Retrospectiva #9
This month's Retrospectiva comes a little later than usual. The whole house got sick battling the flu the past couple weeks. Mixed with a small heatwave here in Copenhagen, means summer hasn't blessed us like we expected. At least not yet.
Now that I'm feeling a bit better, I finally managed to get some writing in. Let's get to it.
Using
GLM-5.2: Finally. An open-weights model that competes with the big frontier models. For the past weeks I've been using GLM-5.2 extensively. Through OpenCode Go it starts at 5 USD/month. It's different than using your GPT 5.5 or Fable, but it feels good in the open-source way. I urge you to take it for a spin. It costs about one-fourth of what Fable costs. And it deals with 99% of issues Fable does.
Pi Stats: You probably know by now that I'm a big fan of the Pi harness. If you like Claude Code better, that's fine - enjoy yourself. One issue with Pi is that it's hard to know exactly how much you're spending. I discovered this little application called Pi Stats, which gives me a widget in my menu bar that shows me exactly how much I've spent and on what. Even though I still pay for a fixed plan every month, it's still important to know (in terms of real value) what's going where.
Lazygit: We write less code, but we are accountable for more. Some of it is not worth looking at — but the important bits are. For the past few months I've experimented with a lot of "code diff viewers". I need somewhere I can review the changes the agent has made, and direct it in case anything goes wrong or weird. I've tried Hunk (and even contributed a couple of PRs: #310, #347), and codediff.nvim in Neovim, which is what my <space>d+d mapping calls. But lazygit paired with difftastic has been hard to beat. Fast to iterate and great diff highlighting.
Sofascore: I like watching sports. Not all sports, not all the time. But when I do (surprise), I like looking at the data. Sofascore is the app that gives me all of this - in a way I love. Who plays where? Who used to play where? When you're not 15 and playing FIFA extensively - it's hard to keep up. This team out of Croatia has built an incredible app!
Reading
Deep Learning for Biology: I finished this one over 2-3 weeks. I recommend it. A great read in an area where there's much left to do!
Reconstructing the Mind's Eye: Some wild research out of Princeton that shows how they reconstruct images from brain activity. Yes. You heard that right.
Scaling Laws, Carefully - Lilian Weng: What is the ideal amount of data given a certain model size? Given a certain compute budget? And vice versa? These are just some of the questions researchers have been asking themselves. Lilian writes about them beautifully.
Inference cost at scale with napkin math: A fast and short reference on how to think about serving models on GPUs. If you wanted to serve GLM-5.2 to multiple users, what would that cost?
Investing with Agents - Lon Riesberg: A very fun read from Lon Riesberg (creator of the awesome Data Elixir newsletter) about using LLMs to make investments in the stock market.
Listening
Not the most inspiring month musically. Being sick means less running, which means less listening.
Machine Learning Street Talk: One of my favourite podcasts about Machine Learning/Deep Learning/AI. You should give it a listen.
Skate Muzik: Listen to SADE - Worldwide FM: I mean - Sade. Do I need to expand?
Watching
World Cup 2026: Norway just eliminated Brazil. Morocco eliminated Canada. Portugal drew with Congo and is playing Spain today. I'm not a sports fanatic, but I come from a place where football is very close to religion.
Western States: When I can't run, I watch other people run. This year's Western States 100 miler was an exciting one to watch. Even though I was rooting for Hans Troyer to win this one, Vincent Bouillard made an amazing run! Record broken, again!