Ryan Kidd: prediction

Transcript context

…And they're the ones that are running the experiments day-to-day, building the tooling, writing the code traditionally to like do the visualizations of the data and kind of taking this sort of initial conceptual hit that the connector came up with and like really kind of systematically mapping out that space. And then these organizations, as they grow, then they start to need amplifiers, which I maybe would call like leaders, you know, people that can sort of build up an organization, see that people are working well together, that it can go past the sort of two pizza rule, right, in scale. Is that changing now? So, you know, when We hear things like 90% of code will be written by Claude, and that seems like it's, you know, kind of closer to right than wrong. And certainly like I vibe coded three AI apps for family members for Christmas presents this year, which is something I, you know, would not have come close to being able to build previously, even with, you know, just one or two generations of model and go. I do wonder how much the skill set is already changing? What are you seeing there? What's the up-to-the-minute in terms of how people are thinking about changing hiring needs? I mean, up-to-the-minute is that you have to be very proficient at using AI. And I think that some of the companies have updated their coding interview processes to allow for use of AI assistance. Because on the job, you have to be using AI all the time. That's just critical to succeeding in this field, to be amplified by AI. I would say that goes for every one of these archetypes we've identified. I do think as well that checking whether AI output is good or not in critical context is still going to be a very important thing. And stitching together different types of AI output and building pipelines to more efficiently process that are also going to be very critical. But we might be leaving the leap code era. I will say this, that like amplifiers, while not currently the most in demand across all different hierarchies of AI safety organization or team are, I think, probably in the next year or two going to be the most in demand. But that's just, that's based on my predictions about AI progress. As you say, it could be slower. You know, there could be jaggedness concerns, you know, that slow down this type of talent transition. But in general, it's never good for your, it's never bad for your employability to spec out as a manager. Managers are very useful and leadership traits in general make you more useful, better employee. It's part of personal growth, I think, to take on some leadership roles. What does supply and demand look like these days in terms of like, you know, I guess maybe even at the highest level, going back to the, you know, the sort of origin story of Matt's, my understanding was you said, geez, this AI safety thing seems like it's going to require a lot of people working on it in a lot of different roles. And This is not something that universities teach, right? So like, how do people, what's the on-ramp to doing this? If they're, if somebody would benefit from one, like, you know, where do they go? So you've essentially created one, and of course there's some other others out there too, but you've created one of the largest and most highly regarded ones. Where are we in terms of like, are there a lot more jobs out there than mats can produce fellows? Are there, yeah, you know, how do you think about that? I feel like we've gone back and forth a couple times where at one time it was like, Oh, we're super talent constrained, and then it was like, Well, maybe not so much anymore. Now it's like there aren't actually a lot of roles for people to go into. Maybe I'm wrong on this, but I feel like this has seesawed back and forth, and I don't know exactly where we are today.…

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