Aman Khan: evaluation

Transcript context

…So what I'm hearing is, if your team is building something that's very similar to some other, to a foundational models product for example, probably a red flag, probably not going to be a huge opportunity. So optimize for things that feel different and new. Anything else you want to add there? Because I have a question. Yeah, I think that's almost like a point of what do people do for the last two years, and now there's this moment of this actually happening again. And this moment is happening around the term of AI agents. I think if you really look at it, I actually bring up Yuriy's point again because I was listening to that episode, I thought that was so insightful of he gets so many emails every single day of, we're AI for this, we're building an AI agent for that. But again, you're sort of trying to fit this technology to solve a problem that, you're not really describing the problem. You're describing the solution, an AI agent to do something. So if you look at it, I'd really ask yourself, does it make sense to build an AI agent within our company or is it just better to allow the foundation model companies to build this agentic layer within their technology? And then your job is to make that experience so amazingly seamless in your existing product, that it doesn't even feel like AI in the first place. And I think that's really powerful. That's the area where product managers can truly innovate. Because let's be honest, you're probably not going to have these cutting edge researchers that can go and design a model from the ground up or maybe design some new technique to build a next agent framework. But what you can do is take that technology and find a way to apply it in your organization, and that's where I think the role of the AI PM really stands out. This episode is brought to you by Paragon, the developer platform for building native customer facing integrations with third party apps. Our native integrations on your product roadmap, whether it's to ingest context from your users' external data and documents, or to sync data and automate tasks across your users other apps, integrations are mission-critical for B2B software products today. But building these integrations in-house cost an average of three months of engineering according to the 2024 State of Integration Survey, which results in difficult roadmap trade offs. This is why engineering teams at Copy.ai, AI21, and over 100, other B2B SaaS companies use Paragon so they can focus their efforts on core product features, not integrations. The result, they've shipped integrations seven times faster, all while avoiding the never ending maintenance that comes with rolling your own integrations. Visit useparagon.com/Lenny to see how Paragon can help you accelerate your product's integration roadmap today and get $1,000 in credit on their Pro and Enterprise plans. That's useP-A-R-A-G-O-N.com. I imagine a lot of product leaders are hearing this and be like, thank God I need everyone on my team to hear this, because I am guessing every PM and every company is looking and proposing all these ideas, all these AI based ideas just because it's like, oh, we got to do AI. Here's an idea, here's an idea, and there's all these people chasing AI products. And so I think this advice is really important, and this has come up a number of times, people just try to keep reminding folks, focus on the problem you're solving and AI is a tool to solve it, not AI for blank just because. How have you found ways to find really interesting, actually good ideas for how to leverage AI within your company or companies you've seen?? Is it hackathons? Is it like we have our goals and just make sure there's AI parts to a solution? Is there anything practically that you find helpful in finding good ideas that are AI oriented?…

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