Our company develops software for medical devices. Risk assessment is everything, and we currently do “You can use AI, but you are responsible that the result works and is correct” and “You can use it, but do not input any company secrets, confidential data, medical records, or things like passwords and security-relevant data”.

I guess the difference is we’re too busy making things and we don’t have the time to brag about AI on social media? Also we’re small and don’t have the reach anyway.

I think this will depend on the industry. Slow vs fast moving, regulated vs not, whether someone depends on your API or not, etc.

But regardless, having had to deal with some legacy code written 10 years ago by someone who isn’t working at the company anymore, I would take an outdated spec over none at all. At least then I know what people intended back then, what they cared about, what they had and hadn’t considered. As long as the spec is written by a human, that information is surely valuable.

You end up with a nice spec that you wouldn’t have had otherwise? That has value even if you discard all the LLM-generated code.

I think experienced engineers are able to go straight from a vague requirement to an implementation without that intermediate step, and that power is easy to abuse. We build an implicit spec on our head, which gets translated to code on the fly, and then gets forgotten.

Not defending the LLM technology, but i do think this is one of the upside.