The problem is that organizations are inefficient in such a way that extra output from white collar workers doesn't translate to improved org-wide performance in a positively correlated, linear fashion.

When the org is misaligned, mismanaged, has poor customer feedback loops, bad product market fit, too much bureaucracy, etc etc no amount of AI slop is going to make a meaningful impact on its bottom line. In fact, it will likely do the opposite through combination of exponentially increasing complexity, combined with worker force deskilling, layoffs, and rising token prices. Real bottleneck is and always has been communication & alignment.

It might make the employees _happier_ in the interim though, which, I believe, is what we're predominantly seeing during this AI mania. People fed up with the bullshit jobs of rewriting the same service for the 5th time in 2 years or creating TPS reports weekly just for their manager to throw them directly in the trash are absolutely giddy that they no longer have to do this manually. I think we need to question the economic value of these jobs in the first place, though.

I've worked at big tech prior to LLMs becoming a thing, and consistently saw projects of 20-50 people carried by 2-3 individuals that actually understood what needed to be done. I don't think this ratio will be any better with genAI, and I also don't think that tokenmaxxing has any meaningful correlation with impact. Bullshit jobs (and questionable personal projects) just get done faster now. Yay, I guess.

Correct most people should be fired.

In the long run these highly inefficient firms are going to get destroyed by people who have a vision and can do what 100+ firms are doing and package it together as one solution that is far superior on dimensions that matter to firms.