Aman Khan: prediction

Transcript context

…I feel a little bit like an outsider on the space myself. I wasn't related at all, the field I studied was mechanical engineering. I didn't really take computer science courses, I had to learn a lot of that on my own. And I didn't take machine learning or AI courses either, I don't have a PhD or master's in the subject. But coming back to both types of product managers you just described, there's the AI PM who's building infrastructure for other AI engineers, and there's the AI power product manager who's building AI products really. And I think in both cases, you care about the end customer. At the end of the day, you really want to be in love with the problem. I know that you said that, that was a great, great quote in my mind as well of, if you're in love with the problem, you are trying to push the boundaries of what's possible with technology to solve that problem. And for me, I really became obsessed trying to help really technical users, AI engineers, data scientists, with problems that I thought were not super challenging, like how do I build a dashboard to understand how my model is working? That can't be that hard to do. And then as you get deeper, the complexity starts to emerge in that part of the stack and you have to realize you pushing, you're actually responsible for pushing technology forward in some ways. You're trying to see what's possible and keep pushing the space forward to solve that customer problem. I think the same thing is true for AI product managers, meaning you're really trying to design the best customer experience and really solve your customers' problems. And I think if you are obsessed with that and you spend time just trying to realize, what would an ideal experience look like that I'm trying to solve, you'll find tools along the way to help unbox really that problem. So I think if we take an example of that, let's imagine that you're working for a company that might be having customers that have customer support problems or people coming in with complaints. And when you think about the surface area of customer support, it's not that great. You usually have to type in some questions with a chatbot that's routing perhaps incorrectly, [inaudible 00:16:13] some document to go solve a problem. Or if you're trying to call in, you have to describe your problem, but you're not really sure if you're being heard correctly. It might be super long wait times. And if you're the product manager of that experience, I think an ideal product experience really looks like a customer reaches you with a problem and you're able to really solve that problem for them. And it doesn't really matter what's in between, you want to reduce the friction of that as much as possible. And so now when you think, okay, let's assume that I'm starting with a phone call, there's a ton of tools that are starting to emerge. And I think a really cutting edge one from the last couple of weeks has been Open AI releasing a real time API. that I'm starting with a phone call, there's a ton of tools that are starting to emerge. And I think a really cutting edge one from the last couple of weeks has been Open AI releasing a real time API. And the real time API is basically a voice API where you can provide some text and almost have this real time experience with a bot that is actually AI generated. And if you're a consumer, you can even try that out in the application yourself. You can open up ChatGPT and if you're a Plus subscriber, you can try this cutting edge sort of voice chatbot experience. And why is this interesting? Because if you're a consumer and you're trying out technology and you're trying out AI technology and trying to push the boundaries of what's possible, I think you can have that light bulb aha moment of, I can take this thing that kind of feels like it's early but it could be something here, and go take it to my team and say maybe it's possible for us to use this thing. And so I think that's really what this whole space is about. I want to underscore that, you are really driven by your own curiosity. And your curiosity can push you in a lot of different directions in terms of the types of tools you might want to pick up for yourself or even implement in your own product. So I think it truly is this opportunity for people to see what drives them and try and find the tools that really help make that experience possible. To pull on this thread a little bit more, say someone wants to apply, I want to be an AI PM, there's two questions here. One is, what do you recommend they specifically learn skill-wise, technical-wise, to have some chance at becoming an AI PM? If that's a thing versus just like, hey, just you're a PM, build awesome products and they happen to integrate AI. That might be the best solution. If that's your advice, definitely say that.…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.