# Build for what models can do now and next

Markdown copy of https://realalpha.app/s/build-for-what-models-can-do-now-and-next/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Tulsee Doshi](https://realalpha.app/builders/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.
- Host: [Lenny Rachitsky](https://realalpha.app/people/lenny-rachitsky/) · Host, Lenny's Podcast · Spent seven years at Airbnb; his product newsletter has over 1M subscribers.
- Show: Lenny's Podcast
- Episode: [Why Google wants to win the frontier conversation | Tulsee Doshi (Head of Product for Gemini)](https://realalpha.app/v/qGf2Yvan4Wg/), Nov 8, 2026
- Moment: 33:07 to 35:33 of the episode (2 min), playing on https://realalpha.app/s/build-for-what-models-can-do-now-and-next/; the episode from there: https://realalpha.app/v/qGf2Yvan4Wg/?t=1987

## Takeaways

1. Keep roughly 60% of the product working now.
2. Prototype capabilities that seem close to becoming reliable.
3. Leave room for ideas that models may soon unlock.

## About this segment

Tulsee Doshi’s 60-20-20 framework balances working features with capabilities that are nearly ready and more ambitious ideas. It lets a product work today while improving as models advance.

From “Why Google wants to win the frontier conversation | Tulsee Doshi (Head of Product for Gemini)”, Nov 8, 2026. [Watch the full episode](https://realalpha.app/v/qGf2Yvan4Wg/)

## Transcript

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

[33:11](https://realalpha.app/v/qGf2Yvan4Wg/?t=1991) Have you heard lots of changed? Okay, so going in somewhat of a different direction, you have this framework that I think is going to be really helpful to people around how far ahead to build in terms of how far AI is and how far your product should assume AI is going to be. You call that a 60-20-20 rule. Explain that.

[33:29](https://realalpha.app/v/qGf2Yvan4Wg/?t=2009) I think the numbers are probably fungible here, but I think the thesis is the same, which is I think as you're building today and as you're a product developer building using these models, I think the important thing is to keep in mind that these models are consistently changing. And so the capabilities that you have today will not be the capabilities you have tomorrow or the next day. And so you want to actually build features that aren't necessarily always working today, right?

[33:58](https://realalpha.app/v/qGf2Yvan4Wg/?t=2038) So typically when you talk about Like traditional startup wisdom. I think you're just like build an MVP that works, right? But I think what you want to do is actually build such that like 60% of what you've built works now. And your prototype is at least functional, right? Then there's a set of maybe the 20% where you're like, it's not perfect, but it like works well enough. And I can see how the models might get here in the very near future.

[34:23](https://realalpha.app/v/qGf2Yvan4Wg/?t=2063) And then here's where I want the models to be. And here's I see glimmers of light. And I feel like if I could crack this, like this would be an amazing product experience. And I think if you build in that way, you are building a product that works today. But you're setting yourself up to build a magical product experience as the models become better and also to grow as the models grow, too.

[34:43](https://realalpha.app/v/qGf2Yvan4Wg/?t=2083) I've heard a lot of advice along these lines of how far ahead to build. And the most common is just like build like three months ahead of where the models are going to be. And this feels like a lot more practical where you can't just bet on the future. You also need to ship some things today that are great and working.

[34:58](https://realalpha.app/v/qGf2Yvan4Wg/?t=2098) It's trying to find that balance, right? And I think also I find personally hard to know where the models, as someone who works on the model, to tell you exactly where the model is going to be three months from now. And so I think using more of your own proxies of like, where is my product? Where do I see glimmers of light? Where do I see it kind of bridging that gap? I think is a more concrete way to hopefully like Ask that same question.

[35:21](https://realalpha.app/v/qGf2Yvan4Wg/?t=2121) This reminds me of just another way of thinking about how to kind of create a portfolio of product bets on a product team. Like the way it used to be is like have some ambitious bold bets,