The fallacy here is believing we already had all the software we were going to use and that AI is now eliminating 90% of the work of creating that. The reality is inverted, we only had a fraction of the software that is now becoming possible and we'll be busy using our new AI tools to create absolutely massive amounts of it over the next years. The ambition level got raised quite a bit recently and that is starting to generate work that can only be done with the support of AI (or an absolutely massive old school development budget).
It's going to require different skills and probably involve a lot more domain experts picking up easy to use AI tools to do things themselves that they previously would have needed specialized programmers for. You get to skip that partially. But you still need to know what you are doing before you can ask for sensible things to get done. Especially when things are mission critical, you kind of want to know stuff works properly and that there's no million $ mistakes lurking anywhere.
Our typical customers would need help with all of that. The amount of times I've had to deal with a customer that had vibe coded anything by themselves remains zero. Just not a thing in the industry. Most of them are still juggling spreadsheets and ERP systems.
> Especially when things are mission critical, you kind of want to know stuff works properly and that there's no million $ mistakes lurking anywhere.
This is what I'm wondering about; things don't change because the company doesn't like change, and the risks of change are very real. So changes either have to be super incremental, or offer such a compelling advantage that they can't be ignored. And AI just doesn't offer the sort of reproducible, reliable results that manufacturing absolutely depends on.
It's just that messing with a company's core manufacturing is something they don't do lightly. They work with multiple shifts of staff that are supposed to work in these environments. People generally don't have a lot of computer skills, so things need to be simple, repeatable, and easy to explain. Any issues with production means cost increases, delays happen, and money is lost.
That being said, these companies are always looking for better ways to do stuff, to eliminate work that is not needed, etc. That's your way in. If there's a demonstrable ROI, most companies get a lot less risk averse.
That used to involve bespoke software integrations. Those are developed at great cost and with some non trivial risk by expensive software agencies. Some of these projects fail and failure is expensive. AI potentially reduces cost and risk here. E.g. a generic SAP integration isn't rocket science to vibe code. We're talking well documented and widely used APIs here. You'd want some oversight and testing here obviously. But it's the type of low level plumbing that traditionally gets outsourced to low wages countries. Using AI here is probably already happening at a large scale.