OpenAI’s $100 Billion Funding Round, OpenClaw Acquired, AI’s Productivity Question

29:13So very interesting development, actually, on the model front. We hinted at it before. Anthropic has a new big model, Sonnet 4.6. and you've said that it is a major upgrade over the most recent model, 4.5. We usually expect these single digit models to be incremental updates, but the stats that you shared on your evaluation for complex work are pretty significant where there's been a 15 % percentage point jump in performance and accuracy between 4.5 and 4.6. This is from you on Twitter or X, shall we say. In the public sector, you saw a jump from 77 % to 88 % in accuracy for complex tasks. Healthcare saw a jump from 60 % to 78%, and legal saw a jump from 57 % to 69 % accuracy on complex tasks.

30:08That's pretty big. It seems like this model has almost been underhyped. Can you talk a little bit about these jumps and what the significance is? I think I think probably the main takeaway should be that that the progress of these meaningful jumps that we've been seeing in AI coding over the past couple of years where, you know, the model at best could do a couple lines of code, you know, in a kind of type ahead type format to two and a half years ago in in coding space. And now obviously people are giving the model a task of, you know, write me tens of thousands of lines of code for a full project.

30:49And we've just seen this incredible rate of progress and this march up toward, you know, more and more capability over time with encoding. I think that same trend is going to come to other other now fields of knowledge work. And so so this jump in sonnets model from four or five before six, I think represents an example of what happens when these models just get trained across more areas of knowledge work. What happens when they are getting better and better at reasoning capabilities that go beyond coding? What happens when they get better at using tools and deciding when to use tools? and that's what our complex work eval, you know, is meant to represent is sort of how does it think through a problem?

31:30How does it decide it's got the right answer? How does it check its work? And these models are getting much better at being able to deliver on that. So I think that'll be the trend for the next couple of years. And even for our own eval, I think we're looking at one of the earliest phases of a knowledge worker type eval. I think we're going to have to make it harder and harder to better represent the capabilities of these models soon. But yeah, these jumps are obviously, you know, very eye-opening. You know, we're going to get a little bit into how AI will do work in the second half when we come back.

32:05But one of the interesting things that's been happening around Claude is there's been this drama between Anthropic and the Pentagon about its use of Claude in this, like, the Pentagon's use of Claude. And there was this story that came out that apparently the Pentagon used Claude to coordinate its attack on Venezuela. This is from ex-user Tony Shevlin. Such a compliment to Claude that amid rumors it was used in a helicopter extraction of the Venezuelan president, nobody's even asking, wait, how can Claude help with that?

32:39People are like, of course, of course it was useful. How would you not have used Claude? It is actually a very funny, like two years ago, So that sentence would have been like, excuse me, what do you like? How would this have like, what would the thing have been? And now it's just like, yeah, I'm sure they use some kind of intelligence to to plan something or figure something out or, you know, correlate data. And that's just sort of priced into, I think, more and more complex work and and and software. Wild. OK, so we still have so much to talk about. We have open claw. We have these new studies on AI productivity.

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34:58It's time to turn those what-ifs into with Shopify today. Sign up for your$1 per month trial at shopify.com slash big tech. Go to shopify.com slash big tech. That's shopify.com slash big tech. And we're back here on Big Technology Podcast with Box CEO Aaron Levy. Aaron, it's always great to have you here. And I think you're really going to enjoy this next segment because this is something that you've been following very closely, and it's going to be great to get your perspective on it. When OpenClaw sold to OpenAI, I said, we've got to get Aaron on the show for his perspective on this. So this is from CNBC.

