02 / preference

14 Dec 2025

One example that comes to mind is when I was working on my startup and before that, when I was at Dropbox, it was very important, especially as a PM to always rally the ship and it was like make sure you're pointed in the right direction and then you can accelerate in that direction. But here, I think because we don't exactly know what capabilities will even come up soon and we don't know what's going to work technically, and then we also don't know what's going to land even if it works technically, it's much more important for us to be very humble and learn a lot more empirically and just try things quickly.

“One example that comes to mind is when I was working on my startup and before that, when I was at Dropbox, it was very important, especially as a PM to always rally the ship and it was like make sure you're pointed in the right direction and then you can accelerate in that direction. But here, I think because we don't exactly know what capabilities will even come up soon and we don't know what's going to work technically, and then we also don't know what's going to land even if it works technically, it's much more important for us to be very humble and learn a lot more empirically and just try things quickly.”

Speaker: Alexander Embiricos
Episode: Why humans are AI’s biggest bottleneck (and what’s coming in 2026) | Alexander Embiricos (OpenAI Codex Product Lead)
Publisher: Lenny's Podcast

Alexander Embiricos

What Alexander said.

Another thing that we do that I think we might be the most user feedback/social media pilled team out there in this space is like a few of us are constantly on Reddit and Twitter, and there's praise up there and there's a lot of complaints, but we take the complaints very seriously and look at them.