it's, it's, it doesn't create productive response. The, the important thing is to kind of be orienting towards a productive response. Doesn't mean to be papering over the difficulties of transition. But it's like, oh, um, you know, we're going to be going into like this intense, you know, category 10 rapids. And here is, here's the kind of paddles you need. And here's the kind of thing you should be doing as you're going into it.

• 16:39Dan Shipper?

  That's the thing you want to, if you're going to say, we're going into the rapids, you want to offer the paddles too, you know? And if you're just saying we're going to the rapids, that's not really helpful, in my view.

• 16:48Speaker 00

  Yes, exactly. And that's, that's, that's, I think, the comms part of it for everybody.

• 16:53Dan Shipper?

  Yeah. If 2025 was the year of agents, what's 2026?

• 16:58Speaker 00

  Well, um, by the way, I, I think there's an interesting thing on this. So I don't think actually 2025 was fully the year of agents. So a lot of agentic development. But I think it was actually mostly only agents and code, right? So, you know, Claude code, codex, etc. Of which, by the way, a relatively very small percentage of humanity actually, in fact, fully experienced, right? Like, if you go to the vast majority of the people you and I know, they're like, well, you mean, you mean, you mean agents all I asked chat GPT a few questions? And had some dialogue? And it's like, well, no, no, no, that's not actually really agents. And yes, there's a chatbot, but it's not really agents. Agents is doing stuff and doing it in

• 17:40Speaker 00

  parallel and doing it in amplification and so on. So I think code had that. But what I think actually, in fact, 26 will be is how we move from

• 17:51Speaker 00

  This kind of basis of agentic, you know, coding agents to agents and everything else. And actually, in fact, what I think that A, there's just going to be a whole bunch of that. Like, for example, like, call it 10 to 100x of people will experience what it is to have a their computer running separately from them, doing something productive for them as they're walking away to go get their coffee and then, and then coming back. You know, whether it's, you know, Claude mini's, you know, a Mac mini is running Claude, Claude code or, or Codex, um, different questions. But like that, you know, applied to a lot of other things because that orchestration then allows

• 18:36Speaker 00

  the parallel allows, you know, eight hours of work allows, you know, that kind of thing. And I think that will be broader. And then the more subtle thing, which I think will also be a really important part of 26 is orchestration. Namely, like, okay, if we begin to have, like, you know, hey, when I'm doing this particular form of intellectual knowledge work, thinking work, cognition work, et cetera. And I now have agents working with me, for me, et cetera. And then I'm orchestrating them. I think orchestration is the thing that will be, you know, I don't think it'll be March 26. I don't think it'll be more Q4 26 or kind of growing into that. And then maybe even intensively 27.

• 19:19Dan Shipper?

  I totally agree with that. I think it's something we're starting to see already.

• 19:24Dan Shipper?

  And it actually, it, it brings me to perhaps my hottest, my hottest take that I would love your input on. Um, and it starts with coding agents, which is, I think that OpenAI is currently missing the real coding market. Because they are not, and they're not really, uh, when, when you think about orchestration, I think of orchestration as being something that's enabled by tools, but it's also enabled, it's like, it's a new skill. It's a new skill for programmers. And when I look at the stuff that OpenAI is producing. I think it's really made for programmers who use AI, like senior engineers who use AI, which is different from AI native engineers who are like just in for Claude code terminals

• 20:08Dan Shipper?

  and are never looking at the code. And it's really valuable. Like the models that they make are really good. If I have a really hard technical challenge, it is, I definitely go to Codex to be like, okay, figure out this like crazy performance bug that I can't figure out. But I don't see them orienting toward this new skill of, it's not vibe coding, but it's not traditional engineering with AI added. It's this third thing that is, I'm, I've got four Claude tabs open. I never look at the code. I'm thinking about how to orchestrate. I'm thinking about how to plan. I'm doing all this stuff and, and I'm technical. So I can, I could go down to the code, but I never do. And I think that's a really interesting thing that

• 20:51Dan Shipper?

  I'm kind of noticing and I, OpenAI is like not used to being behind. And I'm very curious about how that's going to play out. What do you think?

