> Please don't post insinuations about astroturfing, shilling, brigading, foreign agents, and the like. It degrades discussion and is usually mistaken. If you're worried about abuse, email [email protected] and we'll look at the data.
This issue does not come from the coding assistant. In fact, humans will occasionally do the exact same thing as long as their tools have enough permissions to deploy to both local and prod from the same environment.
Fix it by separating the tools (different non-interconnected VMs, etc for dev/qa/preprod/prod environments) and the permissions (different accounts, sessions, tokens, etc for the run/debug/test/deploy loops).
Indeed, the more accurate way to say it is that people in the US don't care enough about mass school shootings to do something about it besides thought and prayers.
Well in addition to what you wrote, the marketing manager ALSO wasn't tracking any ad-related marketing performance indicator (CTR, CR, etc.) in any measurable way for very long periods of time... or they would have caught it almost immediately ("wow ad spend, CTR and CR have all suddenly gone down to 0/0% and have been staying there for days on all our campaigns! What's up with that?").
His team is basically him and two other humans, powering an ambitious well-known project so successful an industry titan ended up acquihiring him/them. That's pretty lean, no?
Well, for starters the program you wrote is wrong (very unreliable) 100% of the time (very predictable)... so you just got your answer I guess.
In any case, most -if not nearly all- of the top-100 LLM will answer your prompt with some code that does what you intended the first program to do. Only they'll actually code it properly of course.
> Are LLMs that super reliable in their output already with all the guardrails around?
Well, what is your definition of "super reliable in the output", and is it a quantifiable/measurable target or just a feeling?
Is it "more than humans", "more than senior developers", "almost perfect", "perfect"?
> It might behave differently than specified and a human is required to validate every output carefully or else.
Sure, just like meatbag developers. All the security flaws AI finds today were introduced years/decades ago by humans and haven't been found (that we know) by humans in ages.