41–50 of 56 posts
I have made 2 iphone apps in the past week. I have never before been able to finish an app as i would run into some insurmountable issue and lose interest. The apps are simple but functional. It has really made me excited about doing lots of things that I could never get over the competence hump of doing previously.
I've been able to use phind + Co-pilot to learn python, build and deploy a FastAPI service on the OpenAPI spec, without really knowing any of those things. Just ask GPT-4 how FastAPI works, how OpenAPI works, and ask it to format and write your YAML for you. It's an amazing TA — better than any I've had in undergrad, and way better than office hours, where your prof don't really care and wants to go back to their res…
It sounds like these sorts of tools are making it easier to get started with new ideas, but I'm intrigued to see what long-term maintenance is going to look like.
In my 20+ year career I've still yet to see the myth of a "10x developer" as a reality. It just doesn't exist.
I'm no genius, not even close, but in my math classes, I did so many practice problems related to a subject that after a while I was able to solve some problems in my head without having to write anything down. Super programers aren't necessarily geniuses but they can use their brain to a greater extent before they start programming. I suspect.
Learning programming languages and writing the trivial bits doesn't describe the hard part of programming: domain knowledge and skillfully translating complex business requirements into working code.
If you're just copying someone else's code, whether from StackOverflow or an LLM, you haven't made yourself a 10x developer. You may have found a shortcut through the boilerplate and repetitive code that occurs across many applications, but have you learned anything? Do you understand the code? Could you write it yourself? Using a forklift doesn't make me a 10x weight lifter. Finishing a paint-by-numbers canvas doesn…
Since LLMs are trained, by their training, and I guess by your prompts (per session at least?), the only participant progressing toward 10X status would be the LLM.
I pay for ChatGPT-4. It's helping me program noticeably better and much faster, even with mid-sized projects involving many files. This is the process that I follow: - I write a system prompt with a succinct description of what I want to implement: "X is an online app that does Y, with these features: ..." I try to be exhaustive, and I write as I would if I were describing what I want to do to a very proficient progr…
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- It gave me the complete code for a Go API using JSON, with handler and routing, using a map to hold the data
- I asked it to switch to a website and it gave me the same code, with the route adjusted and the rendering returning HTML to view the books
- I said I needed a SQLite back-end and it updated the code to fetch from a database, including stuff to open the connection
- I asked it to seed the database with some random data and it added a method to do that
- I asked it for a page to add a book and it gave me the full code back with a route, handler, database code, and form handling logic to do add a book
- I said I needed the option to delete any book and it gave me updated HTML with a small form tag and delete button for every book in the item list, with code to delete the right book when a button is clicked
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I'm not exaggerating when I say that each of the above was literally a single request. I pasted the code returned into a file and ran it and in each case it built and worked.
At only one stage did it get something wrong. I never kept the prompts/code as I was experimenting, but basically it had an off-by-one error in a loop where it did less than or equals to rather than less than. I described the problem (one prompt) and it "worked it out" and gave me the code back with the line fixed.
So that is 6 prompts plus an extra one for the bug, and the result was a working (trivial) site written in Go with a database back-end.
The other main use I've had is pasting in a screen or two's worth of existing Python code. No questions, just the code. It explained what the code did (including a nuance I'd missed) and proactively pointed out a bug I hadn't seen.
It was incredible to see, then it was worrying (am I needed any more?), then reassuring when I realised this was great for getting started with green-field stuff or iterating over small stuff, but less so with big-picture stuff on a large codebase.
I pay for ChatGPT-4. It's helping me program noticeably better and much faster, even with mid-sized projects involving many files. This is the process that I follow: - I write a system prompt with a succinct description of what I want to implement: "X is an online app that does Y, with these features: ..." I try to be exhaustive, and I write as I would if I were describing what I want to do to a very proficient progr…
And would you say this process saves you time? Instead of traditional programming? Or do you find other upsides to it?