We have two common observations about AI coding. At one end of the spectrum, people say programming is over. We are all now program managers: we decide what to build and delegate the coding to AI. At the other end, people ask, “Where is all the great software AI is delivering?” I believe these opposing views run deep. They reflect the difference between software as an industry and software as a craft. Recall Henry Ford’s assembly line: it frustrated workers but made cars affordable. Much the same is happening with software. You can build a new web app in hours with AI. It will be generic, inexpensive, and often better than what you could craft yourself in the same time. For many, that’s enough: a generic app that is slightly limited and not too polished. Yet many people in the West still build businesses selling carefully designed products atop this generic infrastructure. Things get interesting when AI is used by craftsmen who truly care about the end product. Using AI as a craftsman takes longer to bear fruit because it is harder. Here is how I have used AI in recent months. I start a project and ask AI to sketch a solution. It works. I could stop there, post the code on GitHub, and move on. In a year, I would produce 400 new libraries—the sweatshop model of AI production. Instead, I treat the AI output like a human research assistant’s draft: “Nice proof of concept!” Then I spend weeks mercilessly reviewing and refining the code. Importantly, AI’s greatest value may not be writing code. I use it as a research assistant: “What if I did it this way?” I can test ten designs in parallel and discard them all. That freedom is valuable. I continue until my code far exceeds the state of the art—well above what lazy prompts would produce. This craftsman strategy is bearing fruit. It may lead to a golden age of software. But by nature, it is slower and less visible. It is slower partly because we are still developing the right processes. Few will do this. I roast and grind my own coffee. Most people buy overpriced capsules. My coffee is in a different league, but most don’t know what good coffee tastes like. The same applies to software. Many think Microsoft Teams is good software. If you sell to those customers, simple AI prompting is enough—and if you become a billionaire, good for you. But I predict a lasting market for the kind of software a small team of dedicated craftsmen can produce with AI and other tools. Mark Frauenfelder’s book Made by Hand is relevant in this context. Roasting is a hassle. Why do I do it? Why bother making crazily good software if so-so software is enough to pay the bills? Many people won't like the answer: it is a spiritual issue. Once you have enough to eat, why do you build anything? If I chose to be frugal, I could probably retire today. Eat spaghetti. Scroll the web. Some people will reply that it is all about status competition. But roasting my own coffee does not make more popular with the ladies. If anything, it makes me weird. Yet it also makes me happier. For many of us, the craft is the point. And AI won't change that.

We are introducing EU Inc. To make building and growing a business across the EU faster, simpler, and smarter. 🔸 Start a company in less than 48 hours 🔸 No minimum capital requirement 🔸 Fully online and borderless

Oh wow, a popular GitHub Action (tj-actions/changed-files) was fully compromised. Someone committed a base64-encoded payload that runs a script that in turn prints out encoded secrets… Stay safe out there!

Never once in the quarter of a century I've been building for the web has picking MySQL come up as a regret. Unbelievably solid, no-nonsense tech.

Great news. @_MathAcademy_'s Probability and Statistics course will be launched in time for Christmas. The final list of topics is attached. Just call me Santa Claus. 🎅

Our new textbook Theoretical Foundations of Conformal Prediction is out! Conformal prediction is a a statistical technique that augments ML systems with uncertainty information for safe deployment. This book lays out the core theory. arxiv.org/abs/2411.11824

If I count all forks of LLR (github.com/dirkschumacher/ll…) as active users, then I can happily report that this language is used by at least 14 people🤣

Rails 8.0: #NOBUILD, #NOPAAS, all-in on SQLite as a production database option with jobs, cache, and cable, new authentication generator, and so much more! Final release is out 🎉 rubyonrails.org/2024/11/7/ra…

MA is hiring!

Sign for Europe: eu-inc.org

In praise of mystery ✨ After a successful launch aboard a @SpaceX Falcon Heavy rocket from @NASAKennedy, @EuropaClipper is on its way from our ocean world to another to see if Jupiter's moon Europa has conditions suitable for life: go.nasa.gov/3Ua0OnV

Neovim artfully avoided the "rewrite it in rust" catfish. We were waiting for Zig (harmonious instead of hostile with C/legacy): github.com/neovim/neovim/pul… To join the zig mafia, use nvim in ghostty developing a bun app.

Our primary priority for Ruby on Rails is getting you from 0-1. Once you've become rich beyond belief, you can afford to tackle whatever unique frontier problems you face at that scale. Get the bag first, then worry about how to hold it!

🧟 #ORMS tweeps: is anyone out there using one of these packages? I'd love to pick your 🧠. - Gurobi ML - PySCIPOptML - another ML embedding library I don't know about...

Unsure what people with no kids do all day.

Customers are very good at telling you what they'd add. They're terrible at identifying what should be removed. And you don't end up with a good product just by adding everything. Don't act on customer requests, act on their behalf.

To the ones wondering why their investment process in Europe still cannot be digitalized, when @EU_Commission was preparing directive 2019/1151 to enable more digitalization: