>What matters is the outcome, not the effort >At certain companies the scale could be enormous The latter is true and I think the most legitimate reason for w

>What matters is the outcome, not the effort >At certain companies the scale could be enormous The latter is true and I think the most legitimate reason for working at big companies. I should specify in the first they also accomplish little and affect very little. Things like internal tools that went nowhere, running basic ETL scripts, things like updating financial trade systems to comply with some new regulation. And this at a pretty slow pace. My meaning about Nvidia and Meta VR is how people who didn't create value got enormously wealthy anyway. In Nvidia's case, traditional GPU teams (which I suspect received most of the benefit because they've vested the longest and made up most of Nvidia's pre AI boom) got hugely rewarded by data center GPUs, which they played little role in. Conversely Meta's VR team still got paid really well (their stock is even up because of AI hype, despite VR losses) despite their failure. So you have these systems where even if you fail or don't play any role in success, you're still paid enormously well. This is because companies capture the value, then distribute in their very imperfect ways. You're right that the valid reason for this is that tech companies act as risk absorbing entities by paying people to take high risk bets. But the necessary condition for these are 1) Hiring really good people (not just intelligent, but really motivated, curious, visionary etc) 2) A culture which promotes that The on the ground reality of 1) is that it's a huge mess. The system has turned into a giant game. There are entire paid courses advertised to get a job in MAANG. The average entrant to MAANG spends six to eight months somersaulting through leetcode questions, making LinkedIn/Twitter/YouTube clones, doing interview prep, etc etc. Many causes for this, including the bureaucratization of tech companies, massive supply of fresh grads, global economic disparities, etc. It's no longer the days when nerds, hackers and other thinkers drifted together. 2) Because of FOMO, AI hype and frankly general lack of vision from many tech CEOs, it's just a mess. Anything AI is thrown piles of money at (hence the slew of ridiculous AI products). Everything else is under heavy pressure to AI-ify. I've heard from people inside Google has really ended that kind of research culture that produced all the great inventions. There are still great people and teams but increasingly isolated.