• 21:02Speaker 00

  Well, I think, I think it's one of the skills that OpenAI is going to pick up to, because you know, part of what's happening, like, you know, the thing that, you know, this will be great for media because each month it'll be in the horse race, it'll be like, oh my God, Opus 4.5, oh my God, you know, GPT Codex, oh my God, you know, Gemini, oh my God. And because all of them are going to be developing. And what that means structurally is that some of the things where, you know, as opposed to a couple of years where it was literally just OpenAI blazing ahead. And I think this is good for the world and everything else. Like there'll be areas where, for example, Anthropic just did super smart stuff in making Claude code and that,

• 21:44Speaker 00

  and that iteration and took, you know, kind of, as it were, less capital and less depth of compute, but still made stuff that was pretty amazing. And I think that OpenAI will, this is one of the benefits of how competition, you know, kind of benefits industry, benefits society. I think that will make them pick it up and go, okay, we can't be behind on this. We gotta be learning to do this. We gotta be making this happen. And I think that's, that's what will happen. It'll be painful. Competition frequently actually is kind of painful as you, as you push your way on this. But I think that's the, that's the.

• 22:21Speaker 00

  I have a pretty strong belief that that will be the the the the end result. Now, I do think that it's like, you know, credit to Anthropic, that the notion of focusing on code is not just a code product, but an amplification of many, many other things, an amplification of obviously, you know, AI progress and development, but also an amplification on on frankly, every other form of information slash knowledge work, and maybe even much more, many more things. And I think that's one of the reasons why frankly, every kind of major player actually in fact has to be, you know, kind of

• 23:05Speaker 00

  capable at minimum in code, if not leading.

• 23:10Dan Shipper?

  Yeah, I mean, they they did this. It's such an interesting point. They they got to the general purpose agent architecture by just making a great coding agent that had all the right primitives.

• 23:22Dan Shipper?

  And I got to tell you, like, if you look at the software that we developed over the last month or so at every since Opus 4.5 came out, pretty much every new thing we're building, and I like I built this entire end to end reading app. We have this AI paralegal we've been doing for a while that has just got a huge upgrade. Every single app is just Claude code in a trench coat. And it's just basically UI wired to if you press a button, it hits a prompt that has an agent that has a bunch of tools that does the thing you want it to do. And it is the coolest way to build software because it's so much more flexible. Users can modify it. It's just like it's it's just exactly right. And it's so such a pleasure to see someone figure out those primitives.

• 24:00Speaker 00

  Yep. And and and massive credit to the Anthropic team for doing that. And basically, you know, everyone else, hey, you should be, you should be learning from it, building on top of it, trying to iterate to the next generation. Whole set.

• 24:18Dan Shipper?

  Do you have a thought on why Opus is Opus 4.5 is so good? I I'm assuming you think it's that good. I think it's I think it's the best model I've ever used. It's like this crazy leap for me. I'm curious if you agree. And if you do agree, do you have any thoughts on how they managed to do that?

• 24:34Speaker 00

  Well, I think it's amazingly good. I don't know if it's if it's the everything model for me. I mean, I think to some degree.

• 24:46Speaker 00

  You know, kind of, I think G P T five Pro with Codex also is, you know,

• 24:55Speaker 00

  pretty amazing on a lot of levels. And by the way, like, you know, Gemini three on like, science topics and so forth. So like, it's kind of, I still am kind of in a, hey, I bring, you know, all three of them with me to various things I do. Now, that being said, I am very curious about how they they pulled four point five together. And and and one of the mistakes that outsiders think is they think, oh, you just apply scale and, you know, you press play on compute and some of it works and some of it doesn't. And actually, in fact, there is both a lot of both science and art to do it. And it's one of the reasons why, you know, obviously, you know, Meta has needed to restart its kind of A I efforts, because you can't just go, oh,

• 25:37Speaker 00

  I throw a bunch of compute at it and it works. It has to kind of like relearn these things in terms of how it's playing. So I'm, I'm, I think it'll, because, you know, one of the things is, you know, the, the, the techniques, you know, kind of spread out very quickly. So I think we'll learn. But I actually don't know what the, what the, what the, what the new, the new genius was in in Opus four or five. Do you have any, do you, you have any hypotheses?

• 26:04Dan Shipper?

  I have no idea. I, I think the, the only thing that I can think of is recently,

• 26:10Dan Shipper?

  we got a view of the, the underlying like soul document of, of Claude. And the, the interesting thing that, that I feel from Opus, and I agree, like, I use Chat G P T as my daily driver, to be clear. I use it for everything. But when I'm building software, except for like, specific performance things, or like, hard bugs, I'm using Opus as my daily driver.

