Experimenting with #AI #subagents.
I delegated 4 GitHub issues to parallel subagents. The biggest win wasn't the speed — it was context isolation. Here's how I did it.
Experimenting with #AI #subagents.
I delegated 4 GitHub issues to parallel subagents. The biggest win wasn't the speed — it was context isolation. Here's how I did it.
AI-assisted #genealogy with #ClaudeCode
My son recently came to me to brag about using AI to find our ancestors. While the results were correct, I didn’t learn anything new, as it stopped at my grandparents. I was never very interested in my genealogy, but I decided to see if AI would be a good tool for this. In a little less than one month, I managed to gather more than 600 individuals and get back 12 generations in some branches.
Most developers now use coding assistants. I do too—#Copilot at work, #ClaudeCode at home. As a developer, I prefer not to repeat myself. This post explains why and how to avoid repetition with skills.
So Anthropic employees are using Claude Code to contribute AI-generated code to open source repositories and hiding the fact using their own internal “undercover mode”.
Totally trustworthy people.
(Any open source project that at the very least requires disclosure of AI-authored contributions should immediately ban Anthropic employees on principle.)
Automatic programming always has been a euphemism for programming with a higher-level language than was presently available to the programmer.The "higher-level language" LLMs trade in is English, which Dijkstra has strongly argued makes for a poor programming language. But even if, contra Dijkstra, it turns out LLMs somehow change that equation, we are still stuck with Brooks's argument that higher-level programming languages largely only address accidental complexity. They do not get at the essence of what makes creating software systems difficult.
I realized that if I was writing a program and it didn't always work, I had a choice: I could either fix it, or call it AI.--David Parnas