So Uber gave 5,000 engineers.

So Uber gave 5,000 engineers access to cloud code in December.

By February, usage had nearly doubled.

By April, the CTO told the company they burned through the entire annual AI budget.

So the adoption curve tells you everything about what happened.

In December 2024, 32% of Uber's engineers were using cloud code.

By February 2026, that number was 63%.

That seems a little slow to me.

But anyway, that's not a gradual rollout. That's a product so useful that engineers pull it into the workflow faster than finance could model the spent. Okay, that's a lot of employees, though. Uber has about 34,000 employees, engineering is roughly 15% of that. Okay. So all this to say, Neil, is this CTO, if I go back over here, so look, AI-related costs at Uber are up 6X since 2024. This is what we're talking about. And we're seeing this in our organization, yours too. CTO Praveen Nepali Nagas quote was, I'm back to the drawing board. That's the CTO of a $144 billion company admitting that the tools work so well that his team can't afford to keep using them at this rate. So here's the thing. So he has to go back to his CFO and ask for a larger budget now. But to Neil's point, if this is working for you so well, you should be spending more. And here's the other thing. You might be thinking, oh, I can put this all on, you know, open source tokens. But if you're actively building things and shipping code, you can't put on an open source tokens because you might need to rework it a couple of times. And the time you spent there is not worth it. You like, chances are if you're shipping a lot of this stuff, a lot of it's going to have to be on frontier models. So. And there's an important thing here. They roll this out in December and by February

they had good adoption by April. They went through all their tokens. I bet you there's a lot of terrible

usage of Claude Code within this organization. I don't mean in a bad way. It's actually in almost

all organizations where they're doing a lot of things inefficiently and they're not optimizing for cost savings, that'll start coming out soon where companies start thinking about it.

And then his budget from April will last the whole year and he won't need to go back to the

CFO.

We'll see.

I mean, so it says the CFO problem here is now the bottleneck of AI adoption at enterprise level.

The technology works, productivity gains are real.

Uber's own data says 75% of code review comments are marked helpful by engineers.

Okay, there's your thing, Neal.

75% are helpful.

The constraint is that the traditional annual budgeting was designed for tools with predictable

per seat costs and AI coding agents have usage curves that

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