• 26:32Speaker 00

  Yep.

• 26:33Dan Shipper?

  I think that there's usually this trade off that you see a little bit with Codex, where the better it is at programming, the less like empathetic it is. Like, it just feels a little bit more like a senior engineer. It's slightly more autistic or something like that.

• 26:48Dan Shipper?

  And Opus, they sort of figured out how to make it both sort of humanistic and, and understand users and, and, and what I might want and what I might mean and how interfaces work and what like a good interface is. And it's a fantastic programmer. And something about a soul document where it tells it, this is who you are and like what you care about and whatever. It's one example of, I think, anthropic thinking about these things in a, in a, maybe a bit of a more holistic way to, to create a being rather than a tool. And I, I think that that is actually going to be a big deal going forward.

• 27:24Speaker 00

  You know, it's interesting. Um, you know, this is one of the things that inflection kind of started with kind of EQ and actually soul is a very natural, you know, because the inflection start and there's still a lot of ways in which Pi is still, you know, in amongst the leading of the kind of, uh, you know, having a, a richly textured, you know, kind of conversation agent, like focusing on EQ as much as IQ, like, no, not slouch on IQ, but like putting the two together. And actually a soul document, actually, I think is, is maybe the next, you know, because this is what we learn in it, right, is actually great. And it's, and it, it's part of what of course makes Claude code work because it's

• 28:05Speaker 00

  actually in fact, a really good human amplifier and like kind of what, what kind of how do you operate that way? And then, you know, you get better performance if you can interact in that way, the right way. So I think that's a, a good insight. I suspect there's other thing. I think we both suspect there's other things too, and we'll, we'll hopefully learn them in the next few months.

• 28:26Dan Shipper?

  That would be great. Um, so last thing on the coding front. So you, you mentioned the horse race earlier and there's, everyone's going to be trading volleys and, but if we, let's say we want to, we don't want to be fooled by randomness. We don't want to like, you know, uh, track every little change. We, we hit the snooze button and we come back at the end of 2026. Where do you see the landscape of who's winning in the coding agent race?

• 28:50Speaker 00

  Well, so I think it'll, I don't know who will be winning, but I think it'll be, what I, what I would predict strongly is that,

• 29:00Speaker 00

  The the horses that are leading now will still be like neck and neck. It'll be like in in the first hundred meters, this one's a little ahead. Then the next hundred meters, that one's a little ahead and, you know, da, da, da, da. Like, I don't think that the horses that are in the race, any of them will particularly stumble. Right? So like, you'll go, wow, I thought, you know, cursor was really was really fantastic. And it's just gone. Like, I I think that none of them will stumble. Now, I do think what will interesting is the folks who are not in this at all, like, you know, say, like, the easy one to pick on, Apple, right? Despite the fact we use, you know, Macs for our various things, but the AI part of it is, you know,

• 29:43Speaker 00

  nonexistent, is, well, I think the gap will be like even more stunning. The fact that you actually haven't gotten what this coding amplification, everything else means. And I think that will be will be playing out more. But I think they'll they'll all be in the mix. And the thing will be interesting will be not as much as which one will have stumbled out. But I'm really curious about like, what are the one or two, you know, like superstars that will really, you know, get in the mix more? You know, will Replit be more general? Will Lovable be more general? Like, like, like, will those be or will it be something else?

• 30:27Speaker 00

  I mean, and part of what's like, like, with with some high probability, something will surprise us here.

• 30:36Dan Shipper?

  Yeah.

• 30:38Dan Shipper?

  I don't know what it'll be, but predicting surprise.

• 30:41Speaker 00

  Yes.

• 30:44Dan Shipper?

  Yeah, I think that I think that's interesting. One of the things I've been toying with is the stakes are so high and programming is such a obvious use case that is so economically valuable. And it feels like everyone is just like, it's now a night fight for programming. And I wonder if there are, you know, you've been predicting AI will be used for more creative use cases for a while. I wonder if the the surprise entrance comes from a place like that where we don't necessarily expect where it's not actually about programming. The one like caveat to that is, like you said, Claude sort of invented this general agent by being good at

• 31:25Dan Shipper?

  programming. So there's, you know, it's hard to say exactly, but I wonder if that that is coming like it leaves them vulnerable to competitors from from other places because they're just focusing on programming right now.

