I’m on vacation, so I’m getting some time to do things that interest me in between time spent with family and recharging. As part of that, I wanted to write a blog on turmoil and how to use it for testing, and I’ve ended up yak-shaving my way into making a preprocessor for mdBook to compile examples that use external dependencies. I say making instead of writing, because I prompted my way to a solution.

This took me all of 8:00am to 9:30am today to get a working solution. This feels very much in a similar vein to Marc Brooker’s experience with gen AI coding tools. It’s great for small, greenfield tasks where you want a solution, but don’t have the time to dive into all of the weeds yourself.

Here I was using Claude 3.5 Sonnet to iterate. I’ve added the chatbot log to the repo to keep a record of what it was like to actually iterate and reach the solution. There’s a few things I need to do first, but hopefully I’ll be able to share it soon.

The code itself isn’t particularly long, and it’s mostly glue that’s supported by incredible open source projects (mdBook and the whole Rust ecosystem). However, I still find it super impressive that this is where we are at. It feels like a step change in tooling. I’m having more and more of these moments when it comes to reaching to LLMs to help me fill a gap in my available tools.

Long term, would I blindly use this crate? No. I think I would go through the code with a line by line review before publishing, add some TODOs and make notes of the sketchier parts that are likely to bite you. But to get a solution off the ground in no time at all, it’s awesome.

Now I can get back to the blog writing I actually meant to do.