Version 0.29.3 of hica is out and the core is getting pretty stable. I wanted to explore whether hica could be used to write a small Lisp, as a way to stress-test the hica compiler: closures, recursive data structures, lexical scoping, higher-order functions.
Read more...hica has inline test blocks. They sit right next to your functions: no extra test files, no additional imports and no framework.
Run hica test and you’re done, that’s it!
In my post about cloning ls in Koka I mentioned wanting to build a small language that transpiles to Koka. That idea has become hica!
Read more...In a previous post, I introduced Koka and why I started porting ls to it. But I never wrote about the actual backstory.
In a previous post, I introduced the Intent Log, a way to capture the why alongside the what during development. The Intent Log targets and solves a piece of the comprehension problem. But there’s a related problem it didn’t address: the safety problem.
Read more...In previous posts, I’ve talked about the Comprehension Crisis: the risk that as we move faster, especially with AI agents, we lose the “why” behind our code. A git diff tells you what changed. It says nothing about what was tried and rejected. It’s a record of the result, but it deletes the tries and struggles.
I like to explore different programming languages, and I often try them out but most of them ends up as a “Hello World” in a folder I never reopen, digital fossils of a Saturday afternoon curiosity… My actual day-to-day has been settled for a while: Kotlin when I’m building for the web, Rust when I need a CLI tool. I do think about them a lot, but their syntax, semantics, and functionality don’t tickle me the same way anymore.
Read more...When discussing Trunk-Based Development (TBD), we often get bogged down in the mechanics: the branching strategy, the CI speed, or the revert logic. But as a colleague recently pointed out to me, moving away from Pull Requests (PRs) is a “drastic change” that impacts more than just Git history. It impacts the social fabric of the team.
Read more...Trunk-Based Development is designed for speed. It removes waiting and keeps integration continuous. Code moves to the trunk quickly, often within minutes.
Read more...When we talk about the current AI surge, the conversation almost always centres on output.
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