Mike Krieger

We're really big on research, and product is this very small claw still. Or the other metaphor I've been using is you're a teenager. Some of your limbs have grown faster than others, and some are still catching up. The kind of... crazier bet is I would love for us to not have to then double the product team.

We're really big on research, and product is this very small claw still. Or the other metaphor I've been using is you're a teenager. Some of your limbs have grown faster than others, and some are still catching up. The kind of... crazier bet is I would love for us to not have to then double the product team.

We're really big on research, and product is this very small claw still. Or the other metaphor I've been using is you're a teenager. Some of your limbs have grown faster than others, and some are still catching up. The kind of... crazier bet is I would love for us to not have to then double the product team.

I'd love for us instead to find ways of using Cloud to make us more effective at everything we do on products so that we don't have to double. Because every team struggles with this, so this is not a novel observation. But I look back at Instagram, When I left, we were 500 engineers. Were we more productive than at 250? Almost certainly not.

I'd love for us instead to find ways of using Cloud to make us more effective at everything we do on products so that we don't have to double. Because every team struggles with this, so this is not a novel observation. But I look back at Instagram, When I left, we were 500 engineers. Were we more productive than at 250? Almost certainly not.

I'd love for us instead to find ways of using Cloud to make us more effective at everything we do on products so that we don't have to double. Because every team struggles with this, so this is not a novel observation. But I look back at Instagram, When I left, we were 500 engineers. Were we more productive than at 250? Almost certainly not.

Were we more productive than at like 125 to 250 marginally? You know, I had a really depressing interview once when I was trying to hire a VP of Engine. I was like, how do you think about developer efficiency and like team growth?

Were we more productive than at like 125 to 250 marginally? You know, I had a really depressing interview once when I was trying to hire a VP of Engine. I was like, how do you think about developer efficiency and like team growth?

Were we more productive than at like 125 to 250 marginally? You know, I had a really depressing interview once when I was trying to hire a VP of Engine. I was like, how do you think about developer efficiency and like team growth?

And he's like, well, if every single person I hire is at least like net contributing, like something that's succeeding, even if it's like sub number, like a one to one ratio or before, I'm like, That's depressing. And I think it creates all this other swirl around just team culture dilution, et cetera. So that's something I'm personally passionate about.

And he's like, well, if every single person I hire is at least like net contributing, like something that's succeeding, even if it's like sub number, like a one to one ratio or before, I'm like, That's depressing. And I think it creates all this other swirl around just team culture dilution, et cetera. So that's something I'm personally passionate about.

And he's like, well, if every single person I hire is at least like net contributing, like something that's succeeding, even if it's like sub number, like a one to one ratio or before, I'm like, That's depressing. And I think it creates all this other swirl around just team culture dilution, et cetera. So that's something I'm personally passionate about.

How do we take what we know about how these models work and actually make it so the team can stay smaller and more tight-knit?

How do we take what we know about how these models work and actually make it so the team can stay smaller and more tight-knit?

How do we take what we know about how these models work and actually make it so the team can stay smaller and more tight-knit?

I would probably put it in three places. One is in the actual model training and fine-tuning, where part of what we do on the reinforcement learning side is saying we'd like to find a constitution for how we think Cloud should be in the world. And that gets baked into the model itself early, before you hit the system prompt, before people are interacting with it.

I would probably put it in three places. One is in the actual model training and fine-tuning, where part of what we do on the reinforcement learning side is saying we'd like to find a constitution for how we think Cloud should be in the world. And that gets baked into the model itself early, before you hit the system prompt, before people are interacting with it.

I would probably put it in three places. One is in the actual model training and fine-tuning, where part of what we do on the reinforcement learning side is saying we'd like to find a constitution for how we think Cloud should be in the world. And that gets baked into the model itself early, before you hit the system prompt, before people are interacting with it.

That's getting encoded into that around how should it behave? Should it be willing to answer and be willing to chime in on where should it not be. And that's, I think, very linked to the responsible scaling piece. Then next is in the actual system prompt. So we actually, in the spirit of transparency, just started publishing our system prompts.

That's getting encoded into that around how should it behave? Should it be willing to answer and be willing to chime in on where should it not be. And that's, I think, very linked to the responsible scaling piece. Then next is in the actual system prompt. So we actually, in the spirit of transparency, just started publishing our system prompts.