I’ve been building AI for years.
It’s hard to admit, but many projects failed because I wasted months tweaking models and architectures, chasing improvements that never came.
Soon, AI development felt more like gambling than engineering.
And I’m not a good gambler.
I eventually realized I was focusing on the wrong thing:
The main driver of AI development is not your creativity or ability to build complex systems.
It’s your ability to systematically learn, from each experiment, what really matters to your users—and how to act on it.
It took me years to figure out how to systematically escape this loop.
You don’t have to: