I feel like this is only true of internal or enterprise software where switching is expensive. For business to consumer, the impact of bugs can cause a company to go under or at least become a zombie. For any type of company, the thread of a competitor is high and can cause your company to stagnant and slowly go under or bleed and rapidly go under.

There is a real impact to a high amount of bugs, it just doesn’t happen in one quarter. It happens over years and results in higher stress foe the developers. A stagnating company doesn’t hire. It doesn’t give raises and slashes benefits. A lot of terrible things happen before a company goes under. We can watch Twitter speed running this.

I wasn’t talking about rewriting an existing system either. I’m talking about adding to a system. In order to do that effectively, you need to understand the system as it stands and consider how any requirement could clash or be impossible with the current set of requirements. This is why I bring up the AI needing to pull a set of requirements from the existing code. You cannot add requirements without knowing the requirements that already exist.

I think that hallucination is still a massive issue. I don’t even like to call it hallucination because what it really is bad guesses. We should never forget that all any AI does is guess. It doesn’t reason about anything or connect information together. AI will hold contradictory positions because of this.

Currently we have no way to make an AI declare that it just doesn’t know or even very often ask for more information in order to make a decision because the method of training an AI is literally guess and check.

For that reason, I don’t think that AI will ever be the tool for the job when it comes to any kind of requirements gathering. I mean I guess you could, but I always run the risk of being like that lawyer who had made up cases in this result. AI made things up because all it does it make its best guess and it doesn’t care I’d that guess is grounded in much of anything at all.

I feel like AI would fall down even harder here. A lot of long running applications have “secret” rules in them that developers have as either tribal knowledge or they have to reas the code and see is the case. Will AI be sophisticated enough to read a massive repo probably dependent on several others and have a realistic understanding of the requirements inherent in that code system? Because that’s what we pay senior devs to be good at quickly figuring out. I find myself skeptical that AI will be able to do that in a trustworthy way with how it “hallucinates” now and doesn’t have the concept that it just doesn’t know sometimes. If a developer has to spend time checking the AI’s assertions about the rules, is that actually going to be faster than just keeping them in their mind or doing the research themselves?

Well… yes. That was the point made in the article. Validating the email address doesn’t do anything. The easiest way is to just sent a link to the entered address and see if the user can click it.

I don’t think I’ve ever had a working definition of a business rule beyond what feels right intuitively. I’m going to carry this forth with me.

Perhaps you’ve been reading this with mounting frustration: How about validating the address according to the SMTP spec?

Indeed, that sounds like something one should do, but turns out to be rarely necessary. As already outlined, users can easily supply a bogus address like foo@bar.com. It’s valid according to the spec, and so what? How does that information help you?

I feel like this is the difference between an academic and a professional. One is trying to do it provably right and the other is trying to satisfy a need with limited resources.