• 31:36Speaker 00

  Well, I definitely so I do think programming is part of the architecture for getting everything else. And like, for example, part of the reason why coding is important is that even when we get to, hey, how are you going to have a much better paralegal, I'll know what you're doing, among other things, better medical assistant, better tutor, etc. I think coding will actually in fact be not just the amplifier of it, but the fitness function of, you know, how do we, how do we kind of like, you know, kind of go, hey, this is getting better. This is amplifying the work better, etc. That parallel, not just the the the foundations of coding driving, planning, you know, longer work, paralization, orchestration, etc. But also, like, well, how

• 32:21Speaker 00

  does like a better legal document work will actually in fact also be coming out of it. And I think some of that will also be in creative, like it's, it won't be surprising to me. Like, obviously, everyone's trying to figure out, like, okay, how do we, well, not everyone, a number of people trying to figure out how do we take, you know, V O Sora, etc. And then, and then go, okay, can we create a 30 minute movie off it? And, you know, the coding like pattern will be part of of of what happens there. And so can be in those kind of creative. Now, obviously, you know, some of the more interesting possible surprises are

• 32:59Speaker 00

  Well, because there's a number of different efforts trying to do this too. Well, could we get raw ideation, like better at science? So like, we read a whole bunch of science papers and we can do scientific hypotheses. Now, by the way, you begin to say, well, maybe that'll also be true of like AI research and ideas for doing this. And suddenly it's doing idea generation in this kind of thing. And that's, that's definitely a whole bunch of projects trying to work at that. So the notion of, hey, if you can think a lot better, you can then, you can then apply that to this kind of creativity and this kind of new ideas. Those I think are much more speculative.

• 33:42Speaker 00

  Like it's, it's, it's an interesting hypothesis. There are people who will hold them saying, hey, we've just seen that with scale, learning and compute. And it's going to happen. And I'm like, well, look, it's crazy that everyone smart should assign a non-zero hypothesis, you know, probability of that, because that's really amplifying. But on the other hand, I think it's like, nah, it's not clear that we're, we're yet seeing any of that. Even when you see people like, you know, Terrence Tao saying, hey, I'm using, you know,

• 34:14Speaker 00

  generative AI to help me understand where I should be thinking in my, in my math analysis. And yes, but yeah, I think a hundred percent. But of course, Terrence Tao is one of the most, you know, genius mathematicians of our age and is providing a ton of the metacognition in this.

• 34:32Dan Shipper?

  That makes sense. Yeah, I think I'm trying, I'm going back to your, your comment about no one stumbling. And I'm trying to like one, I'm wondering who would stumble if there was a stumble. And I think my current feeling is I would, I would guess cursor.

• 34:48Speaker 00

  Yeah, that's probably the highest likelihood.

• 34:51Dan Shipper?

  Not that they go away. They're obviously going to be a successful company, all that kind of stuff. But I, I think that they're caught a little bit in the same position that OpenAI is. But OpenAI has more flexibility here where cursor.

• 35:04Dan Shipper?

  A lot of their business is built on traditional developers using IDEs with inside of big companies with AI on the side. And they're sort of caught between that paradigm and this totally new 2E Claude code type paradigm and they're they they kind of have to do both. And I think that's going to hamper their product direction and velocity in a way that I would bet in a couple of years will look back and be like, that was a interesting era. And it's still like a widely distributed piece of software, but it's it's not the next generation thing that we thought it was.

• 35:35Speaker 00

  That's I agree. And that's one of the reasons I brought it up in the other one. I've been thinking about that is like the the hardest. And in another angle of that is, you know, how are we going to be not just integrating the kind of the application functionality UI, but the the underlying model and compute fabric capabilities. And, you know, cursor is is is just beginning to do that kind of stuff. And, you know, what the shape of that is and does is going to have to be dual targeted, like you mentioned, or multi targeted. I think it's a it's a it's a harder slalom race for them.

• 36:13Dan Shipper?

  I think the narrative right now is that enterprise AI deployments are not doing as well as hoped, as people hope.

• 36:20Dan Shipper?

  What do you think the narrative will be in the enterprise by the end of 2026?

• 36:24Speaker 00

  Well, I think for sure there will be some intense usage. And the one that I've been predicting that I think a lot of enterprises will get out of their way on is just amplify coordination, you know, meetings, et cetera. Right? So a lot of them say, like, the obvious thing to do now is record every single meeting and run AI agents on it. Not just to transcribe it, but to say, hey, what are like, who are who in the organization should be notified about stuff? Who who should be asked about stuff?

