Indeed, the funding news follows a stretch of breakneck revenue growth as shared by Sierra, which first said it hit $100 million in annual recurring revenue in late November, then published another post in early February, saying it had hit $150 million in ARR.

That pacing reflects both the urgency enterprises feel about deploying AI and the costs that come with it. Taylor, who also serves as chairman of OpenAI and was formerly co-CEO of Salesforce, has said that the best-case outcome for agentic AI is lower costs and higher revenue for clients, but before those returns materialize, the ramp-up phase can be pricey.

That exact scenario showed up in a conversation at one of TechCrunch’s StrictlyVC events last week. Uber CTO Praveen Neppalli Naga put it plainly in conversation with this editor, saying that Uber “blew through our [AI] budget” soon after opening the door to agentic AI tools late last year. He also said the company is starting to see meaningful results.

Across a staff of roughly 8,000 engineers and technical workers, about 10% of all code being produced at the company is now generated autonomously, he said, adding that “10% at our scale is huge.” As a proof-of-concept, Uber tasked one team with building a new hotel-booking integration using only agentic workflows. Work that would normally take a year was done in six months, he said.