35:39OpenClaw creator Peter Steinberger joins OpenAI. The creator of the viral AI agent OpenClaw is joining OpenAI, and the service will live in a foundation as an open source project that OpenAI will continue to support, Sam Altman said. he said that Steinberger is going to join OpenAI to drive the next generation of personal agents. So we'd love to get your perspective here just on a little bit about very briefly what OpenClaw is, because it's always good to sort of refresh there. And then why is it significant that OpenAI either acquired it or brought Steinberger aboard? Yeah, so I think the innovation that that Steinberger kind of created with OpenClaw was, and there's been various attempts at this, you know, obviously over the past couple of years, but I think it was only really possible in probably the last couple of months of model capability.

36:34But the big jump is, you know, we have these agents that effectively act on behalf of us, and we are controlling it and steering it to go do tasks for us. So Claude Code, you kind of type in your terminal, you tell it to generate some code, and it goes off and does work and comes back, and it's waiting for its next task for you to give it. Or Codex, you're in a UI telling it to go and generate some code for you, Devon, Factory, all these kind of agents. And that's basically been the state of the art of agents for the past year or so, plus or minus. and OpenClaw kind of took, you know, many of the same principles, but said, well, what if that agent is sort of running on its own and it had access to your computer and your browser and all the services that you use and it's just literally running on an ongoing basis and you chat with it and you can ask it to do things, but it can also ping you as sort of relevant.

37:41And that was this, this is sort of a very new kind of way to think about agents that, again, we've seen examples of, but nothing obviously that has taken off at the at the level that OpenClaw did. And and it gives you a little bit of a peek into what the future could be, where you don't you don't have these agents that you only sort of spin up and spin down as you need them to do work for you. But you have actually an agent that's sort of always, always on kind of working, working for you and executing tasks for you. And that's why people are setting up, you know, their own separate computers for these agents.

38:15They can just keep running off in their own environment. And, and, you know, hard to know exactly how you fully would package that up and how it could manifest in a way that would be really, really simple for people to use and, and fully secure, fully safe and secure for people that don't kind of know their way around all these systems. um lots to figure out there but but not that different from you know what i when i think about it as like a you know a principle update or a paradigm update uh you know i remember the viral video of of of devin must be two years ago now and you know i don't remember exactly all the details if they if they did a slack message or if they were in the ui but you you kind of told devin to go off and do work and you could just see it it's producing its code it had another environment where you could see what, what it was building.

39:06And, you know, they got, they got, you know, I think there are a lot of people that were like, Oh, this will never work. How could this possibly work? It's not actually doing that. And there were these viral takedowns from non-believers and, but, but for, for, for some people who were deep in the AI space, we were like, Oh shoot. Like that is a very different way to think about, you know, working with an agent. You're not in an IDE, you're not coding alongside it. You're just setting off a task and it's going to go and do a bunch of work for you. And now, obviously, it's very clear that that's the dominant paradigm that we're going to be in.

39:39Codex has proven it. You know, Cloud Code has proven it. Devon and Factory have proven it. You know, I assume Cursor is betting even more on agents. You can kind of see them pushing more on the agent side of the user experience as opposed to the IDE side. So that was an update that we got a couple of years ago. And I think we're going to see the same thing now in other areas of knowledge work and, and open, and, and, you know, open claw introduces an interesting kind of paradigm that, that could, that, that could persist across, you know, more and more areas of work. Right. And now as a software CEO, I really would love to hear your perspective on what this means for software.

40:18I'll just give some context here. You know, I've spent the past, I guess, week and a half now, just like with my nose in cloud code, I've just been going crazy with it. And, you know, initially it was like, can you build me like a, basically a software version of a spreadsheet that like sends an email when I complete a field. But then it was like, well, why don't you plug that into YouTube's API? Why don't you plug that into, you know, I'm looking for an apartment. Can you plug into StreetEasy and Zillow? And all of a sudden it's like, oh, it goes from basically me going to the internet to the AI, you know, sorting through the internet for me.

