[cdf]

AI code assistants are amazing when you start from zero and just need a 80% working prototype. But once you start trying to refine the product from there, that's where the automation gets counterproductive. If you can exactly specify the problem, eg "Password input crashes when the password has an apostrophe", AI can probably fix it. But if the bug report comes in as "Password input randomly crashes", I will be very surprised if AI can figure out why and fix it. Where a human wrote the code, he or she may figure out why fairly quickly. Now, if you want a human who didnt write the code to understand the AI generated code, it may take a lot longer. In fact, in all likelihood, the AI assisted products are likely to be buggier and stay so longer, esp if companies start to think they can fire the senior devs and hire less skilled devs and fill the gap with AI. At some point, the pendulum will swing back, and companies will be chasing devs again.

[bruce511]

It's certainly going to be fun seeing this all play out over the next 10 years.

In some ways it's like taking over a project written by someone else that's "80% done". You're locked into their design, get to analyze all that code 1 bug report at a time, get frustrated by obvious mistakes, confused (and mislead) when they relied on some clever side effect.

The quality of life in this maintainence mode depends enormously on the quality of the original coder. "Why did you choose this over that?" Is a common question I have for earlier devs. The AI answer is the least satisfying "it seemed like a good probability at the time".

IME writing the app from scratch to "done" is 10% of the lifecycle of the code. It's the other 90%, spanning over decades, where the quality (or lack thereof) reveals itself.

Personally I'm finding AI useful as a tool. Would I want to be the human fixing AI bugs? (From human bug reports which are pretty vague?) I'm not so sure about that.