Comment by globular-toast

It's a couple of hours right now, then another couple of hours "correcting" the AI when it still goes wrong, another couple of hours tweaking the file again, another couple of hours to update when the model changes, another couple of hours when someone writes a new blog post with another method etc.

There's a huge difference between investing time into a deterministic tool like a text editor or programming language and a moving target like "AI".

The difference between programming in Notepad in a language you don't know and using "AI" will be huge. But the difference between being fluent in a language and having a powerful editor/IDE? Minimal at best. I actually think productivity is worse because it tricks you into wasting time via the "just one more roll" (ie. gambling) mentality. Not to mention you're not building that fluency or toolkit for yourself, making you barely more valuable than the "AI" itself.

You say that as if tech hasn't always been a moving target anyway. The skills I spent months learning a specific language and IDE became obsolete with the next job and the next paradigm shift. That's been one of the few consistent themes throughout my career. Hours here and there, spread across months and years, just learning whatever was new. Sometimes, like with Linux, it really paid off. Other times, like PHP, it did, and then fizzled out.

The other thing is, this need for determinism bewilders me. I mean, I get where it comes from, we want nice, predictable reliable machines. But how deterministic does it need to be? If today, it decides to generate code and the variable is called fileName, and tomorrow it's filePath, as long as it's passing tests, what do I care that it's not totally deterministic and the names of the variables it generates are different? as long as it's consistent with existing code, and it passes tests, whats the importance of it being deterministic to a computer science level of rigor? It reminds me about the travelling salesman problem, or the knapsack problem. Both NP hard, but users don't care about that. They just want the computer to tell them something good enough for them to go on about their day. So if a customer comes up to you and offers you a pile of money to solve either one of those problems, do I laugh in their face, knowing damn well I won't be the one to prove that NP = P, or do I explain to them the situation, and build them software that will do the best it can, with however much compute resources they're willing to pay for?