Products are becoming living systems, not static artifacts

In AI product development, a "rewards model" is a system that evaluates and scores product outcomes, and "digesting" it means processing and acting on its feedback.

All of a sudden products aren't just like these static artifacts that we start to ship that's not just like, 'Hey, come up with an idea or an insight. Go solve a problem, ship it into the world, maybe make it a little bit better and then have a dashboard.' All of a sudden, the whole KPI is what is the metabolism of a product team to be able to ingest data and then digest the rewards model and then create some sort of outcome?

I think there's a big difference between moving from 80% performance to 90% performance to 99% performance to 99.9% performance. Within the next one or two years, the models are going to automate 80% of the average L6 software engineer's job. It's going to take another few years to move to 90%, and another few to 99%.

Think of SEO as a product. The product managers are the people that should be thinking about this SEO question because it's a product question.

"Scaling loss" appears to be a transcription error - likely meant to say "scaling laws," which refer to predictable patterns in AI model performance as you increase data, compute, and model size.

I definitely think we need more innovations. I think scaling loss of more data, more GPUs, and bigger current model architecture is there's still a lot to be done there, but I absolutely think we need to innovate more.