I’ve just spent a few weeks continually enhancing a script in a language I’m not all that familiar with, exclusively using ChatGPT 4. The experience leaves a LOT to be desired.
The first few prompts are nothing short of amazing. You go from blank page to something that mostly works in a few seconds. Inevitably, though, something needs to change. That’s where things start to go awry.
You’ll get a few changes in, and things will be going well. Then you’ll ask for another change, and the resulting code will eliminate one of your earlier changes. For example, I asked ChatGPT to write a quick python script that does fuzzy matching. I wanted to feed it a list of filenames from a file and have it find the closest match on my hard drive. I asked for a progress bar, which it added. By the time I was done having it generate code, the progress bar had been removed a couple of times, and changed out for a different progress bar at least three times. (On the bright side, I now know of multiple progress bar solutions in Python!)
If you continue on long enough, the “memory” of ChatGPT isn’t sufficient to remember everything you’ve been doing. You get to a point where you need to feed it your script very frequently to give it the context it needs to answer a question or implement a change.
And on top of all that, it doesn’t often implement the best change. In one instance, I wanted it to write a function that would parse a CSV, count up duplicate values in a particular field, and add that value to each row of the CSV. I could tell right away that the first solution was not an efficient way to accomplish the task. I had to question ChatGPT in another prompt about whether it was efficient. (I was soundly impressed that it recognized the problem after I brought it up and gave me something that ended up being quite fast and efficient.)
Moral of the story: you can’t do this effectively without an understanding of computer science.
I’ve just spent a few weeks continually enhancing a script in a language I’m not all that familiar with, exclusively using ChatGPT 4. The experience leaves a LOT to be desired.
The first few prompts are nothing short of amazing. You go from blank page to something that mostly works in a few seconds. Inevitably, though, something needs to change. That’s where things start to go awry.
You’ll get a few changes in, and things will be going well. Then you’ll ask for another change, and the resulting code will eliminate one of your earlier changes. For example, I asked ChatGPT to write a quick python script that does fuzzy matching. I wanted to feed it a list of filenames from a file and have it find the closest match on my hard drive. I asked for a progress bar, which it added. By the time I was done having it generate code, the progress bar had been removed a couple of times, and changed out for a different progress bar at least three times. (On the bright side, I now know of multiple progress bar solutions in Python!)
If you continue on long enough, the “memory” of ChatGPT isn’t sufficient to remember everything you’ve been doing. You get to a point where you need to feed it your script very frequently to give it the context it needs to answer a question or implement a change.
And on top of all that, it doesn’t often implement the best change. In one instance, I wanted it to write a function that would parse a CSV, count up duplicate values in a particular field, and add that value to each row of the CSV. I could tell right away that the first solution was not an efficient way to accomplish the task. I had to question ChatGPT in another prompt about whether it was efficient. (I was soundly impressed that it recognized the problem after I brought it up and gave me something that ended up being quite fast and efficient.)
Moral of the story: you can’t do this effectively without an understanding of computer science.