# The Neo Show: Special Edition #3 - Marc Benioff with Dario Amodei *Norton Neo* · https://www.youtube.com/watch?v=TEDwEirZTOU ## Summary In this short conversation, Marc Benioff interviews Dario Amodei about AI writing code at Anthropic. Amodei says that on many teams roughly 90% of code is now written by Claude, with humans editing and supervising, and gives an example of Claude finding an obscure cluster bug. He argues this does not mean firing engineers, because comparative advantage means engineers become more leveraged and productive. ## Key points - Dario Amodei says Anthropic releases a smarter model roughly every 3 months, and models are slowly getting better than most humans at most things. - The model is not building itself; there are no self-replicating robots, but Claude is used to build products, train the next Claude, and serve Claude faster. - Amodei predicted six months ago that in six months 90% of code would be written by AI models, and says this is now true within Anthropic and at a number of companies they work with. - On many teams at Anthropic, about 90% of code is written by Claude, with humans in an editing and supervisory role. - Claude found a super obscure bug in a broken training cluster that engineers had spent days on and missed. - Amodei says 90% AI-written code does not mean firing 90% of software engineers; under comparative advantage you may need just as many or more engineers. - Engineers can be 10 times more productive by focusing on the hardest 10% of code and supervising AI models. - Amodei characterizes this as a rebalancing of work, not a replacement. ## Notes ### AI Progress at Anthropic - Dario Amodei notes that every 3 months Anthropic makes a model smarter than the previous one, and models are slowly getting better than most humans at most things. - The model is not building itself — there are no self-replicating nanobots or robots — but Anthropic uses Claude to build products on top of Claude, train the next Claude, and serve Claude faster. ### The 90% Code Prediction - Six months earlier, Amodei predicted that in six months 90% of code would be written by AI models. - Some people think the prediction is wrong, but he says it is absolutely true within Anthropic and at a number of companies they work with. - On many teams (not uniformly everywhere) at Anthropic, 90% of code is written by the model today. ### How Humans Work With Claude - Teams play an editing and supervisory role: you can ask Claude to write a feature, then a human reviews the code or asks another copy of Claude for help. - Example: while training the most recently released Claude, the cluster was broken due to a long-running bug. Engineers spent a few days on it, but when they asked Claude to play around with the cluster, it found a super obscure bug the engineers had missed. - Amodei describes this as Claude being like a very talented teammate. ### Does This Mean Fewer Engineers? - Marc Benioff presses on whether 90% AI-written code means fewer engineers, and when it will be 95% or 99%, also referencing Amodei's aggressive comments about firing executives. - Amodei says people can misinterpret this as firing 90% of software engineers. - Under the principle of comparative advantage, you usually need just as many engineers, possibly more, because they are more leveraged. - Engineers focus on the hardest 10% of code, editing, or supervising a group of AI models, and can end up 10 times more productive. - Amodei concludes it is a rebalancing of the work, not a replacement. ## Transcript [00:00] One thing that's real is that, you know, every 3 months we make a model that's smarter than the month than the model we made before. And indeed, the models are slowly getting to where they're, you know, better than most humans at most things. Maybe at some point better all humans at than all things. The other thing I think is real is, you know, the model is not building itself in the sense that like I have a specific copy of the model that's like making a specific copy of the the, you know, the the next model. you know, we don't have our self-replicating, you know, nanobots or robots or or whatever, but but what absolutely is happening is that within Anthropic and elsewhere, we are using Claude to help build products on top of [00:40] Claude and to help train the next Claude to help serve Claude faster. Um, you know, six months ago, I I made this prediction that, you know, in in six months, 90% of code would be written by by by AI models. Some people think that prediction is wrong but within Anthropic and within a number of companies that we work with that is absolutely true. Um now 90 you know >> so you're saying that 90% of all code at anthropics being written by the by the model today >> on on many teams you know not uniformly every >> is that something that you've kind of provided something kind of >> something auditable around that or like shown how that's happened. Yeah, the teams play an editing and supervisory role, but you know, Claude can both you [01:23] can say write this feature and claude will do it and then the human kind of looks over the code or asks for help from another another model, another copy of Claude. Um uh the other thing is sometimes we have these long running bugs. You know, when we were training our our the most recently released Claude, it was like, you know, the cluster was broken. There was this bug. Engineers were spending a few days on it. And, you know, we just we just went to Claude and we said, I don't know, just kind of play around with the cluster and see if you can figure out what's wrong. And, you know, Claude found this just super obscure bug that the engineers had missed. So, this this was one area where it was like Claude is [01:59] like having a very talented teammate. So if claude is now running writing 90% of all of the code in enthropic do you need less engineers if 90% of all the code when will it be 95% or 99%. >> Yeah. So you know I I you know I think people can misinterpret it as you know you know like Claude writing 90% of the code means we're firing 90% of the software engineers. But you know if you're familiar with the principle of >> well you have made some very aggressive comments around firing executives >> that that so um >> I just want to put two and two together to get four. Okay. >> Um uh so uh um you know if >> one thing I've learned in knowing you for so long is I have to come back and kind of like get that qualifying [02:45] question again. Yes. Because you're go you know you you're you're going fast. So trying to I'm trying to keep up with you and it's amazing but I want to just make sure I understand exactly what you're saying. >> Yes, absolutely. Let me let me let me take them one by one. So um uh you know under comparative advantage if Claude is writing 90% of the code what that means usually is you need just as many software engineers you might need more because they can they can then be more leveraged. they can focus on the 10% that's editing the code or writing the 10% that's the hardest or supervising a group of a of AI models. And so what happens is, you know, you can just end up being 10 times more productive [03:28] because the remaining 10% is is now a complement to the to the AI system that's that's getting much better at at getting much better at what it's producing. So So >> it's a rebalancing of the work is what you're really saying. >> It's it's not a replacement. It's on a replacement.