This might help you:

https://archive.jamesaltucher.com/blog/reinventing-yourself/

I am surprised that people pay $12/ month for a single Substack newsletter.

"He wasn't convicted for that". Maybe that's the point. Maybe he should have been.

The AI should be doing the reading, then deciding what to do, then doing it, right? While you are at the beach, or unemployed. That's what Sam says.

> But seems like people are working more and not less with AI.

Overall productivity hasn't increased, has it? At best there are cases of increased per productivity due to layoffs, at worst it's just busywork.

> Somebody needs to care enough.

Why?

On productivity: I feel the baseline for productivity has moved up. As a personal anecdote, I had a startup before with 25+ engineers. Now we are a startup of 2 co-founders and a couple of interns, and if I step back, I feel we can produce a surprising amount of stuff. But producing is just the input side, which brings me to 'care'.

On somebody needs to care enough: I meant that AI agents by design have no intrinsic motivations, so (stating the obvious) they do not really care if the product works or actually solves the user's problem. This puts the onus on the human to care for the problem to really solve it, vs just building something. With increased AI output there are too many things to care about which the AI won't, and I believe that's why people might be working more and not less

I think we are talking about the same thing and reaching wildly different conclusions. If "producing is just the input side" and you still need people to check if the product really solves the user's problems, then I get to conclude that the bottleneck has never been the "generating the code" part of the work, and actual productivity - i.e, delivering things that actually solves the customer's problem - is pretty much the same.

I think we agree on the diagnosis: generating code was never the whole bottleneck. Where we differ is the conclusion. Work is implementation plus verification (specing, testing, checking it actually solves the problem). Pre-AI, implementation was so slow that verification hid inside its schedule - you verified while the next thing was being built. AI collapsed implementation time, so verification is now the exposed bottleneck - and the cheapest way teams absorb that today is more human hours. So: output per person is up, hours up too, and the delivered-value gain is real but smaller than the raw output gain suggests. Which I think explains both our observations.

> Decoupling between layers will be essential!

You then don't need to "break the speed boundary".

"Trite as the gh issue is and surely this is thankless work, the bottom line and reality is that rsync is a cornerstone for a lot of sensitive pipelines".

Maybe don't piss off the maintainer then?

Maintainers aren’t infallible. Could he have been nicer? Sure. But we don’t need to walk on eggshells around maintainers.

That’s stupid and inefficient.

> If we don't even know the ratio between amortized capital expenses and operational costs, outside investor analysis is impossible.

And yet we surely need this data for the IPO? Or are they relying on rule changes on the indexes to force ETFs to buy shares?

The IPOs are months away, potentially 6 months or more. We're in a volatile macro environment. AI companies have all the incentives to not create higher expectations regarding their financial situation a long time before the IPO. Obviously at IPO they will have to disclose their full financial situation.

The market is super hyped anyway for their IPOs. If they raise investors expectations now and things change until the IPO, investors will be disappointed. It's a lose-lose proposition.

The smart play for any company is to keep their cards close to their chest until close to the IPO time.

They are abusing our trust. That's the issue.

It's true though, isn't it.... The question is do they use it?

"Rolling their own seems silly".

But isn't AI going to destroy all current software vendors?? Everybody is going to roll their own?? In fact, AIs will handle all support autonomously?? I mean they can spin up their database if needed?? What more do they need?

Hence the SAAS apocalypse...

Oh wait... this sarcasm will get me targeted by the LessWrong AI god when he/she/it becomes omnipotent....

The sarcasm is neither funny nor well written. Nobody will care.