Diane Penn: recommendation

Transcript context

…So speaking on this thread, Dario, interestingly, if you look back at all his predictions, he's just like, "Okay, coding's going to be solved 100% in a year." Something like that. He kept talking about how AI is going to do all our code. And I remember everyone being like, "There's no way. This is way too complicated. How is AI ever going to get really good at this very complex thing that humans do? No, this is going to be humans for a long time." He was completely right. Something else that he talks a lot about is this exponential. Now that we're on, that's the way he describes it, now we're like, we're on the exponential curve. I remember not long ago, new models were being released and everybody was like, "Okay, we're done. There's no more upside. It's plateauing. It's over. There's no more room to grow." And now it's the opposite. Now we're inside. If you think about the curve of the exponential, we're inside of the exponential now, which by definition means every improvement is a massive jump because we're on that hockey stick part. What's it like just being on the inside of this crazy historic moment when AI is improving so fast, so much is being unlocked? What is it like and how should people prepare for the coming acceleration of more and more improvement from AI? One thing I like to say on the team is most of us weren't actively working yet when the internet transitioned from this novelty to something that everyone can use. And it feels like that's just taking humans... I think analogies are helpful. And so the analogy of that is I think a couple of things. Number one is adaptability becomes very important. I think we have evals, we have on the safety side, safety testing, red teaming on the capabilities and product side, new prototypes, products like Claude Code, Tag and others. But it's very hard to predict the exact moment or the exact model. And so the adaptability of when you're faced with new information, how do you then make better decisions versus keeping the same plan? And so that agility is really important. I think another piece is with that, how do you actually be thinking very first principles and reason through what's next? What's the so what? How do we invest in new products? How do we invest in explaining the differences to users? So a lot of the experiences I think of being in that exponential is that pace, understanding how you operate and make better decisions, and then applying that first principle's thinking to then do something that maybe we pull up a plan that we're expecting a few months from now, but now the model can actually do and work on and actually bring that to users. So this is things like co-work, skills, tag. It's a very positive self-enforcing loop. And I think a big part of it also is just having the trust in each other, making sure we're thinking through the right decision making. We're bringing folks along. Some teams might see the exponential feel it faster than others. So how do we have the grace to bring the organization, the growing organization and company along on that? So what I'm hearing here is you almost don't know what will be possible with every model release. And so the important things to focus on is being adaptable as things emerge. To your point, the product itself has to catch up to what is possible. To your point again, just like it can do so much, but people may not understand how to do it and may not be able to do it. So the product making it easy and even just telling you, here's something you could do feels like an important part. Is that roughly what you're describing?…

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