Robert Ta argues that senior experts training AI systems create outsized value for their organizations but rarely get paid for it. He pushes for compensation tied to the multiplicative productivity boost their expertise generates. The other speaker proposes tracking how each expert's encoded knowledge drives measurable company value through a knowledge-attribution system.
There is one other nugget that I got from an executive who has ran teams of 3,000 to 4,000+ product managers, designers, engineers. One of my mentors, Mike, he talks about this, which is we know that that's the thing to do, which is get the experts to compound their intelligence. We know that they're the A-players of the org. And then the question is, are we compensating them for that fairly? And I thought he brought up such a good point, which is if we're now we're asking these people to go out of their way to annotate the data and say that's part of the job, job's changing and hey, you have way more leverage by doing this thing. Aka I'm annotating these stories, I'm annotating these agent runs, I'm annotating the whatever to improve the harness. Now the harness has a multiplicative productivity J-curve effect on every employee in your org. You take that unicorn employee, you have them train the agent, and if their investment into that produces a J-curve sort of productivity multiplier for the rest of your org, aka a novice sort of product manager can come in and act as a staff-level PM, like, you know, they're not gonna have the same judgment quality or whatever, but they can come in there and be effective way more than the before world where you had the shadow for 6 to 12 months and then you're maybe effective. In my opinion, hot take maybe, think about your incentive structure for that behavior that you want to compound that investment for this intelligence layer, the company brain. Are you incenting your A-players to be on the front lines to do that? That's a really critical thing that I think every exec should be thinking about. And if you aren't and they're not doing it, well then you haven't created the systems or the environment to encourage the behavior that you would like out of the org. And that's just full stop the issue. What's your take on that? Should experts be compensated for the compounding leverage leverage that their time now gets by doing these activities, by doing the annotations, by doing the agent reviews.
Yeah, the world I'd like to see is one knowledge attribution, like say you're encoding expertise into a dataset and that's used to train prompts and agents that are used by other people. I mean, you can trace the attribution now. That's really like ideally becomes kind of a knowledge marketplace where you get credit, you get attribution. The agent I helped train and did so many different tasks today, you know, like it did 100 tasks today. That's your leaderboard, right? You don't want token matching leaderboard. You want like, where's the knowledge attribution used in context to provide company value leaderboard. That's how I like to see it.
