So much this. People who say ai can’t write code are just using it wrong. You need to break things down to bite size problems and just let it autocomplete a few lines at a time. Increase your productivity like 200%. And don’t get me started about not having to search through a bunch of garbage google results to find the documentation I’m actually looking for.
Not 200 %. Maybe 5-10 %. You still have to read all of it to check for mistakes, which may sometimes take longer than if you would have just written it yourself (with a good autocomplete). The times it makes a mistake you have lost time by using it.
It’s even worse when it just doesn’t work. I cannot even describe how frustrating it is to wait for an auto complete that never comes. Erase the line, try again aaaand nothing. After a few tries you opt write the code manually instead, having wasted time just fiddling with buggy software.
I don’t know about ChatGPT, but Github Copilot can act like an autocomplete. Or you can think of it as a fancier Intellisense. You still have to watch its output as it can make mistakes or hallucinate library function calls and things like that, but it can also be quite good at anticipating what I was going to write and saves me some keystrokes. I’ve also found I can prompt it in a way by writing a comment and it’ll follow up with attempt to fill in code based upon that comment. I’ve certainly found it to be a net time saver.
Well not quite - I use ChatGPT more like to brainstorm ideas and sometimes I’ll paste a whole file or two into the prompt and ask what’s wrong and tell it the issue I’m seeing, it usually gives me the correct answer right away or after clarifying once or twice.
I use copilot for tab completion. Sometimes it finishes a line or two sometimes more. Usually it’s good code if it’s able to read your existing codebase as a reference. bonus points for using an MCP.
Warp terminal for intensive workflows. It’s integrated into your machine and can do whatever like implementing CICD scripts, executing commands, ssh into remote servers set up your infrastructure etc… I’ll use this when I really need the ai to understand my code base as a whole before providing any code or executing commands.
So much this. People who say ai can’t write code are just using it wrong. You need to break things down to bite size problems and just let it autocomplete a few lines at a time. Increase your productivity like 200%. And don’t get me started about not having to search through a bunch of garbage google results to find the documentation I’m actually looking for.
Not 200 %. Maybe 5-10 %. You still have to read all of it to check for mistakes, which may sometimes take longer than if you would have just written it yourself (with a good autocomplete). The times it makes a mistake you have lost time by using it.
It’s even worse when it just doesn’t work. I cannot even describe how frustrating it is to wait for an auto complete that never comes. Erase the line, try again aaaand nothing. After a few tries you opt write the code manually instead, having wasted time just fiddling with buggy software.
It’s laughable to me that people haven’t figured this out.
How? “Hey, ChatGPT, write the thirty-second line of this function?”
I don’t know about ChatGPT, but Github Copilot can act like an autocomplete. Or you can think of it as a fancier Intellisense. You still have to watch its output as it can make mistakes or hallucinate library function calls and things like that, but it can also be quite good at anticipating what I was going to write and saves me some keystrokes. I’ve also found I can prompt it in a way by writing a comment and it’ll follow up with attempt to fill in code based upon that comment. I’ve certainly found it to be a net time saver.
Well not quite - I use ChatGPT more like to brainstorm ideas and sometimes I’ll paste a whole file or two into the prompt and ask what’s wrong and tell it the issue I’m seeing, it usually gives me the correct answer right away or after clarifying once or twice.
I use copilot for tab completion. Sometimes it finishes a line or two sometimes more. Usually it’s good code if it’s able to read your existing codebase as a reference. bonus points for using an MCP.
Warp terminal for intensive workflows. It’s integrated into your machine and can do whatever like implementing CICD scripts, executing commands, ssh into remote servers set up your infrastructure etc… I’ll use this when I really need the ai to understand my code base as a whole before providing any code or executing commands.