jchonphoenix

Wasn't this originally HN?

PG hasn't been in the bay for a long time so he doesn't understand what the ecosystem is like anymore.

For example "startups make the best stuff" is just wrong these days. I almost always assume the startup's product today is going to screw you or is hacky, because they prove over and over again they cut corners for growth. Very few startups still take the mentality PG has in his era and now ship half broken hacked stuff.

Much of yc advice is correct. But much of it is also dated as you're noticing

It was likely done by claude

You miss the major factor in your compensation: pricing pressure due to supply/demand.

By removing all the junior engineers, you've fundamentally changed the market forces longer term and most people expect that to negatively impact you in the supply demand curve regardless of whether or not the statements you've made above are true, which they most likely are for senior engineers.

This is CMU so they would be at the bleeding edge just like MIT/Stanford. But I think all the schools are behind today

Zico is Chair of the ML Department at CMU, which arguably has had the largest contribution to foundational ML academia.

OpenAI board member is his least interesting credential

The author misses the forest for the trees. He's accurately articulating the current state of tools he's using but isn't acknowledging or extrapolating the next derivative I.e the rate of improvement of these tools.

That being said, everything is overvalued and a lot of this is ridiculous.

This entire post smells like someone who's salty and trying not to face reality. I might not even disagree entirely with what's being stated here but the framing is just clearly wrong

Anysource.dev is the answer

Data engineering completely automated by a startups technology. This dataset sells for hundreds of thousands a year and can be fully cleansed and prepared from raw data purely with AI.

My guess is the telemetry data.

OAI spends gobs of money on Mercor and Windsurf telemetry gets them similar data. My guess is they saw their Mercor spend hitting close to 1B a year in the next 5 years if they did nothing to curb it

Meta tools are best in class when the requirement is scale. Or that the external tools haven't matured yet

OpenAI initially raised 50m in their institutional round.

1b was a non profit donation, so there wasn't an expectation of returns on that one.