Ship to learn, not to be right

We have a principle called Ship to Learn. Ship fast, ship early, ship often. So, in that idea is the idea of failure. It's not going to go right. And, it's going to go wrong more often than not.

Many times, the fastest way to learn is to ship.

We have this philosophy, we call iterative deployment, and the idea is we're all learning about these models together. So there's a real sense in which it's way better to ship something even when you don't know the full set of capabilities and iterate together in public.

Sometimes you need to roll back and change things, but it's another opportunity to learn.

If you fail fast, you still have plenty of time to try another attempt and build another version of the product. The more attempts that you have, you simply increase the likelihood of being successful.

When you have great strategy, perfect strategy but poor execution, you don't win because your strategy never makes it to the market. And what's even worse is that you have learned nothing.

This is a pattern with AI, you won't know what to polish until after you ship.

What you want to do is that you want to be the first one to hit the brick wall. This is particularly true when you are in a market that is competitive. The reason for that is that if you consider yourself as an innovation-centric company and you believe that you are building experiences that fundamentally don't exist anywhere else and you're sort of paving the way for the rest of the folks to basically get inspired with how you are building these experiences, speed is the single biggest determinant, in my experience, in terms of who ends up being more successful versus not.