40:55And you actually tweeted about this with the OpenClaw situation. You said, in a world of OpenClaw codecs, CloudCode, Cowork, Manus, which Meta acquired and other agentic systems, it's becoming clear that the future of software has to be API first, but also enable human interaction for verification, collaboration with agents and people and working on the output. So what does it mean for the software industry if it becomes API first? Because, you know, on one hand, you're, you're enabling your customers to get horrendous amount of utility. If they're interacting with you this way, on the other hand, you know, Zillow, um, probably got some value in me going there.

41:33YouTube probably wants me on YouTube. Now it's all happening in my, like, you know, my dashboards that I've built with cloud code. Yeah. So, uh, maybe we'll separate the markets a little bit because you, you threw in a lot of consumer products at the end of, of that um you know i uh hard to say how much how much of the consumer internet kind of gets collapsed into api calls versus versus you know the average consumer just still wants to go to youtube and see the feed and and they're not going to do for me youtube is that's strictly on like the back end so that's like the the creator side of youtube like i've used it to sort like uh thumbnails and then uh rank them by you know click through rate and then also tell us how how long people are staying on the videos, but point taken on the consumer side, you're not going to want to go to your Claude bot to watch YouTube probably.

42:22Yeah. And so, so that's why I kind of separate a little bit now, now I'm, but, but you have to be a little bit sympathetic or at least think through because, because again, uh, absolutely major consumer properties are going to see a reduction in traffic when the answer just comes up in chat to BT or when, you know, some kind of automated system is just delivering the answer. So, so I, I, I think that's a whole, whole category people have to think through. On the enterprise software side, that's obviously where we spend our time. I'll speak for Box for a second and then maybe you can broaden out for software.

42:53At Box, we're like 100 % excited about this because one of the things that agents are both really good at, but also need for their workflows are your files. They need to be able to access the information to work with to answer questions for you, to produce new information, to be able to store off memories and it's working and they're working sessions that you can go and interact with. They need to be able to read specifications and documentation. All of that ends up being files. So what we are building is a platform layer that whether you're a person interacting with your data, whether you're an application that needs to access data or whether you're an agent that needs a file system to interact with, we want to be the platform layer that connects all of that and uh the key why we we at at box we think we're in a a kind of unique position is we don't think it's enough for the agent just to have its own sort of sandbox environment of of of a file system uh nor is it it is it going to work for just people to have a separate environment you're going to need something that actually connects those two worlds together so that people are going to need some form of end user interface even if that's an end user interface in a chat bot, they're still gonna need to kind of, you know, interact with their data with something visual.

44:14And they'll likely eventually wanna like log into something and see all their content and be able to manage their sharing permissions and who they're working with. But agents just need a set of APIs and agents need to be able to work with those APIs and facilitate all of the work that they're doing. So what we're investing in is making sure we've got the most powerful capabilities for agents to be able to work with all of this content that you want to give it. Now, there's all these new implications, which is how do you give an agent a separate space to work in that you're collaborating with that agent, but its blast radius is somewhat contained, so it doesn't kind of delete all of your data.

44:52And now all of a sudden, you have this kind of crisis on your hands because your open claw agent went and mucked with everything. That just happened to Amazon, by the way. I mean, not to interrupt you, but Amazon, there was just this story in the FT that Amazon had lots of had outages because the agent was like, you know what I'm going to do to fix this problem? Just erase everything. I can make the problem go away. No more code. You didn't like your solution. You didn't like your folder structure. Great. Now there is none. So so you do have to you have to be thoughtful about about how do you kind of create the right, you know, lines of demarcation between these systems.

45:27But but again, for us, if you imagine that there's five or 10 or 100 times more agents in the future than people, which is, I think, a relatively safe assumption given the productivity increase that they're going to enable, all of those agents are going to work with enterprise information. They're going to need a secure space to work with that information. They're going to be able to store that data. They're going to be able to operate off of it. They're going to be able to answer questions for end users. They're going to be able to, you know, need to be able to store their own data. So that's what we're building.

