Just today I got Claude to convert a company’s PDF protocol specification into an actual working python implementation of that protocol. It would have been uncreative drudge work for a human, but I would have absolutely paid a week of junior dev time for it. Instead I wrote it alongside AI and it took me barely more than an hour.
The best part is, I’ve never written any (substantial) python code before.
It would seem you don't care too much about verifying its output or about its correctness. If you did, it wouldn't take you just an hour. I guess you'll let correctness be someone else's problem.
Your wild assumptions and snarky accusations are unnecessary. The library is for me to use; there isn't a "someone else" for me to pass problems onto. I then did what I usually do — start writing real code with it ASAP, because real code is how you find real problems.
I developed the library interactively, one API call at a time, in a manner akin to pair programming. Code quality was significantly better than I'd expect from $2000 worth of a GOOD mid-tier programmer — the code was well written, well organised, and comprehensively annotated. The code wasn't perfect, but a majority of faults had a basis in the underlying documentation being wrong or ambiguous.
The $20/month for Cursor Pro literally justified its cost in less than 10 minutes.
I don't know the OP here, but in my experience a junior dev at an average company would likely not do much more than the AI would. These aren't your grandfather's engineers, after all.
A junior dev wouldn't have produced output of such consistency, and they wouldn't have annotated their code nearly as well. The majority of code was better than I'd expect from a junior, and the comments were better than I'd expect from the majority of people at every skill level.
I have to agree. It's still a bit hit or miss, but the hits are a huge time and money saver especially in refactoring. And unlike what most of the rather demeaning comments in those HN threads state, I am not some 'grunt' doing 'boilerplate work'. I mostly do geometry/math stuff, and the AIs really do know what they're talking about there sometimes. I don't have many peers I can talk to most of the time, and Claude is really helping me gather my thoughts.
That being said, I definitely believe it's only useful for isolated problems. Even with Copilot, I feel like the AIs just lack a bigger context of the projects.
Another thing that helped me was designing an initial prompt that really works for me. I think most people just expect to throw in their issue and get a tailored solution, but that's just not how it works in my experience.
For me, it's allowing me to do things I wouldn't have even attempted before. I'm writing in languages I've never written in before (python) and dealing with stuff I've never dealt with before (multicast UDP). This isn't complicated stuff by any stretch, but AI means I can be highly productive in python without needing to spend any time learning python.
The best part is, I’ve never written any (substantial) python code before.