[pzs]

Related question: how do we resolve the problem that we sign a blank cheque for the autonomous agents to use however many tokens they deem necessary to respond to your request? The analogy from team management: you don't just ask someone in your team to look into something only to realize three weeks later (in the absence of any updates) that they got nowhere with a problem that you expected to take less than a day to solve.

EDIT: fixed typo

[rco8786]

We'll have to solve for that sometime soon-ish I think. Claude Code has at least some sort of token estimation built-in to it now. I asked it to kick off a large agent team (~100 agents) to rewrite a bunch of SQL queries, one per agent. It did the first 10 or so, then reported back that it would cost too much to do it this way...so it "took the reins" without my permission and tried to convert each query using only the main agent and abandoned the teams. The results were bad.

But in any case, we're definitely coming up on the need for that.

[pjc50]

> blank cheque

The Bing AI summary tells me that AI companies invested $202.3 billion in AI last year. Users are going to have to pay that back at some point. This is going to be even worse as a cost control situation than AWS.

[lossyalgo]

Didn't you hear? Ads are coming! (well not to Claude, because I guess they plan to somehow get unlimited SV funding?!)

[thephyber]

> Users are going to have to pay that back at some point.

That’s not how VC investments work. Just because something costs a lot to build doesn’t mean that anyone will pay for it. I’m pretty sure I haven’t worked for any startup that ever returned a profit to its investors.

I suspect you are right in that inference costs currently seem underpriced so users will get nickel-and-dinked of a while until the providers leverage a better margin per user.

Some of the players are aiming for AGI. If they hit that goal, the cost is easily worth it. The remaining players are trying to capture market share and build a moat where none currently exists.

[Kye]

An AI product manager agent trained on all the experience of product managers setting budgets for features and holding teams to it. Am I joking? I do not know.

[peab]

This seems pretty in line with how you’d manage a human - you give it a time constraint. a human isn't guaranteed to fix a problem either, and humans are paid by time