[andy99]

In some sense, devs are now responsible for a P&L the way a business manager would be, but I suspect that nobody is paying enough attention to the P part of it. When you incentivize people to spend as much money as possible but don’t hold them accountable properly for what they actually produce, this is what happens.

[rwmj]

I wonder how it's possible for a developer to assign profit. The article mentions Uber's $1500 limit per developer per month. At work we're using an LLM to analyze Windows crash dumps, which turns out to be quite expensive -- several dollars per dump, and you might analyze many every hour. Others don't use AIs very much. Should those not using so many tokens donate them to the crash dump people? And back to your point, how can we assign a profit to this? Customers love having their crash dumps analyzed quickly, but that's not the same as it being profitable.

[mittensc]

> At work we're using an LLM to analyze Windows crash dumps, which turns out to be quite expensive -- several dollars per dump, and you might analyze many every hour

Is that in any way useful?, how so?, are dumps from optimized builds?

I've found that most of the time I don't even need to open a dump because of regular automation providing all thread callstacks in tickets... That and logs are generally enough...

[rwmj]

I'm not directly involved in the day to day activity around this, but as I understand it, it's about triaging related crashes together and associating them with prior bugs and suggesting fixes, else escalating.

[mittensc]

thanks!

Associating with past bugs is a nice use case

Suggesting fixes seems risky, can lead people on wrong paths and waste time or fixing a sympthom instead of proper root case and waste the bug report?

Grouping is pretty easy without LLMs, just pattern match callstack symbols

Triage, sure, but a human would be able to do that as well in a couple of minutes for free with callstack in tickets, couple of dollars per ticket seems excessive in comparison

[nlpnerd]

https://seldon-ai.com/blog/how-much-of-your-llm-bill-is-just...

[dbuxton]

It is just extremely difficult in most companies to draw a line between a specific feature and an amount of revenue. A lot of engineering has a stochastic type of impact.

(It’s often easier to see what a feature does to reduce costs though)