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...
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
(It’s often easier to see what a feature does to reduce costs though)
I frequently max out my weekly usage, and given this [1], hopefully Codex might give me more milage.
https://x.com/SemiAnalysis_/status/2064815044085318040?s=20
also, codex apparently uses fewer tokens to complete tasks, in part because their tokeniser is about 80% the length of that in tokens for the same string as that of the latest anthropic ones. This might be fable only though.
Sure, if you start at this point, where a good chunk of employees, who never had that ability, can now spend a lot of money at their discretion, that's probably going to be costly at first. Then people will learn from that and set direction adn guardrails.
You spend 3 days making AI do something, and now what, you're suppose to spend 2 days trying to keep up with whatever it's done? That's like if your coworker's projects, every week, were handed to you on Thursday and you're told to finish them up.
No matter how smart you are, the bootstrap of new knowledge is impossible.
So sure, it's easy to turn the spigot off at arbitrary dollar values, but you can't just turn the worker's mindset off.
Workflow is valuable because of how in the flow it is.
It seems like execs these days think that if they're not doing the One Thing Everyone's Doing, they're necessarily missing out, leaving potential revenue on the table, what have you. But the only reason to use AI in a business is if it makes you more money, so if you try it, and it's not doing that...I guess the question is, who are you going to believe, Sam Altman or your lying eyes?
Dare I say the GPU bought today won't be economical in 3-4 years time?
for those who use vim (me) there's also, e.g., this: https://voipnuggets.com/2025/03/30/supercharge-your-vim-edit...
Is this all built in these days so that you can Superpowers a prompt to the point where it will automagically chug along for hours until it’s satisfied it’s completed the end goal?
I run several AI-based products, and I’ve moved almost entirely to agentic coding, so this is a huge concern for me. One thing that has helped in the coding realm is separating planning from execution: I use a stronger, more expensive model for architecture, research, and difficult decisions, then hand the implementation work to cheaper agents where the task is more constrained.
On the product side, I treat token usage and costs like any other production resource. We record usage by request, user, feature, and model, surface it in admin dashboards, and set budgets and hard cutoffs.
Alerts are useful, but automatic limits matter more—especially as a small business guy so a 2 AM loop doesn't bankrupt me :)
It's like the company gave every senior dev a super eager brilliant fellow coder to do their work for them so they can 'do more important things' i.e. Netflix and sleep.
'Yes still working on this ticket' When codex/cc completed it flawlessly last week. The upside is absorbed by the devs knowing they could be soon surplus to requirements.
My concern is that with all the bundling that the model labs are doing the lock-in becomes harder than anticipated to unwind
Discussion then: https://news.ycombinator.com/item?id=48602571
<gets bill>
No wait