No Priors: Artificial Intelligence | Technology | Startups
00:07:46 · Satya Nadella
[00:07:46] S0: Yeah. I think yeah. To your point, obviously, coding is now got But it's interesting, by the way, Ladish, to even talk about the coding, right? Which is coding has worked so well that we now have to rebuild the IDE, right? I mean, it's kind of nuts to see what we launched. It's like, oh my god, I have these 100 agent sessions. Cognitive load, it transfers back to me as a human is so excessive that now I need a new UI. Oh, by the way, the chat as the only artifact is also impossible. So, that's why we need a canvas. So, it's kind of interesting for all the things about where is software needed or where is UI needed. You kind of need that even for code, right, in a fully agentic world. But that said, one of the things that we are starting to see, we start seeing that co work, but even some of the work we showed with Autopilot, right on what you see with Claws, is a good one. Because if you sort of think about a lot of human capital is doing the glue work, right, if you now can augment that with tokensagents that are long running, durable, right, then your ability to scale, even what is still judgment and glue work, gets amplified like coding does. So you can I'm positive that six months from now, we'll all be saying, oh, wow. Like all through the night, there was a bunch of stuff that all these autopilots that I have working on my behalf with my delegated authority, so to speak. Right? I can sort of, given even my identity, did a bunch of work. Then, of course, I'll need my new ADE to say, what did you do? Like, did I do this work? And so on. So I think that that's where compressing of workflows, completing of tasks, that's where I think a lot of the value gets created.
00:09:38 · Elad Gil
[00:09:38] S3: I think you raised a really interesting point, which is there's the actual agent that's doing the code, then there's a harness around it. And that's the environment, that's the context, that's everything you're setting up as a developer around actually a coding agent. What is the harness for the enterprise? Is there an equivalent concept for broader productivity work, or how do you think about that concept sort of generalized?
00:09:56 · Satya Nadella
[00:09:56] S0: That's right. So, in some sense, you kind of want the harness to define the models, data, and the tools, and so that you have a loop across those three. And so, what we are trying to, first of all, make sure is each of our products that we build, right, whether it's GitHub Copilot or the security copilot, the stuff we showed with Emdash, or even the discovery for science, it doesn't matter. All of them are multimodal harnesses with tools access so that you can do this progressive disclosure of tools even so that they're token efficient. And then you're feeding it with very rich context. Because that's sort of the other hard lesson we have learned in the last two years is, oh my God, the amount of work you need to do to prep the context layer such that your plan can execute in the most efficient way is where the magic is. So we have, in our case, we have the GitHub harness, which essentially we're using across all our products. It's available in Foundry. And we're open, like you can use your Lama harness, whatever, or you can use any open harness or any harness of yours and train with your tools and multiple models and your context. And so that's the pitch. Because right now, a lot of dialogue is, hey, if I train the harness plus tools and the model together, you get evals. And what we are proving out is, and the best example of that, is what we did with Emdash, right? Because when it launched, it found bugs or vulnerabilities that were not found by mythos. And so there is existence proof, I would claim, that you can have a multimodal harness that can, in fact, be more performant in the real world.
00:11:48 · Sarah Guo
[00:11:48] S1: So premise behind the training at the independent Frontier Labs is really, you know, we're gonna have these models, We'll have an API business and we'll support enterprises and startups, but a first party product, be it productivity or code or search drives the majority of revenue. That's a different value equation than you're describing, I think, with the Microsoft ecosystem. If if that's the case, tell me if it's the case, because obviously you have first party products and you have enablement products. What is the role of the develop like, what's gonna be hard and the set of skills and the value capture the developer has in that world?
00:12:23 · Satya Nadella
[00:12:23] S0: Yeah. So I think that there's always gonna be the case that someone who is super successful as a platform builder can also have first party products. It was true with Windows. It was true with the SaaS side and the cloud side as well with us and others and so on. But the thing that is, is it should not be a limiter to other people achieving that same success, Right? That, I think, is the core difference, which is the network effects this time around, around intelligence are such because they learn from data and not really lots of data. It's just a few samples that you have to see to understand what's novel about something. So that's why the game becomes how to protect. So that's why I would say every company having private evals may be the biggest IP. Right? I think about it. Like, what's that private eval that you can then use even a frontier model to hill climb on and not leak the traces? Maybe one of the biggest drivers of IP. Like so in other words, another asset test is you have an eval that's private. You're using model A. Can you switch it to model B and, know, climb up? If you can, then you're in control. If you can't, you're not in control. And that's where even the harness decision becomes super important. Right? So therefore, having an open harness, letting all models come in, having your evals, your context, your tools help you hill climb, I think, is the skills that an AI native startup needs, a SaaS company needs, or every enterprise needs.
00:14:07 · swyx, Satya Nadella
[00:14:07] S2: Yeah. I think in a very real way, you are Microsoft historically, as an operating systems company and then become a cloud company, maybe, like, the third act is that you're a harness or eval's company, whatever whatever the the sort of conglomerate of concepts that you wanna put together. And I think, like, enabling every company to have, like, frontier intelligence or what what I forget the the exact term that you use is the is the mission. Right? [00:14:32] S0: That's it. [00:14:33] S2: That is that is the platform promise that you build with us. You will get your intelligence for your data.