Comment on AI agents wrong ~70% of time: Carnegie Mellon study
zbyte64@awful.systems 3 days agoLiterally the opposite experience when I helped material scientists with their R&D. Breaking in production would mean people who get paid 2x more than me are suddenly unable to do their job. But then again, our requirements made sense because we would literally look at a manual process to automate with the engineers.
MangoCats@feddit.it 3 days ago
Yeah, sometimes the requirements write themselves and in those cases successful execution is “on the critical path.”
Unfortunately, our requirements are filtered from our paying customers through an ever rotating cast of Marketing and Sales characters who, nominally, are our direct customers so we make product for them - but they rarely have any clear or consistent vision of what they want, but they know they want new stuff - that’s for sure.
zbyte64@awful.systems 3 days ago
When requirements are “Whatever” then by all means use the “Whatever” machine: eev.ee/blog/2025/07/03/the-rise-of-whatever/
And then look for a better gig because such an environment is going to be toxic to your skill set. The more exacting the shop, the better they pay.
MangoCats@feddit.it 3 days ago
That hasn’t been my experience, but it sounds like good advice anyway. My experience has been that the more profitable the parent company, the better the job security and the better the pay too. Once “in,” tune in to the culture and align with the people at your level and above who seem like they’ll be sticking around long term. If the company isn’t financially secure, all bets are off and you should be seeking, and taking, a better offer when you can find one.
I knocked around startups for 12/22 years (depending on how you characterize that one 12 year gig that ended with everybody laid off…) The pay was good enough, but job security just wasn’t on the menu. Finally, one got bought by a big fish and I’ve been in the belly of the beast for 11 years now.