Before the holidays I spent a few weeks overhauling my development environment after giving Omarchy a shot and realizing what I was missing out on when it comes to Locking into the Flow State^TM. Now that I’m coming back to everything after a couple weeks of bumming around Thailand and not touching my computer, I’m quite chuffed with where I left things, and I figured I’d share my renewed appreciation with you, dear reader.

So in Part 1, I was pretty enthusiastic about managed Kubernetes. I’d just spun up a DigitalOcean cluster and deployed Temporal with a handful of commands. Mission accomplished, right?

Real-time payment verification for Solana with NATS, SSE, and Temporal.

I’ll walk you through my experience building comments into my Hugo blog with Bluesky.

A new take on affiliate marketing and authentic online advertising.

Back again! I came across an interesting YouTube video about DuckLake. If you want to know about DuckLake, watch/read that content; I’m not going to regurgitate it here (I simply cannot do it justice). The gist can be summarized by this snippet from the manifesto “Once a database has entered the Lakehouse stack anyway, it makes an insane amount of sense to also use it for managing the rest of the table metadata! "

It’s 2025 and there are at least that many ways to manage Python dependencies. This short blog post will cover the two approaches I recommend for most use cases.

I came across this post by Xuanwo about starting a link blog in the spirit of Simon Willison’s post here. This is pretty close to what I’m striving for here, and it spurred me to write up some snippets about how I’ve gotten started with Simon’s amazing tools: llm, datasette, and sqlite-utils (and a few helpers I’ll mention below).

Ok, everyone’s doing posts on the uv shebang trick so I have to, too. But no actually I really do want to cover this killer feature of uv because it finally gives us the python “scripts” that we were promised.

Mastering Multi-Label Classification in Python with Scikit-Learn

Welcome back! Today, we’re diving into multi-label classification.