Shaun Clowes: preference

Transcript context

…I love that. And it sounds like in your experience you're just using straight-up OpenAI, ChatGPT, Claude, not any specific tool for user research for this specific use case. No, mostly I find that the straight-up LLMs themselves are good enough and we do have some internal tooling that we built around, I don't know if you've ever had Sachin Rekhi on the show, you may have. He was a product leader pretty well known in the gross community, and he was a leader at LinkedIn for a long time and he used to call this concept a Feedback River, and he basically said that really smart product managers are constantly swimming at a Feedback River. They set out to surround themselves by Feedback River and I really deeply believe in that. It's like, "Okay, how can I surround myself with user interview data, with direct customer feedback, with NPS data, with competitor information?" Like I'm always trying to wash myself over with information. And where I'm going with this is that LLMs and tooling based on it can be exceptionally good for this. So for example, at Confluent we get a ton of inbound customer requests, as you can imagine coming from the field or directly from customers. We use LLMs to take in those asks to summarize what they're about, to find other asks that are like that one, really in a compelling way, a real way, like a semantic way, not other words, exactly the same, are these the same concept? So that we can look across all of the inbound demand on us and say, "Well, the most popular idea is this one and is getting more popular. The least popular idea is this one. It is getting less popular." In a really deep rich way, even across hundreds or thousands of pieces of inbound feedback. I think it's a really great time to be a product manager if you can put these types of tools to work, but they don't do the job for you, they just help you do these things that are intricate in that job of finding the gaps, finding the opportunities, finding the common threads without necessarily having to do all of it just inside your wear-wear, just inside your brain. I'm going to stay in this AI river that we're in right now and ask a couple more AI-related questions. And this may be what you just said, but I'm curious if there's more here. You kind of have this hot take that the way AI will most impact product management is data management and data versus models you're building or anything else. Can you talk about what you've seen there?…

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