The hardest problems are solved most easily by building tools to make the problem obvious. Debugging tools are the most effective projects to vibe-code, hands down.

My talk from #PyConUS last week just hit YouTube! Learn how audio software works in Python in only 30 minutes: youtube.com/watch?v=kpKrsF…

signs this website is doing well: ads from a verified lamp

I just searched for a domain name for a potential new project and found that former coworkers of mine - from 12 (!) years ago - started and folded a company with that name. The internet is so small, sometimes.

balaji-amg.surge.sh/blog/typing-11…

Also, you know, you don’t make a bridge 400% stronger than it needs to be on the basis that, “well, can’t hurt to overdo it.” Yes, it does. It costs money, and time, resources. Engineering is the weighing and managing of these constraints and tradeoffs. This wood is fine.

Working in ML gives one the knowledge to know what’s possible, but not the wisdom to avoid wasting a full afternoon trying to get some obscure, experimental, low-quality research repo running.

A lot of the engineers with the deepest experience that I work with also have an absurdly wide span: everything from memory allocators to CSS selectors. They just like to build cool stuff, and that’s why they picked up so many things.

IME really good software ppl who deeply care find the least use from LLM coding and are often ideologically opposed to it because they like to exert editorial control over every line. slop research coders such as myself don’t care as much and have much larger gains

Anecdote time: I spent 5 minutes using OpenAI Codex while waiting for a bagel this morning. It "fixed" three bugs in my codebases. As soon as I got home, I realized they each introduced new bugs. The real fixes took 10 seconds each when I took a moment to read the code.

macOS sometimes likes telling me how old my laptop is for some reason?

beep boop, let's compute

You know you're in too deep when the solution to your problem appears to lie in a GitHub repo with one commit, one file, and zero comments by someone who hasn't touched GitHub in 8 months.

wedding planning as a software engineer in 2025 means reverse-engineering the links that hotels give you so you save your guests from the dark patterns that hotels use on them when attempting to book in your room block

lack of design signals "I'm too focused on the mission to focus on design, so I'm just going to write pure HTML" but always peek under the hood to find out if that's true or not

i feel like, even though there is a LOT of good content out there, there still is not a good holistic overview of concurrency in python

friends have started turning down $1-2M/year offers to join big AI companies as engineers. three so far this summer all early-30s with 10+ years of big tech experience. all saying they don’t want to be stuck working 80-hour weeks at this stage of their lives. logical, but wild

Imagine explaining to my younger self that I’m struggling at work because my code editor, forked from an open source Microsoft editor written in typed JavaScript that can write code for me from text based prompts, is eating up the 64 GB of RAM on my Mac laptop.

I love it when a plan comes together. Huge congratulations to all of my colleagues around the world who came together to make this product happen! newsroom.spotify.com/2025-08-19/mix…

joshuavaldez.com/the-unbearable…