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 fo

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 programmer who needs to understand the problem and the solution. I save this to a prompts/0-system.txt file that will be part of the project. - I design an architecture and define the general boundary conditions. I may ask ChatGPT for opinions, but at this stage, it's mostly based on experience. I add it to the system prompt. - I write a description of the first chunk of functionality that I want to implement, usually a set of functions or a class, at the individual file level. For example, prompts/1-dal.txt. - I (actually ChatGPT) wrote a very simple recursive cat script (https://github.com/juanre/catprompt https://github.com/juanre/catprompt) that combines several files into a single prompt (a file can include other files, etc). I add a line to prompt/1-dal.txt pointing to the system prompt, and use catprompt to create a combined prompt that will include the overall description and the specifics of the functionality I am after. - I give this prompt to ChatGPT, and it produces the code. It's typically perfectly fine. I add it to the project, for example, as dal.py, review, and fix whatever may need fixing. - I ask ChatGPT to create tests in the same session. This also tends to work fine. - Then I move to the next piece of functionality, in a new session. I write another description, in another file, including the system prompt and usually the code already created. The prompts remain: they become a description of the code (and of my intentions) for other programmers, and they can help ChatGPT write documentation as well. I enjoy programming like this. The effort I make in writing concise descriptions helps me think more clearly. I used to love literate programming back in the 90s, and this feels very much like it. Knuth described it thus: "Let us change our traditional attitude to the construction of programs: Instead of imagining that our main task is to instruct a computer what to do, let us concentrate rather on explaining to human beings what we want a computer to do." Replace "human beings" with LLMs, and I think that's where we are now.