Sundar Pichai: evaluation

Transcript context

…Can I add a few problems I see when it comes to actual diffusion of AI in industry? I'm curious how and when you think we'll solve them. Because as I see it, we have a big intelligence overhang. The AIs are now amazing in terms of what they can do in the abstract. If you look at how AI-native a company is or just how much it uses that intelligence, there'll probably be a shortfall. The problems that I see are something like, one: it actually takes a while to get good as an engineer at prompting your AI well. You can prompt AI better or worse to write code. Then there's a lot of, say, Stripe-specific prompting in our case to know which tools to use. There's the general being good at prompting, and then there's the Stripe being good at prompting. Then, of course, you have the fact that it's hard to share an AI-generated code base because you have a blast radius, and you're just changing so much and the turnover of the code is high enough where maybe you're rewriting it several times before you ship, that it's hard for many people to collaborate on the code base versus before when the code velocity was slower. Then as you go outside of engineering, the big one I see is access to data where you'd like to have your agent go, "How many times a day do people at companies around the world say, 'Hey, what's the status of this deal?'" That is like information that the company knows and should be agentically answerable. We actually have some cool stuff at Stripe where I was seeing where you can actually answer that pretty well. But with both habits and access to data, and as you get into a bigger company, the permissions engine of who can actually get access to this data, that all needs to be rewritten. Then you get into role definition where, like you were saying, Eng, PM, design stems a little bit from a prior year. You may want to, at least in some cases, merge those roles a little bit as AI gets better at all those since you've got a product... Anyway, that's my characterization of—in 2026—the models are capable of this, but we're only using them so much. What do you think that adoption of the intelligence looks like? Look, a lot of us are working on literally what the Gemini team... The Gemini enterprise teams and the Antigravity teams, they're all precisely working on these problems. This is the roadmap you're talking about, right? That's literally we are using it internally, running into these barriers, working past it. That's the products that are shipping. We are still diffusing it because what you do is people, as part of using it, like if you're the SRE team at Google, you suddenly find portions which you can create an automated workflow. That's happening in these spots. But doing it more systematically when you develop skills, how does it get centralized? How is it available to the models and for everyone to use? Identity access controls are real hard problems, and so we are working through those things. But those are the key things which are limiting diffusion to us, too. We take security a lot more seriously, and so we have to. That is another layer on top of all these things, the cost of mistakes when you're running these services, we have to work through it. But I think because of it, when we solve it, I think we will bring it in a more robust way, which will help. I feel like we're going through that fixed cost right now, but you will see this jump of what people are able to do when we bring it outside, and others are doing it, too. In a more robust way, the models are improving. Google re-forecasts its business a few times a year, formally, I presume. At least we do at Stripe where we set a budget for the year, and then three times a year, we produce a formal re-forecast. When you think about it, a re-forecast is a moment in time function where you take the state of the business, some of which is in people's heads, but most of which is written down everywhere where it's like, "How is this product doing? How is that product doing? Will this deal close? Will that happen?" Whatever. There's the moment in time state of the business, we put it into a function and out comes the updated numbers for the year. You can imagine an AI doing a fully, no human in the loop, forecast? What quarter do you think Google's first fully agentic forecast is?…

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