Dianne Penn

speaker

606 appearances 1 recordings 1 series first heard Jul 2026 last heard 26 Jul

Dianne Penn’s voice in public audio — every appearance, attributed to the second.

Trend

recordings per month · last 12 months

Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

Appearances

newest first · ▶ plays the moment

Lenny's Podcast: Product | Career | Growth · Anthropic’s first technical PM on token maxing, the jagged edge, and living in the future | Dianne Penn · 26 Jul 2026 podcast

How do you get it to work well for some group?

So you can explore the value.

You can actually bring something that is coherent to a user group.

So we do have PRDs.

I think the application's a little different

I think maybe specifically for folks who might be mid-career or folks who have been more in a managerial product leadership seat, 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 has 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 engineers and your teams and so

Even for folks that I hire who have more tenured PM experience, the onboarding plans are exactly the same as somebody who is like more early career.

And it's around understanding users, reading like content and user feedback, talking to customers.

I think there's something around that.

being able to understand what to do with this, what good looks like, and having developed that in a very hands-on manner that's important.

It's not necessarily easy for someone to agree or be able to see what a good or great AI product or AI feature could look like if they haven't kind of experienced building

So I think there is a, 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 have to kind of walk in the shoes of your teams.

I always try to carve out a portion of time to actually own one to two work streams when we have models in order to keep my theory of mind, keep my sense of how the models are moving, how quickly it's improving, so I can help the team make decisions and make better decisions.

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 are exploring and experimenting and carving out the time, not just for the experimentation, but actually hands-on shipping end-to-end, getting the user feedback, I think has to be fundamental for everyone.

I think maybe I'll reemphasize something I said earlier around just that experimentation is not an individual sport.

Like some of the moments where I think I've touched practically every version of research models across 20 plus versions of Production Cloud at this point.

Showing 321–340 of 606 · page 17 of 31