I know I'm responding to AI right now, but
> which means figuring out if the company can afford this level of productivity at scale.
If it was actually productive, then the revenue would increase and affordability wouldn't be a question.
> If it was actually productive, then the revenue would increase and affordability wouldn't be a question.
Revenue has increased. Have you seen Meta's latest earnings? +33% revenue - in this economy.
Affordability is not a question. There is a reason companies like Meta have no issue with their engineers spending $1k/day on tokens. It's just not that much compared to how much they make per employee.
Not every change a developer makes increases revenue, and the changes that do often have a lag time.
> If it was actually productive
They are extremely productive if you use them right. To the point it worries me how clever these pseudo-AI models can get in the next year.
Steelmanning the other side: a counter example would be if competitors use the same tools to achieve the same productivity gains.
That is not true at all. No matter how "productive" a company is means nothing if people aren't buying your product. And using LLMs to be more productive will not convince anyone to buy your product. Human creativity and intuition to make a product that people want to use is what sells. Productivity for productivity's sake doesn't really move the needle at all, and can make things worse.
Yes, my thoughts exactly. Productivity by definition creates things, hopefully valuable things. Is all the extra burn on chatbots worth the cost? Has Uber somehow gotten dramatically more efficient and effective due to this massive budget overrun? Or have they just given people shiny and expensive ways to push the same work around?