AI product managers and leaders at every level must be hands-on builders who personally ship with the technology and sweat tokens alongside their teams, or they cannot develop the judgment to make good decisions.
Dianne argues that tenure offers no shortcut: senior PMs and managers need the same hands-on onboarding as new hires because you cannot evaluate what good looks like in AI products without building yourself, and she personally carves out time to own one to two work streams per model cycle to stay grounded. ✦ AI generated
Dianne Penn · Lenny's Podcast · 2026-07-26 · original ↗
starts at this moment · 50:13
“Is there anything else that you find is shifted in what patterns are common across people that are doing well in this new AI world in terms of product managers and folks on the product teams?”
One thing that I think I feel pretty strongly about is in order to be good managers of teams and PMs working with this technology, you have to be really hands-on yourself and have spent not just time tinkering but actually shipping with this technology and and and again being in the details and sweating the tokens along with your PMS and your engineer and your teams. And so even for folks that I hire who have more tenure PM experience, the onboarding plans are exactly the same as somebody who is like more uh early career and it's around understanding users, reading like consented user feedback, talking to customers. I think there's something around uh being able to like understand what to do with this, what what good looks like and having developed that in a very hands-on manner. That's important. Um it's not necessarily easy for someone to uh agree or be able to see what a what a good or great AI product or AI feature could look like if they haven't kind of experienced building themselves. Um, so I think I think there is a I I I do feel pretty strongly that like, you know, if you're a manager, you have to be hands-on. You have to spend a portion of your time actually shipping. You you have to kind of walk in the shoes of your teams. uh and and that's I I always try to carve out a portion of time uh to to actually like own one to two work streams when we have models in order to keep like keep my theory of mind, keep my sense of how the models are moving, how quickly it's improving uh uh so I can help the team make make decisions and and make better decisions.
verbatim transcript · starts at 50:13
50:13product teams? Is there anything else that you're like, okay, does something you got to shift or something you look for more people? I think maybe specifically uh for folks who might be midc career or folks who have been more in a managerial like product like leadership seat. Um, one thing that I think I feel pretty strongly about is in order to be good managers of teams and PMs working with this technology,
50:43you have to be really hands-on yourself and have spent not just time tinkering but actually shipping with this technology and and and again being in the details and sweating the tokens along with your PMS and your engineer. and your teams. And so even for folks that I hire who have more tenure PM experience, the onboarding plans are exactly the same as somebody who is like more uh early career and
51:17it's around understanding users, reading like consented user feedback, talking to customers. I think there's something around uh being able to like understand what to do with this, what what good looks like and having developed that in a very hands-on manner. That's important. Um it's not necessarily easy for someone to uh agree or be able to see what a what a good or great AI product or AI feature
51:51could look like if they haven't kind of experienced building themselves. Um, so I think I think there is a I I I do feel pretty strongly that like, you know, if you're a manager, you have to be hands-on. You have to spend a portion of your time actually shipping. You you have to kind of walk in the shoes of your teams. uh and and that's I I always try to carve out a portion of
52:16time uh to to actually like own one to two work streams when we have models in order to keep like keep my theory of mind, keep my sense of how the models are moving, how quickly it's improving uh uh so I can help the team make make decisions and and make better decisions. So, what I'm hearing here is if you're not, no matter where you are in the
52:38ladder of hierarchy at a company, if you're not building yourself, if you're not actually talking to Claude, talking to Codex, building stuff, you're not going to make it. >> And you should have fun working with his technology. I think that's the other piece. I think the folks that would be most successful regardless of their level are people who love working with AI and and are exploring and