Bill Gurley spent three decades making billion-dollar bets on founders. He backed Uber, OpenTable, and a dozen other category-defining companies. Then he retired from venture and wrote "Running Down a Dream," spending the last two years advising people early in their careers to pursue their passions with unrelenting force.

Last week on the All In podcast, the hosts asked him how that advice holds up in a world where AI doomers are predicting mass job loss. His answer reframed the entire conversation.

Before worrying about AI eliminating jobs, Gurley pointed to a number that doesn't get nearly enough attention: 59% of workers are already ambivalent about their jobs. Quiet quitters. People who haven't left but aren't leaning in either. His point was simple. Maybe we're not asking the right questions. Maybe, as he put it, "nobody is asking the warehouse worker at Amazon whether they actually want that job."

He then cited Mark Cuban: "There are two types of people in the world. Those that use AI to learn faster than they ever could before, and those that use AI to avoid learning altogether."

Gurley points out that distinction is really a matter of whether or not you’re high agency and passionate about your job.

It’s a distinction that I've watched play out in real time across our customer base.

The Three Buckets

Now that AI literacy is a baseline skill, we're past the era of "learning to prompt." What we're watching now is behavioural. Across our customers, adoption of Gigi falls into three distinct groups.

The first group doesn't adopt at all. They're set in their current workflows. For whatever reason, whether it's resistance to change, comfort with the status quo, or something harder to name, they choose not to engage.

The second group treats Gigi as a cheat code, as Cuban mentioned. The goal isn't to do more, it's to do the same with less effort. They automate as much as possible, stay hands-off, and measure success by how little they have to touch. The job just gets easier.

The third group is different. They see Gigi as a force multiplier. They assign work they couldn't have done on their own. They raise the ceiling on what they can deliver to clients. They use Gigi to get ahead personally and drive their company forward.

What Adoption Actually Signals

Here's what we've concluded from watching this: how a media manager adopts Gigi is a direct proxy for how they feel about their job.

The third group adopts AI because they want to be great. Their behaviour is a statement: I care about this work, I want to stand out, I want to transform what our team is capable of. Last week we published a case study with the agency Canvas. The entire Canvas team is a direct example of this third group. From day one they had high conviction about what advertising excellence should look like, and they immediately recognised that Gigi could get them there in ways they never could before. They became our most active and engaged customer, pushing both our team and Gigi toward possibilities none of us had mapped yet.

The inverse is equally true. Lack of adoption signals ambivalence. It signals a person who, in Gurley's framing, was never high agency to begin with. These are the same people who were quiet quitting before AI showed up and AI merely illuminates their ambivalence.

Why Tracking AI Usage is Good

There's been a strange backlash against AI scorecards and AI usage appearing in performance reviews. I think this is backwards. We should be leaning into this.

The team members who lean into AI demonstrate a growth mindset and a genuine desire to improve. The ones who don't are demonstrating something too. AI usage in performance reviews is just formalizing what behaviour has already told you.

The best people aren't afraid of being measured on it. They're the ones pushing for more. Gurley's insight wasn't really about AI, it was about high agency and AI just gave us a way to measure it.