45:53And we have to make sure, again, we make that as easy as possible for agents to go and utilize. I think that there's a meaningful amount of software that already exists that will also have to do the same thing. They will have to make their software ready for agents. I think there'll be some forms of software that get kind of compressed where agents don't really need to use their tools in the same way that people did. And that's obviously where you're going to see some pressure in the software market in some areas. And then there's going to be all new platforms that have to exist because we didn't anticipate the kind of new problems that agents are going to run into.

46:26And that's where you'll have, again, API-first companies get launched from the start thinking only in terms of platforms. And I think this is just going to be a tremendous amount of growth for anyone who at least has a play in that architecture. Okay, so you mentioned productivity. And I think this is something that's worth examining as we end the show because I think there is this sort of discussion around AI. oftentimes it's, well, there's productivity increases and it's sort of accepted like, you know, that's there already are, there will be, but the data is a little bit mixed. And I just want to run it by you and get your perspective on what the data is saying.

47:03So this is from Fortune. Thousands of CEOs just admitted AI had no impact on employment or productivity. And it has economists resurrecting a paradox from 40 years ago. So it talks a little bit about how In the 1960s, we had transistors, microprocessors, integrated circuits, and productivity growth actually ended up slowing from 2.9 % beforehand to 1.1 % in 1973. And so now you have all the CEOs that have been pulled, and it is, yes, 6 ,000 CEOs. two-thirds of the executives reported using AI, but it was 1.5 hours a week. 25 % of the respondents reported not using it in the workplace at all. Nearly 90 % of the firm said AI had no impact on employment or productivity over the last three years.

47:54I mean, maybe this is research done last year, but even still, you know, I'm curious. I'm curious, when was that published? Or when was the research taken? It is published February 2026. I don't know exactly when the research was conducted. Yeah. But with the number of respondents, obviously that would have been probably, you know, sometime last year. But sorry, keep going. No, go ahead. Oh. Like as in just like defend AI or what? I was just going to ask like what your perspective is here because it does seem like we're, you know, in some ways, and this is sort of, we want to pressure test a little bit about like some of these assumptions that we're going to have more AI agents.

48:35then we'll have workers, that it will lead to this increase in productivity, whereas we're still seeing data where that is at the sort of best when you look at this data up in the air. Yeah. Yeah. I can understand the dissonance that might be out there between the tech-enabled economy and the rest of the economy, because what's happening is in tech, these agents are are so effective at coding and and developers have have far fewer barriers to adopt agents for coding than the rest of the knowledge worker economy has for the same level of productivity gain kind of use cases. So in coding, you've got these just incredible properties, which is the models are hyper hyper trained on code.

49:26They, you know, coding itself is a text only medium. You know, Dario and Dwarkesh on their latest podcast kind of hinted at an interesting point, which is your code base contains most of the context that you end up working with. It's got your documentation. It's got your all of the existing work that you've done. And if you kind of compare and then you developers are just, you know, are obviously more technical, generally more tapped into the internet and what's going on and the latest trends. They pull down the latest new products and try them out. Now you can compare that to the rest of knowledge work.

50:03The marketer at a CPG company, the lawyer at a mid-sized law firm. I'm making up some kind of caricatures of various job functions. But basically, they're going about their day and they're not thinking like, how do I go and construct my workflow to, to just fully take advantage of agents and automate everything I'm doing? Like that, that's just like, probably not top of mind for, you know, most knowledge workers. They're going to go to chat to BT. They're going to ask some questions. They're going to get an email written for them. They're going to summarize a, you know, a document, they're going to build a new strategy plan.

50:43And then, you know, they're going to be, you know, the company will, will do incrementally a little bit more as a result of that. And, um, Maybe their strategy changes a little bit more or the financial analyst comes up with some new insights. That's, I think, probably been the state of AI for the past couple of years, at least whenever a survey like this would have tried to analyze. Compare that to engineering where, you know, we have products that we build five. You know, these are the estimates from the actual engineer that we will build five times faster because of AI coding. and we will, as a result of that, be able to ship significantly more capabilities to our customers.

