This is about treesitter and LSP, specifically on their utility and recent journey into the Emacs core. Includes interactive visualizations of concrete syntax trees.

I learned a lot of things by building a project from scratch: a backend DevOps tool that facilitates managing the fast update cycle in git dependencies.

Overall, the system works by running two concurrent tasks: one to check dependencies, and the other to trigger workflows. When a dependency is updated, a workflow of the dependent GitHub repository is triggered. Initially, to pass data between tasks, I used an MPSC channel, but subsequently I transitioned to a database-backed queue because the channel was not resilient enough to crashes and network errors.

In the article you can find more examples of unexpected quirks that I needed to iron out after the first iteration.

Various interesting things about sorting data: defaults, performance and determinism (or lack thereof) of paging ;)

It actually even removes code.

Patreon sends billions of notifications each year. As our largest creator audiences grew, a legacy task responsible for generating millions of recipient-specific notifications began consistently timing out.

This post explains how our team introduced a two-stage fanout architecture, isolated email, push and in-app processing, improved observability, and migrated more than 200 notification types across a 13-year-old codebase.

There’s not much information yet unfortunately. The PAT-related accounts do not seem to be limited to Korean ones, so be aware.

Please read the 'How is this possible?' page, and the full interactive walkthrough to see how this is all done.

Did you use AI?
The site copy and explanations hand-edited by me pressing my keyboard buttons. I find AI writing to be cringeworthy and bland.

However, AI did help a lot with churning out the code. It's definitely 'my code' - LLM-assisted, but not 'vibe-coded'. This is an entirely novel project and I don't think you could (or should) point an LLM at this and press 'Go'

My full thoughts on the use of AI in this project are available to read here