• 37:04Speaker 00

  Where action items are following up on, you know, like a whole set of things, what what what what what? You know, team of agents should start working on some of this stuff and preparing for the next thing. What what should be the briefing for the next meeting, you know, off this? All that stuff should be done. And I think that people aren't doing it because. They're like, well, shit, I'm worried. Does it, does it get the legal liability? You know, um, you know, we never really recorded everything that was happening in this and someone made an off color joke and does that, does that have a problem? And, you know, and I think actually, in fact, part of the unlock to this will be also using agents. So you go, okay, I'm worried about legal liability. Well, here's the legal liability check agent that, that can go, you know, because

• 37:48Speaker 00

  you're not, we're gonna scrub, you know, anything that, or change it, anything that, that we think is actually in fact a, is, is a real issue. Um, or, um, things like that. And so what I would say is yes, it'll be much more intensely positive. And I think it'll be positive because we'll have two groups of things that will be now in real deployment. One is like, I think maybe by the end of 26, if you're not, yeah, let me state this a little bit more crisply. If, if you,

• 38:28Speaker 00

  for a company to be a thriving, going and growing concern and evolving with the times, you will need to be recording every single meeting and using agents on it to amplify your work process. And by the end of 2026, if you're, if you're not doing it, that's because you're making excuses. And actually, in fact, it's a little bit like, hey, you know, these cars won't be a big thing. We can keep doing our horses and buggies. You know, that, that, that, that is, I think, one. And then two is, um, that you will start systematically deploying,

• 39:07Speaker 00

  groups of agents in various problems. Um, and that's part of the reason why I tend to think that, you know, if you said, hey, I need to predict what the next thing is, it's orchestration, because it's groups of agents doing things. And that's part of the reason why, like, I don't think it'll kick off Q1 per se, but like, will grow through 26 and then, you know, whether or not 26 is orchestration year or 27 is orchestration year, that's, that's, that's the reason why you have a high prediction there.

• 39:36Dan Shipper?

  I totally agree with you. I think it's so clear to me that agents are going to Reshape how we think about doing company operations. And the my, one of my big proof points for that is just internally. We did our 2026 planning with an agent. And basically now we're like 20 people. So it's like the first time we have to do like a real planning type exercise for, you know, every department and budgets and like all that kind of stuff. And so Brandon, who's our COO, made this agent that for anyone in the company, it has access to all of our, you know, all of our notion and all of our data. Anyone in the company that that has a, that is a leader in the company, talks to the agent.

• 40:19Dan Shipper?

  And it asks them like really interesting questions about, okay, how does this, you know, let layer up to the overall company strategy, which it has access to? What kind of resources do you need? Here are some tough questions to think about decisions you might need to make. And then basically we have this notion page now, and it's just like every single department has this like really crisp, really clean strategy document that someone has gone through and it levers up into the like the overall company strategy. And then you can do all these amazing things like.

• 40:54Dan Shipper?

  The first thing I did was I had Claude be like, okay, who's not talking to each other that should talk to each other? And it found all of these strategy, strategy documents that like, I needed to get three people in a room together to just like figure that out.

• 41:08Dan Shipper?

  Or another one is, you know, you do a strategy document and then you forget about it in Q1. You're making a decision and you forget about the overall strategy or what you said you were going to do. So one of the things I'm going to do over Christmas is I have, we have this, this Claude code in a trench coat running in our Discord, which is, we use that as our internal chat. And it's called R2C2. And I'm going to basically have R2C2 listening in. And anytime we're making a decision, I can just tag it and be like, hey, how does this, how does this lever, layer up to the like 2026 strategy for this department and the whole org? And like, how would you think about it?

• 41:50Dan Shipper?

  And it's a, it's a sort of way to kind of make that, make those documents more alive and more like woven into the everyday of how you make decisions. And I think that's so important and exciting.

• 42:03Speaker 00

  Yep, I think that's exactly right. And that's that's the broader version of just doing the coordination on meeting is how well, how does the coordination of the meeting also relate to, you know, strategy, changing conditions in market, changing conditions in competitors, et cetera. And, you know, like, this, this is, this is the tangible substantiation of what is AI mean is that you have intelligence at the scale and price of electricity. And so that means that, you know, previously where you had to be extremely selective about where you applied intelligence, because intelligence is always kind of through high priced, you know, kind of human talent, which, by the way, I think will continue. But then you go look, let's, let's, let's apply it all in all these other places as well.

