Everything Benedict Evans said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Evans: AI Model Makers Lack Value Capture Due to Identical Technologies
“Because right now there isn't a path to value capture because right now you've got a lot of people doing basically the same thing with basically the same technology and the same data and the same chips.”
Evans: OpenAI's new ChatGPT work product is a confusing disaster
“I was playing with a new chat GPT work product, which is clearly not that it's a complete disaster. It's chaotic, confusing mess”
Evans: LLMs lack broad product-market fit beyond software developers
“The LLM itself Is not a great product for most people. Usage is a mile wide and an inch deep, and you have this kind of polarization between people where this really, really works, and they really, really have product market fit, which is basically software de…”
Evans: Model makers will lose pricing power within five years
“And the paradox is like right now they can name their price, but that isn't where we're going to be in five years. You can argue about how quickly the infrastructure gets built out and how fast the GPUs arrive, blah, blah, blah, blah. Fine. But that's a supply…”
Evans: Tech industry cannot spend $10 trillion annually on AI infrastructure
“We can't spend 10 trillion dollars a year on our AI infrastructure, because there isn't 10 trillion dollars a year there to spend on it.”
Evans: Chatbots and foundation models are not standalone products
“I don't think foundation models. A product. I don't think a chatbot is a product. I think the value will be further up.”
Evans: Current generative AI technology cannot drive daily consumer usage
“We don't see a way that consumers will use this daily rather than weekly with the technology we have right now.”
Evans: Tech industry will spend $1T to $2T on AI CapEx
“Over the next couple of years, we've got like a trillion or two trillion dollars of capex coming down the pipe, and the models get a hundred x, 200 x, if it's more efficient every year.”
Evans: Infrastructure providers historically fail to capture value compared to OS
“Chip companies didn't capture the value. ISPs didn't capture the value. Mobile network operators didn't capture the value. Windows and iOS did, but they were doing something else.”
Evans: Foundation AI models are commodities and low-level infrastructure
“The models are kind of diff commodities, and the chatbot isn't the right UI or the right product, and the companies aren't going to be able to build all of that stuff themselves, so therefore they're low-level infrastructure.”
Evans: Only 3 to 6 companies will build frontier AI models
“You're going to have, pick a number, three to six companies making a frontier model. Spending, no one knows, no one honest knows, like something between two hundred billion dollars and two trillion dollars a year on building these models.”
Evans: Coding is the only AI use case with clear product-market fit
“The place that's got product market fit right now is coding. Nothing else has equivalent product market fit right now.”
Evans: AI will drive 10x to 100x increase in total software creation
“What does this do to software, and the answer is, more software, like, way more software. I mean, all software companies exist to solve problems created by other software companies, and that was the joke in security, like, All security software exists to solve…”
Evans: Enterprise AI productivity gains will be competed away
“These things become competitive necessities, and everybody has to buy it and use it. But the cost saving or the productivity gain that you get from it just kind of gets competed away, so you don't get to charge more for it.”
Evans: AI foundation models will likely become commodity infrastructure
“Are the model companies going to have come some kind of, you know, oligopolistic power over the tech industry, or is this going to be commodity infrastructure with,
The value being somewhere else to which I think the answer is it's commodity infrastructure, bu…”
Evans: Chatbots are a terrible user interface for AI
“I feel like chatbots are terrible interface and users need product and interface and tooling and company and go to market around that.
And so that we all have thousands of companies that go out and build that.”
Evans: External customers will spend $100B–$150B on AI coding this year
“This year, people outside of those labs will spend, clearly will spend something in the order of hundred, hundred and fifty billion dollars to use AI coding. Just to use AI coding. And that's not AI people spending money from NVIDIA. That's real money. And tha…”
Evans: Only idiots believe people will use vibe coding to rebuild Stripe
“Like, no, people are not going to vibe code to their own stripe, but that's kind of a straw man. Like it's, I'd say it's a straw man, except there are people who say this, but only idiots.”
Evans: Picking AI winners today is like predicting Excite versus Yahoo
“And so then you can kind of get into calling those races where, again, it's like being in 1997 and saying, well, is it going to be Excite or Yahoo? And the answer was no, generally.”
Evans: Enterprise AI software replacement will take three to ten years
“So I know people aren't going to tear out SAP and replace it with X, Y, Z. Maybe in five, in like three, five, 10 years, yes, that whole estate will look radically different. And all those jobs will have changed, but it will take, you know, two, three, four, f…”
Evans: AI will transform the world even if models stop improving today
“Even if like the model stopped, you're getting better tomorrow. If this is it, and we hit a brick wall tomorrow, this is an incredibly useful technology that's going to change the world and get rolled out over the next 10 years.”
Evans: Distribution and brand matter most when AI models are commodities
“So distribution of an adequate product when the field is basically commodity distribution on brand become a big deal.”
Evans: Scoring precise percentages of job automation from AI is deluded
“I was looking at this as whole, there's a sort of US government called own data set called own natural or something like that, which tries to kind of analyze every single job and then people try and kind of score it and they try and say, well, you know, this p…”
Evans: A software company's moat is go-to-market, not writing code
“I don't feel like the reason it's hard to compete with X or Y or Z company is how long it would take you to write the code to replicate the product. It's almost never the problem. It's the problem. The hard part is everything else. It's working out what the pr…”