When Your Life’s Work Becomes Free and Abundant

Reflections on how tools like Claude are reshaping engineering.

Not long ago, I spent a weekend writing code with Claude, Anthropic’s AI assistant. I’ve been programming for more than 20 years. I was one of the first engineers at Facebook, where I built the original search engine. I went on to become chief technology officer of Dropbox, where I scaled the engineering team from 25 people to a thousand. Code has been the foundation of my career, the craft I’ve spent my adult life mastering. And after that weekend, one thing was very clear to me: We will never write code by hand again. Something I was very good at is now free and abundant.

While I was building software with AI, I also noticed that the AI agents elsewhere were building social networks, the very product I helped create at Facebook. Little coding agents were spinning up functional social platforms for themselves. It’s all a bit silly, but what they produce is kind of indistinguishable from what humans built on the larger internet. Both the form and the function of my early career are now being produced by machines.

I sat with that for a while, and what I felt was wonder mixed with a profound sadness. There’s something deeply disorienting about watching the pillars of your professional identity, what you built and how you built it, get reproduced in a weekend by a tool that doesn’t need to eat or sleep.

But here’s the thing about disorientation: It passes. And what replaced my sadness was something I didn’t expect: a kind of wild, almost reckless energy.

In the five days after that weekend, I produced more code than I had in the previous five years. That is not an exaggeration. The software I was making was better than the code I had produced on my own in the past, and far more ambitious. Things I would never have attempted before, because the cost of building them would have been too high, suddenly became possible in an afternoon. I wasn’t watching myself become obsolete. I was watching the constraints I’d accepted my whole career dissolve.

That shift, from sadness to mastery, reveals something important about this moment. The conversation around AI and work has calcified into two camps. The doomers say we’re all going to be replaced, and the boosters say everything will be fine. Neither camp captures what it actually feels like to live through this. The truth is messier. You can hold wonder and grief in the same hand, mourn a version of yourself while sprinting toward a new one.

What I’ve found more interesting than my own experience, though, is what I’ve observed in the people around me. I run South Park Commons, a community and venture capital fund for builders who are figuring out what to work on next. Through SPC, I see hundreds of engineers, founders and technologists navigating this shift in real time. And there’s a pattern that keeps surfacing: The old playbook for evaluating talent is breaking down.

One of our members recently ran about 20 work trials for engineering hires—essentially, extended, weeklong job interviews—and found zero correlation between years of experience and adaptability to AI tools. Another member told me that what predicted success in hiring people who possess that adaptability was evidence of a builder’s disposition: cool personal websites, side projects, an obvious love of making things. FAANG on the résumé and a name-brand university, meanwhile, predicted almost nothing.

A third member shared something even more striking. His company started giving tasks that were intentionally too long to complete by hand during coding interviews. The assignment became a remarkably clean filter: You could quickly tell who was using AI tools in their daily work versus who had merely been reading about them. The gap in the number of lines of code the two groups write wasn’t 10%. It was closer to 10x.

This might sound like a narrow observation about the software industry, but I think it’s something bigger. We are in the middle of what may be the largest shift ever in how knowledge work gets done. And the trait that matters most isn’t intelligence, or credentials or years of experience. It’s someone’s relationship with change—not whether they’ve seen change before, but whether they run toward it.

There’s a common assumption that younger workers will adapt more easily and older ones will resist. But the dividing line isn’t generational—it’s dispositional. Willingness to change seems to operate as an independent variable, cutting across age and seniority in ways that defy easy categorization. I’ve watched 15-year industry veterans pick up these tools and absolutely crush it, while some recent graduates treat AI as an abstraction to be debated rather than a tool to be used.

As an investor, this realization has reshaped what I look for in founders. The people I’m most excited about aren’t the ones with perfect pedigrees. They’re the people who seem constitutionally unable to stop tinkering, who get antsy when things stay the same, who treat every new tool like a puzzle they need to solve before the day is over. I’ve started to think of it as the difference between your résumé and your restlessness. I’d bet on restlessness every time.

Silicon Valley has always been one of the most meritocratic industries, but that has never meant credentials and experience don’t matter here. They just matter less. Now they are going to become even less important.

Paul Ford wrote beautifully in The New York Times about vibe coding’s potential to democratize software, to put the power of building into more hands. I share his optimism. But I’d add that this democratization isn’t just about access to tools. It’s a reordering of what we value in people. We spent decades building a culture that worships credentials and experience. Those things aren’t worthless, but they’re no longer sufficient. The new currency is adaptability, and unlike a Stanford degree, it’s available to everyone.

If anything, this shift is teaching me what it is like to be human again—not human in the romantic, AI-can-never-replace-us sense, but human in the uncomfortable sense, the part where you have to let go of the thing you were in order to become the thing you might be.

That’s always been the hardest part, long before AI. The technology just made it impossible to ignore.

This article was first published in The Information.

Aditya Agarwal is a general partner at South Park Commons. He was previously chief technology officer of Dropbox and an early engineer at Facebook.

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