The Ledger, every show

“There's an open source ecosystem in, in China that is near neck and neck. Let's say at least still maybe kind of, you know, one to three months behind, but not a year or two years behind.”

“The funniest concept that the more code we write, the less we would need engineers would be the opposite because now your systems are even more complex than before, which means that you're going to be running into even more challenges of when you need to do a …”

“There are going to be more lawyers in the next five years than we have today.”

“We will.”

“We've talked to customers where where they have had, had colleagues that, that can't actually they can't present the actual ROI savings to their board. The actual kind of expected ROI savings to the board because the board won't believe how, how they won't bel…”

“And I think what you're seeing with scaling is we will be able to certainly accomplish our collective definition of super intelligence. With the current, ah, the current path we're on with scaling laws.”

“It's going to change the nature of the incoming class of engineers that you hire. Like they will literally not be able to code without AI assistant, assisting them.”

“If as of, you know, Tuesday afternoon, you know, the tariffs that have been proposed, if those roll through you know, this is going to be a total disaster.”

“Now it doesn't mean that it's all startups. It's going to be Salesforce and it's going to be service. Now it's going to be Oracle. And it's gonna be box.net which is not our official brand. We, you know, we will capture collectively all of that.”

“I just don't agree with the TAM compression because I think there's another kind of counter event that's happening that, that AI is, is really going after like services. And so that then conversely expands the TAM software where IT budgets weren't usually appl…”

“That is as much going to be an incumbent's game as a startup's game this time around.”

“There's a lot of belief that like, oh, well, well, you might have these solo companies that, you know, become multi-billion dollar companies with just one person or, you know, three people and a bunch of AI. I think that will be done, you know, just by virtue …”

“Obviously you have companies going from zero to a hundred million or five hundred million in revenue in, you know, one to two years. Like this has never happened before in software. Or kind of technology broadly.”

“And the enterprise actually right now we're like nowhere near the level of intelligence needed for the vast majority of enterprise tasks.”

“And the only kind of caveat is, like, that's going to probably take, like, 10 to 20 years. Not just because of model progress, but because of the rollout of all this.”

“I think it's going to become the number one topic in the next presidential election.”

“And this is like classic Jevons paradox, which is we lowered the cost of engineering, which means that everybody wants to do more of it, and now finally people can. And so you're gonna see this huge surplus in, in demand For engineers across the economy in ind…”

“There's this layer that's sort of needed between the model's capabilities and the ultimate customer's workflow, and that's kind of this bridge layer. And that's where effectively, you know, probably trillions of dollars of market cap will eventually emerge.”

“This amazing progress that will totally add 10 or 15 or 20 years to people's lives over the next 50 years and absolutely kind of impact preventable, you know, diseases from people.”

“I think practically in the next three to five years, we probably have to end up in an environment where models do get evaluated by the government. There is a sort of collaborative approach between the government and research and the labs. You know, the governm…”

“I think the tone is actually remarkably optimistic and excited and positive as opposed to, you know, there's a sort of, You know, typical trough of disillusionment, you know, from Gartner and the hype cycle or whatnot.”

“One, you know, coding agent could be consuming, you know, a thousand dollars of compute on a single task. So clearly like you can't lump that all into a 20 dollar per user per month fee.”

“The data center providers, the labs, et cetera, have pricing power. They don't need to lower their prices on anything. So you're not seeing the typical things that drive down the cost of compute. I'm highly optimistic that that happens over the next five to 10…”

“You're going to need, you know, new, new pieces of software. Probably there's probably a, you know, a five billion dollar startup waiting to happen just in like ERP for your AI compute.”

“I think what's going to happen is you're going to have a mosaic of models in the enterprise. I think the average enterprise will certainly be using, you know, half a dozen models in their organization.”

“So I think it's just going to be this sort of dual, dual model with the one nuance being probably by like you know, database queries, headless will just be a hundred times larger than the interface driven, you know, way of doing work.”

“So I think any enterprise software company in three years from now, that sort of, that, that gets through this AI transformation period, It will have a seat business model, assuming it has an end user component, and it'll have a consumption business model.”

“You will actually see, interestingly, if you're like an executive and you start to do this, you'll see lots of areas actually where you should hire more people because you're like, oh my God, this thing is spitting out, you know, incredible goldmine of value, …”

“So, so that, and that's going to be, there's going to be businesses that are doing that for decades. Like it's going to be an incredible opportunity for this kind of next generation set of firms, as well as existing ones that, that lean into that.”

“Where again, you were normally constrained by the number of people on these platforms, but now the headless user can be, you know, a hundred or a thousand X the scale of those human users.”

“I don't think that it's a five to 10 X gain. I do think it's a two to three X gain, maybe across the board. You are still rate limited by how quickly can you review this stuff and check on the work.”

“Maybe if you're graduating, you know, name your computer science school today, you don't go immediately to Google. You go to literally John Deere or Caterpillar or Eli Lilly, but the skills that you have are going to be just as relevant in just a different dom…”

“I'm not a hundred percent clear on that, but there is a hundred percent a role right now that there's going to be 500,000, a million jobs created for, and it's basically some kind of agent operator.”

“And I don't think it like, You know, 10 X's the size of IT spend or technology spend globally, but it certainly doubles it.”

“And then the only part why, why 18 months is like not even a relevant window to me is I think diffusion is going to take longer than Silicon Valley thinks.”

“That is like what I just described right now is 10 years of work for Accenture in every enterprise on the planet or the next gen Accenture that does this in particular industries or workflows.”

“I promise you, you're not going to be able to blame Anthropic when something goes wrong. And so if you can't blame Anthropic when something goes wrong, then at some point it doesn't really work to tell the company, like to tell your customer, well, That, that …”

“The labs are not going to, you know, take on the liability for every single use case that you do. They're gonna have very narrow liability that they have around copyright and IP protection and stuff like that, but they're not gonna, you know, they're not gonna…”

“The good news is there's going to be value in, in both sides, because even the vertical domain specific players will be riding on top of the intelligence from the horizontal labs. And so in both, in all the scenarios, the labs win, you know, a very big prize l…”

“I think there'll be hundreds of successful, thousands of successful products at that layer, simply because again, enterprises, they just want to, they want to wake up. They want to get their job done. They want to have some alpha relative to competitors. And t…”

“The diffusion of AI capability is going to take longer than people in Silicon Valley realize.”

“I do think that will be relatively disruptive You know, for some time until the bigger incumbents can kind of, you know, get out of the way on this. And that will at least create, you know, some precedent or case studies of what this new sort of corporation co…”

“You can just see how the AI tsunami could wipe you out. If you make just two, three, four or five wrong decisions in this space, like couple wrong architecture decisions, couple wrong AI feature decisions, couple wrong API platform decisions. And you might be …”

“The thing that's going to happen on the ledger of software is we're going to produce far more output of code and thus features per dollar. But on the other end of this, we're going to actually end up spending probably just as much on how do you get all of that…”

“But no matter what, there's going to be 10 to a hundred times more code. So I think you can be very long engineering right now as just a, you know, purely on the dimension of software is going to become increasingly more important. Once agents are, you know, t…”

“We're talking about a category where, you know, it'll be measured in the tens of trillions of dollars. The market caps that will be generated by AI. Some of that will go to the chip providers. Some of that will go to the supply chain of the chip providers. Som…”

“There's five or 10 or a hundred 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.”

“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.”