I think this is where the future of coding is. It is still useful to be a coder, the more experienced the better. But you will not write or edit a lot of lines anymore. You will organize the codebase in a way AI can handle it, make architectural decisions and organize the workflow around AI doing the actual coding.

The way I currently do this is that I wrote a small python file that I can start with

    llmcode.py /path/to/repo

Which then offers a simple web interface at localhost:8080 where I can select the files to serialize and describe a task.

It then creates a prompt like this:

    Look at the code files below and do the following:

    {task_description}

    Output all files that you need to change in full again,
    including your changes. In the same format as I provide
    the files below, that means each file starts with
    filename: and ends with :filename
    Under no circumstances output any other text, no additional
    infos, no code formatting chars. Only the code in the
    given format.

    Here are the files:

    somefile.py:
    ...code of somefile.py...
    :somefile.py

    someotherfile.py:
    ...code of someotherfile.py...
    :someotherfile.py

    assets/css/somestyles.css:
    ...code of somestyles.css...
    :assets/css/somestyles.css

    etc

Then llmcode.py sends it to an LLM, parses the output and writes the files back to disk.

I then look at the changes via "git diff".

It's quite fascinating. I often only make minor changes before accepting the "pull request" the llm made. Sometimes I have to make no changes at all.