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Lenny's Podcast · 4 min · Nov 8, 2026

Model behavior is part of the product's UX

Tulsee Doshi says UX varies by user, from broad-access products to power-user tools, and includes how the model communicates.

In this episode

Full analysis
  1. 2:11Model PMs have to discover what training produces3 min
  2. 33:07Build for what models can do now and nextPro pick 2 min
  3. 26:30Better evaluations can expose gaps in representation3 min
  4. 10:33Google's safety plan combines monitoring with cyber defense3 min
  5. 21:22Research PMs should test models and start with small evals3 min
  6. 37:27Teams need time to build and share AI workflows5 min
  7. 14:06Model behavior is part of the product's UX4 min
  8. 6:26Google pairs frontier models with a full-stack strategy3 min
“it's also important to think about the model as having a UX also.”
Tulsee Doshiat 17:02 · Lenny's Podcast
17:02

Takeaways

  1. Match the interface to the user's needs and expertise.
  2. Model transparency and communication are also UX.
  3. Turn feedback into behavior specs, rubrics and training data.

About this segment

Tulsee Doshi says UX varies by user, from broad-access products to power-user tools, and includes how the model communicates. PMs turn customer feedback into behavior specs, rubrics and reward-modeling data.

Tulsee Doshi

Tulsee Doshi is head of product for Google’s frontier AI models.

Leads the Gemini product roadmap and strategy after five years heading Google's Responsible AI product work.

  • Lenny Rachitsky, Host · Host, Lenny's Podcast

    Spent seven years at Airbnb; his product newsletter has over 1M subscribers.

From “Why Google wants to win the frontier conversation | Tulsee Doshi (Head of Product for Gemini)”, Nov 8, 2026. Watch the full episode

Transcript

From the transcript Lenny's Podcast publishes with the episode.

  1. 14:09

    Okay. So one of the interesting things that's happening kind of from a product perspective with AI is Products are getting very complicated. For example, Google gets a lot of flack for it being hard to find all the magical things you all do. Like a lot of people don't know AI Studio even exists. A lot of people can't find VIA or Genie and all these things. Similarly, Codex, ChatGPT recently launched Dots and now you go to the interface of Codex and it's like tabs and dropdowns and Dots and it's just like out of control.

  2. 14:41

    And Cloud Code is the same thing. It's just getting very complicated. That code work and then they drop code work and And interestingly, I'm in this WhatsApp group with a bunch of PMs, and there's a PM from one of the labs.

  3. 14:51

    Well, I won't be in this WhatsApp group. Sorry. Okay. Let's talk. Let's talk. And he showed that there's this kind of urgency to get frontier power of AI out to users as fast as possible, partly to stay competitive, partly because they don't know exactly what it's used for yet. So let's get it to people, figure out what they're using for it, and then make the UX better. So there's this kind of intentional, let's just get it out there, figure it out later how to make it a great UX.

  4. 15:18

    Thoughts on this kind of balance of making the product really easy to use versus just getting things out as quickly as possible. And is that something you deal with? Two thoughts, maybe, maybe three.

  5. 15:28

    The first one I'll say is I do think we do need to be playing with new paradigms and new UX approaches, if you will, to how people will engage with models. Right. So you mentioned, for example, Genie or Veo, which is which we're now building Omni. Like if you look at, for example, Flow. Flow is a product that we've been designing, thinking about video editing in generation, music editing in generation.

  6. 15:54

    And so I think we are trying to play with like Notebook LM is a good example of a different form factor. I think our labs teams are actively thinking about like, how do we try different form factors in different UX for different individuals to engage with these models? And so I do think we need to keep innovating and playing around with what UX looks like. I think at the same time, Your point is also right, which is like, I think depending on who your user is, you want a different form factor too, right?

  7. 16:20

    So like, I think, for example, with AI mode, we're talking about billions of users coming to search, asking their questions. I think you do need to have a certain UX there that is accessible to every user, right? At the same time, on the other end of the spectrum, when you have something like anti-gravity, you are trying to build for a power user. And you are trying to build for users who know how to use slash commands and can actively engage across both the terminal and the IDE.

  8. 16:47

    And you want to be able to support kind of a wide range of what a user can do. And so I think depending on who your user is, you have a certain level of flexibility with how you think about the UX, right? That makes sense.

  9. 16:59

    Basically, there's different services for different levels of how radical you can change things.

  10. 17:03

    Yeah. And I think the other part, too, is like, I think it's also important to think about the model as having a UX also. Right. So one of the things I think about a lot is like a PM for the model is like, what is the UX of actually using the model? Right. So how transparent is the model? How well does it communicate with you? What questions does it come back and ask you? Right. These are all actually this is all UX in its own way.

  11. 17:24

    And so I think it's also really interesting to think about, like, how do we bring conversations about UX into the actual model development process itself? That is really interesting.

  12. 17:32

    Basically, the personality of the model is the UX of the model. How do you, as a PM, inform that work with the researchers? Is it like, here's feedback on the way it's talking, and it should be a little more verbose here, and here's ways it could format things differently?

  13. 17:46

    I think the role of the PM here is actually really awesome because you are actually getting to shape what is the direction of where we want to go with the model's behavior, right? And so we have a team that works on model behavior here. And a lot of what we've been thinking about together is, A, looking at customer feedback and user feedback for how they engage. But also thinking through what does good look like for Gemini specifically, right?

  14. 18:10

    And how do we develop kind of a spec, if you will, for what does that look like? And then being able to translate that to rubrics, right, that we can then evaluate the model on to be able to translate that into data that we can actually leverage for the model to be able to translate that into our reward modeling. And so it's been actually like a really nice collaboration between PM and the research team.