• 42:48Dan Shipper?

  Yeah, totally. And, and, and by the way, like, once you have that free intelligence, you can put the information that you need everyone to consume in lots of different formats. Like, we have a vibe coded 2026 strategy app that people can like click through. And we're going to do a podcast and there's all this stuff where it's like, you don't want to read this long document, just listen to it on your run. And, and it just helps make the whole company get on the same page in a new way.

• 43:12Speaker 00

  Yep, no, exactly.

• 43:15Dan Shipper?

  Uh, okay, AGI timelines. Where, uh, are we going to hit AGI in 2026? If not, uh, when are we going to hit AGI? Depending like whatever your, for whatever your definition of AGI is.

• 43:27Speaker 00

  Yes, well, this is, this is you have to start with, what is AGI? And, and, and, you know, my usual joke here is AGI is the AI we haven't invented yet. So, so each, each year, we're not going to hit there. Because in one sense, we have created AGI already. Like, if you say, hey, if AGI is, uh, that you have a variety of tasks where the, um, the AI is, is, is substantially better than your average human, the answer is already. Like, for example, in writing, AI is better than most human beings at writing in various ways, in terms of the vast majority. Now you say the good writers, no, well, good writers, it's a little bit more mixed, although good writers should be using AI to amplify themselves. Et cetera, et cetera, et cetera.

• 44:11Speaker 00

  And there's a bunch of areas where it was already super intelligent. It has a breadth of knowledge. It has an ability to, to work at a speed that, that human beings simply can't. So if you say, hey, I'd like a, I'd like a report on this, or I'd like to understand this kind of thing. It can work at a speed that a human being can't, which is part of the reason why they, it needs to be used in that player. Now, we've always had. You know, uh, speed multipliers, planes, cars, etc. This is just cognitive, so it's weird and new and all the rest. Now, um, so I think, you know, we've got forms of superintelligence already. We have forms of AGI already. So they go, okay, what's the definition for what will be 26? Now, a little bit of that is, I think, um,

• 44:55Speaker 00

  what we will see more of in 26 is a combination of, of parallelization, longer workflows and orchestration, which means that the notion of, um, of I now kind of, and that's part of the reason why I like getting more to the realization of what agents are. I think we'll see more of that. And so it'll play more towards the, oh, like, I don't think we'll have the press button, get, you know, full human capable software engineer who's like, I'm ready to do the thing that you've asked me to do. Um, which is, I think, what, you know, the sci-fi and kind of thing that people are looking for.

• 45:40Speaker 00

  But I do think you'll see kind of much more of the, hey, I come in as a human engineer and it's like, I'm only really capable of I've got my, my, my, my team agent set, tool set that I'm deploying on various things. And the way that I do them is not just kind of like looking at the suggestion for inclusion for the type ahead in my code. But as you were mentioning is like, hey, look, I, I, I set this one and this one and this one and this one. And I actually, in fact, because part of what I have agents doing is I have them cross checking each other's code. So I'm not actually even necessarily re, uh, it like I'm running a bunch of it where I actually haven't looked at it. Right? Partially because I'm like, oh, if something breaks, then I'll look at it.

• 46:24Speaker 00

  Or I'm also expecting to have my, my coding cross check agents going, hey, you might want to pay attention to this. I'll go, okay, I'll go look at that, you know? And that kind of thing is, I think, the, the, the sort of, of, of AGI we're going to have applied to a, to a broader range of topics. And so it'll be more in the, hey, this is actually doing real work. In a more broad sense than just the, you know, the, the, the coding application we've had.

• 46:59Dan Shipper?

  If you, if we listed out the holy commandments of AI. So thou shalt always scale, compute and data. Or thou shalt always align your models and make sure they do exactly what you expect them to do as as much as, as much as possible. And there are probably more. Which holy commandment do you think will need to be broken or will turn out to be misapplied or irrelevant? So I'll give you an example. I feel like all of the alignment, the way that we do alignment has turned, like has, has created models that are sycophantic and kind of do, they're people pleasers. They do what we want them to do, more or less.

• 47:43Dan Shipper?

  And if you really want a good engineer, we're going to find that allowing models to have their own opinions and values and desires that are distinct from humans is actually an important part of creating models that can do more in the world and be more autonomous. And the trade off is that they don't always do exactly what you want. And that's a, that's a new thing that we have, that we're going to have to get used to that I think is against the received wisdom of, of how you should build AI.