51:23We will be able to solve significantly more problems for our customers. In many cases, we might not even charge more for that functionality. We are going to pack that into their existing licenses because we now can. So to some extent, what would you measure in our kind of productivity? This is now just a priced-in thing that we do because we have to deliver more and more value because obviously tech is hyper-competitive and we want to now add more capability to our customers. I think that has not yet rippled through the rest of knowledge work. And I think it just will. It will have to because the tools will get better and better and you'll have one competitor in a market that is able to use AI to either lower their costs or lower their fees to the customer or be able to deliver a substantially higher product to the customer.

52:13And as you see more and more examples of that, that will just start to transform these market dynamics. You know, I would say equally that, you know, I like to operate off of, you know, I think Bezos had this line is when the anecdotes and the data disagree, you have to look at the anecdotes. And so, you know, look at the, you know, the equal headline from two weeks ago of KPMG asking their auditor to lower their fees because of AI. That I think is your, that's your initial signal of, of actually what's going to happen, which is a company is going to say, you know, that kind of work that, that, that we now know we can, we can bring automation to, we should be spending less on and then using those dollars to do something else in our company that is, that is higher productivity or more or that makes us more effective or more competitive.

53:08And once you do that dozens or hundreds or thousands or tens of thousands of times in an ecosystem, that's where you'll start to see kind of this reshaping of how these markets will play out. It's happening in tech unquestionably. And now the only thing is what's the roadmap to that happening across the rest of the economy? That's going to take time. People have to change their workflows. People don't have data set up in a way that is sort of prepared for agents. The agents themselves don't always have the right interfaces or tooling to be supported in knowledge work. So I'm actually extremely pragmatic about this, where I think I could agree with the survey that you just read and equally be completely unfazed and more of anything just say people should be probably prepared for this will come from more areas of knowledge work.

53:54I'm the biggest optimist on the jobs impact of that, so I don't see that as a scary thing. I think it's just going to mean companies will have to sign up to do way more for their customers. I think that that will be where it shows up is we will have a surplus on the consumer side of all of the vendors that we work with. We'll just have to deliver better and better services for us. Or if you're a B2B company, then all of your vendors will have to deliver greater services. And we will wake up in five or ten years and it'll actually kind of feel like relatively normal. Like there's not going to be some kind of crazy, it's not going to be the sci-fi movie.

54:30It's going to be that that that we just we just have incrementally better consumer experiences and better services, just as if you went back, you know, 40 years ago and tried to imagine life of of a lawyer or a health care professional. And you'd be like, wow, how did you do your job like without a computer? Like, how did you like how did you understand the legal case precedence without an Internet search that you could go do? That's going to be work in five years from now is you'll be like, how did you do that without an agent that drafted your entire contract for you instantly so you could respond to the client that was on the phone?

55:08We will have that same set of questions and be confused how we even work the way we do today. But yet it won't be some kind of completely transformation of we'll stop people. They'll be working together. They'll deploy tasks to agents. Those agents will go off and do work. And then people will go and bring it back to the task at hand to move whatever their sort of work or project is forward. That's right. Yeah. When I'm watching Cloud Code Go, I look at it and I say, wait, people did this before? That seems like a lot of time to do things that are automatable. No, but literally, you used to have to spend like two weeks on like a library change that you wanted to make in your code base.

55:51And that's now a 10-minute activity. and but but are we spending any less time building software no it's because we're just now doing the things that we didn't get to because we were spending the two weeks doing the library update right okay aaron we have to get you out of here because you have to go to your your next meeting i think but uh just want to say thank you again great always great having you on the show uh next wednesday we're gonna have michael paulin on he is the author of a new book about consciousness so we'll talk about ai consciousness all right everybody stay tuned for that and we'll see you next time on Big Technology Podcast.

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