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Lenny's Podcast · 3 min · Nov 8, 2026

Google pairs frontier models with a full-stack strategy

Tulsee Doshi · Head of Product, Google

Google links hardware, frontier models and products, while targeting users across a cost-quality range.

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
Up next · My First MillionPeer groups can become durable businesses in overlooked industriesPro pick 7:16
“we actually go all the way from the hardware to then the modeling to then this kind of end user application.”
Tulsee Doshiat 7:41 · Lenny's Podcast
7:41

Takeaways

  1. Google links hardware, models and end-user products.
  2. It targets different users across the cost-quality range.
  3. Doshi says Google wants to compete at the frontier.

About this segment

Google links hardware, frontier models and products, while targeting users across a cost-quality range. Tulsee Doshi says Google still aims to compete at the frontier, not only win through distribution.

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. 6:30

    I want to talk a little bit about Google's place in the AI race. It feels like a lot of people feel that Google lags behind the top two labs right now, Anthropic and OpenAI. And Google has these moments of being the best and then it kind of feels like it slows down a bit. I'm curious what you can share about just Google's strategy in the AI race and what maybe people don't understand on the inside of how you all think about this stuff.

  2. 6:54

    First of all, hopefully by the time this conversation goes out, you will be using Gemini 4 Argonne, which is exciting. And so I really do hope we're having a conversation about a frontier AI model that folks are excited to use. And I think Gemini 4 speaks a little bit to our strategy, right? Because it really is our push to continue to build a frontier lab, a frontier set of models, a frontier set of capabilities on our path.

  3. 7:23

    I think if you look at Google's strategy, it really is full stack, right? So one of the things that I think is powerful about Google is all the way from hardware to end products that serve billions of users. I think the stat is like we have 14 products that are above a billion users. I should check that number, but I think that's the stat. And so if you think about that, we actually go all the way from the hardware to then the modeling to then this kind of end user application.

  4. 7:52

    And our goal ultimately is to not just build amazing frontier experiences, which is definitely a part of the goal, but it is also to build models across this Pareto curve of cost to quality that can serve different users at different points in their lifestyle, whether that be a search user who is coming for Information, right? Whether it is an engineer who is trying to build the next amazing thing, whether it is for a cyber defender who is trying to protect a critical piece of infrastructure.

  5. 8:20

    I think our goal is to make sure that we have models that serve that range of use cases and that we're actually building with feedback from these users.

  6. 8:30

    So what I'm hearing is there's so many vectors where Google can win. There's the most efficient kind of Pareto Frontier. For token costs, there's the smartest model. There's also just making your products better. For example, AI mode, AI overviews. And so it's not that you need to be the best at the most advanced AI model that people can use, like Chatbot, basically. You can win in all these other areas.

  7. 8:54

    But it sounds like you're also trying to win and have the most state-of-the-art model I actually think we do want to win the frontier conversation, right?

  8. 9:03

    I don't think we should say that Google is not participating in the frontier. And I think we are building better and better models. And I think Gemini for Argonne definitely is at the frontier in the place that we are at. But I think one thing that is amazing is being able to build a breadth of experiences and build a diversity of experiences for users. And I think for Google, Our goal ultimately is to build amazing experiences that actually make people's lives better, right?

  9. 9:37

    And that is, I think, ultimately the goal, whatever part of the frontier you're building for.