We're making a niche B2B application, and this is very much it for us as well.
Our customers are in a cutthroat market with low margins. We can't spend a ton on pre-analysis, redundancies and so on.
Instead we've focused reduced the impact of failures.
We've made it trivial to switch to an older build in case the new one has an issue. Thus if they hit a bug they can almost always work around it by going to an older build.
This of course requires us to be careful about database changes, but that's relatively easy.
You can not. AI though, can be cheap enough to produce that. I wonder what happens if you take a b2b application and let it rewrite with AI to Nuclear Industry/ Aviation standards into a seperate repo. Then on fixes/rewrite the engineers take the "safety aware repository" as inspiration.
What you're describing is almost exactly the opposite of what LLMs are good for. Quickly getting a draft of something roughly like what you want without having to look a bunch of stuff up? Great, go wild. Writing something to a very high standard, with careful attention to specs and possible failure cases, and meticulous following of rules? Antithetical to the way cutting-edge AI works.
Have you tried using an LLM to write code to any kind of standard? I recently spent two hours trying to get GPT 4 to build a fiddly regex and ultimately found a better solution on Stack Overflow. In my experiments it also produced lackluster concurrent code.
You’ve missed the point. Those standards don’t relate at all to writing code, they relate to process, procedure and due diligence - i.e. governance. Those all cost a lot in terms of man hours.
Exactly. Even without learning from those groups, there's a ton of stuff we know we could do to improve the reliability of our product. It's just that it would take way too much development time and our customers wouldn't want to pay for it.
It's like buying a thermometer from Home Depot vs a highly accurate, calibrated lab thermometer. Sometimes you just don't need that quality and it's a waste paying for it.
Yeah, it costs. That, and that people will accept shite software makes it high quality a fight software companies can avoid. Rationally therefore, they do.
Our customers are in a cutthroat market with low margins. We can't spend a ton on pre-analysis, redundancies and so on.
Instead we've focused reduced the impact of failures.
We've made it trivial to switch to an older build in case the new one has an issue. Thus if they hit a bug they can almost always work around it by going to an older build.
This of course requires us to be careful about database changes, but that's relatively easy.