• 48:14Speaker 00

  Yeah, obviously that's tricky because you don't want them to, you know, Allah, the old paperclip problem. You don't want them to be misaligned in ways that are serious, like in ways that are like, hey, I know what you want better than what you think you want. And look at what I've delivered is better. That is kind of what you want. You don't want the, oh, what I really want to do is, you know, like, you know, strip mine your, like erase your hard drive. You know? And so, um, and like, for example, he said, well, I think what you really need is more time outside. So I'm going to actually lock you out from your computer and your devices for the next three hours, just to make sure that you go get that time outside. And you're like, no, no, no, no, don't want that. So, so that's tricky.

• 48:58Speaker 00

  I would say, um,

• 49:05Speaker 00

  Let's see, it's interesting. The change of commitments, I mean, what I've been, my head has been mostly wrapped around is, what does it mean? Like, almost goes back to this iconic Marvin Minsky book, Society of Mind, is, it's, you know, tribes of agents. And so I tend to think a little bit about how you get opinionated is, is like you set up agents that are deliberately, like, like debating.

• 49:37Dan Shipper?

  Intention, opponent processors.

• 49:39Speaker 00

  Yes, opponent processors. And that's actually part of how you're solving things. And it's part of how you get that, that, that more variation. And I guess I would tend to think that you'd still want the orchestrator not to be sycophantically aligned, but to have a very good sense of what it is you're trying to do, right? And even if you have, if you're fuzzy about it, or you're wrong about it, it's actually in fact drive, like helping you be better about that kind of thing, as opposed to ultimately going, well, I'm gonna go in direction X when you think Y. And so, so I'm not sure I buy into the orchestrator thing

• 50:21Speaker 00

  the way you do, but I guess, you know, what I might, um,

• 50:29Speaker 00

  what I might say is kind of an interesting question is maybe where, um,

• 50:38Speaker 00

  the notion of, kind of, like, like this might be, and I'm a little worried about this one too. So even like giving this one, I'm not sure I would want this one to be exact. It has a similar shape, which is like currently, we have a very, uh, natural thing where we try to say, hey, look, we're trying to get as much interpretability of the agents. We want, like, one of the sci-fi worry cases is they start speaking in languages to each other that we don't understand, and what, what does that mean? And that becomes further out of control and may get more in the paperclip direction and a set of things to kind of pay attention to that. And I, you know, I think those are good questions and should be paid attention to.

• 51:21Speaker 00

  They're not, they're not, I don't have the ten out of the fire, the five fire alarm construction of them, but I do think it's an important, something could go seriously wrong and is worth paying attention to. Now, maybe what I think is the thing is to say, actually, in fact, what we want is we want a speed of coordination between the agents and a communication where this, that where what might be tolerable and allowed and shaped in certain ways is the same way that when you have these generative AI models where you say, well, I can't look under the hood and know what's going, like I can't know, I can't look at that and prove that it's not paper clipping the world or something as a way of doing it.

• 52:04Speaker 00

  That may also be true of the comms fabric of how they're coordinating and kind of what the kind of the fitness and, and part of, because I want the speed of coordination, the speed of learning between them to be such that I'll accept parameters of lack of interpretability there. And that's super scary in some ways. So I'm not like it's, I say this is like, ah, how would we shape it? And what, what parameters would it be okay? And so, but I do think we will tend that direction. So that would be, that would be an area. It's a little bit like, actually, maybe one of the things that else also might be is like another commandment was don't do self-improvement. Don't allow these self-improvement. And yet, in many ways, we are doing forms of self-improvement, not just like data modeling,

• 52:49Speaker 00

  but like coding and that wrapping back and so forth. And that's going to continue in certain shapes. And so what, what shapes is that okay? And what shapes is that not okay? Is I think, you know, where the commandments at least changing.

• 53:03Dan Shipper?

  Yeah, we're, we're going to have to do some legalistic, you know, interpretation of, of the commandments. So all of our Talmud scholars are going to be newly employed as AI researchers. I love that. I think that's so right. The first people to, to just take the risk to be like, you can communicate in ways we don't understand. I think it, yeah, there are so many gains to that and it's so anathema to AI safety that I think it's, it's really been a commandment. And, and I, I bet there are ways to make it like, make the boundaries of that safe.

