Last week I used ChatGPT for the first time for a real world task at work. It was a self-contained lambda function to perform some admin tasks, so it seemed like an ideal fit. Although the experience was good, it's far from the end of programmers. This was my experience:

* Although ChatGPT is pretty good at generating code, it kept making simple mistakes such as calling non-existing APIs or introducing bugs. Some of them it could fix itself, some I had to fix.

* The code provided worked well for the "happy path" but failed miserably for some corner cases. I had to fix that manually.

* The code was working, but I wouldn't consider it production ready. It required some cleanup, unit tests, etc. Again, some of this with ChatGPT, some without.

* Not to mention that I was the one with the knowledge about the domain, what problem to solve, a vague idea of how...

Not to pick on OP but extracting a few seconds of video from a file is a pretty straightforward task, you can essentially do it with a bash one liner [1]. My biggest question is how ChatGPT performs with a large codebase, contributed over time by different authors, with complex domain logic and layers of abstraction.

I also had a brief existential crisis, but I just shrugged it off and got back to work.

[1] https://askubuntu.com/questions/59383/extract-part-of-a-vide...