There are as many ways to use LLMs to write code as there are engineers experimenting with them. I love reading about LLM workflows, picking up tips, and trying to streamline my own setup.
I’ve already linked to Simon Willison’s Here’s how I use LLMs to help me write code, but I’ll start with it again. Simon describes using LLMs to write code as difficult and unintuitive which I agree with, especially when I was just getting started. His post then includes a bullet point list of tips.
An older post that I just came across is How I use LLMs by Karen Sharma. This one focuses on using Aider to write and run code. As someone who used to spend almost all of my time in a terminal, I can appreciate this workflow. Aider is very powerful. If I was still spending all my dev time in tmux and vim, I can definitely see myself using something like this.
While you’re at Karen’s blog, check out Cleaning up Notes with LLM. He wrote a Python script using LLM to clean up Obsidian files. Not only is this a great example of LLM use it’s also something that I, as an Obsidian user, could run on my own files to generate some better tags and categories.
Next, up Harper Reed shares My LLM codegen workflow atm. I appreciate the fact that he separated greenfield from legacy code. Many people focus on using LLMs for greenfield, but as an engineer at a large corporation most of my time is spent working on existing code.
Harper’s workflow for greenfield development is really interesting. He uses one LLM for planning. This generates a prompt_plan.md and a todo.md checklist. He then feeds those files to another LLM either directly to something like Claude or using Aider. For non-greenfield he uses a set of mise tasks to get context and feed it to the LLM.
Harper followed up the original workflow post with Basic Claude Code. The workflow is similar to the previous post, but it uses Claude Code instead of Aider. Claude Code opens the generated files and handles everything that needs to be done.
As for me, I’ve been trying to follow An LLM Codegen Hero’s Journey. I’m currently using GPT-4 through Copilot in Visual Studio Code. Having an employer provide free access to all the tools is really nice. For most of my work I’m using autocomplete, but I’m trying to let Copilot do more. I guess that puts me somewhere around step 3.
I’ve spent a good chunk of time working on instruction files for VS Code. This improves Copilot’s ability to make changes to our existing code. An interesting trick is to have Copilot enhance your instruction file using what it knows about your application. I was able to catch and correct some misunderstandings which made Copilot that much better.
If you have an interesting workflow or a link to someone else’s workflow, please share it with me on Bluesky. We’re all still learning and sharing is caring.