• 53:36Speaker 00

  Yes. So we'll need to work on making the boundaries it's safe, but I think that will happen.

• 53:41Dan Shipper?

  Yeah. One thing that I actually think, going back to the previous point is about AI that doesn't do what you say. And, and that being kind of, my, my contention is, it's, I think that that actually may be really useful for autonomy and doing interesting things that we wouldn't predict. And I think your contention is that's a horrible user experience. One way to potentially square that circle is once you have an orchestrator that is aligned with you and you do trust. It's okay if the orchestrator is using an agent that's a pain in the ass. Because it could be like, I don't care what you say orchestrator, I'm going to go off for three months and do this thing. And the orchestrator is like, oh, fine. Like, I'll get most of it done with this other set of agents that actually follow my instructions.

• 54:24Dan Shipper?

  But this one is just off doing its thing. And every once in a while, it comes back with something brilliant. And that's actually valuable and important. And having a good enough orchestrator allows us to move in that direction because the human doesn't have to deal with the bullshit.

• 54:37Speaker 00

  Yep, that's what I was gesturing at. That's the reason why the orchestrator needs some deep alignment. But the orchestrator might have agents that are like, hey, I think everything you think is bozo and I'm going to go try something else. Okay, go ahead. Don't just go do it. Bring it back to me. But, you know, go, go research it. That's great.

• 54:56Dan Shipper?

  Okay, we're almost out of time. So I've got one last question for you. What is the most important undersung category in AI that we're not talking about right now that we will be talking about at the end of 2026? And I want to put some restrictions around this. So a couple of the categories that that may come to mind are like robotics or science or something like that. But I want to get, I want to get more specific and have like a really specific, concrete reason that you think that that thing will be

• 55:25Dan Shipper?

  valuable and important and, and something that we talk about a lot in 2026.

• 55:33Speaker 00

  Well, I'll choose one that's a little, it's just because I'm close to it. It's not really self-serving, but it's close to it. I think so right now.

• 55:45Speaker 00

  The vast majority of stuff we're doing is extremely close to human language. So it's either obviously human language itself or coding or kind of cool. And I think we will be doing a lot more in-depth models of things that are not close to human language. So for example, biology, and this is kind of part of the reason is because of all the work that we've been doing with, you know, Manus AI with Senator Muggerji and Usual Singh and kind of understanding that, you know, it's a frequent trope to say biology is a language. It's actually one of the reasons why I'm kind of focusing on it because if you kind of go world of atoms and bits, bio is kind of, is kind of not fully atoms and closer to bits and has a kind of a programmability, kind of compute characteristic to it, you know,

• 56:29Speaker 00

  exactly how it's compute is still a little bit DVD. You get people like, you know, Penrose, you know, arguing what's unique about human cognition is, is, is quantum computing effects and so on. And it's an interesting question. And then, you know, what's the borderline between being able to simulate quantum and genuinely quantum is, you know, what is, what comes of that is all kind of interesting questions. But I think what this results to is what I think we will see is things that were the generative AI, you know, model building out of data and prediction and everything else will be out of, call it computational sets or language sets that is further afield from human language. And obviously, I think

• 57:14Speaker 00

  biology is probably the most natural one where that would come out of. And obviously, you know, I've been working on that and thinking about that intensely, of course, because of Manus.

• 57:26Dan Shipper?

  And what's the big concrete impact that will have in 2026 that will cause us to be talking about it a lot?

• 57:31Speaker 00

  Well, the one we're going for is amazing new, you know, biological therapeutics or, you know, kind of understanding. I don't know if 26 will be the full, full hit there. I mean, there's a probabilistic curve, but it wouldn't surprise me if.

• 57:54Speaker 00

  You know, um, you know, would you get the equivalent of kind of a move thirty seven in something around biology, right? And might be it's a molecule that makes a, you know, that makes a massive difference, you know, man, us trying to cure cancer, et cetera. And we discovered something that was not like, what I would hope maybe as a reasonably high probability is we discover a research possibility like I, oh, this might be one of those things. This might be, it's like, you know, probability twenty seven percent that this is a move thirty seven in this, this arena. And maybe that's the twenty six.

• 58:34Dan Shipper?

  That would be amazing. Reid, always a pleasure. This is so fun.

• 58:39Speaker 00

  Likewise, Dan. I look forward to seeing you in the new year.

• 58:42Dan Shipper?

  Sounds good.

• 58:51Speaker 02

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