Transcript
A (0:00)
Many organizations use multiple AI tools from multiple vendors across multiple departments. At the break, join Steve Soder, Vice President and Industry Principal at workiva, to learn how audit and governance teams should approach this fragmented landscape.
B (0:19)
Welcome to Tech News briefing. It's Tuesday, February 24th. I'm Katie Dayton for the Wall Street Journal. The age of growing headcount is over. And at least in the world of AI startups, small companies are doing all they can to remain that way, whilst growing revenue. As part of a bid to showcase efficiency to investors, we take a look at how the trend is reshaping the tech industry. Then we're going on a tour of America's newest tech factories. After years of political promises and encouragement from the government, more chip makers and other manufacturing companies are breaking ground on US plants and gearing up to hire American workers. But can these facilities really compete with their counterparts in Asia? Stay with us to find out. But first, once upon a time, a growing headcount at a new company was seen as a positive sign. Now, in an age of AI outsourcing, not so much. Some Silicon Valley startups are running leaner than ever, using the latest AI tools to keep staff numbers as low as possible. My colleague Belin is here to talk about this new flex. So, Bel, generally speaking, where are these companies finding that AI works best within the workforce? Are there particular jobs or even functions that you've heard these AI companies cutting out and replacing with technology?
C (1:41)
In most cases, it's the software engineering function. So these software developers that use tools like anthropics, cloud code or OpenAI's codecs, which are really sort of supercharging the way in which they write code and many times replacing the act of writing code at all. And so what they're doing is just reviewing the code or looking at the code that's being written by the AI. And that's the kind of pattern that's seen across many companies, not just startups in Silicon Valley.
B (2:08)
And how lean is lean? Like, what kind of headcount versus revenue range are we talking about here?
C (2:14)
You can look at the definition as a startup that has, has maybe less than 100 employees and is tracking revenue per employee. So they're looking at efficiency as one of the most important metrics very early on, and that's more important to them in some cases than growth. Because the old way of looking at things in Silicon Valley was that you had these companies that were just trying to grow as quickly as possible, these startups that considered it a badge of honor to have a lot of employees, and that was something you touted in a press release. But nowadays it's really about staying small and lean and very mean.
