Writing type params with <> (e.g. List<Int>) seems the most natural to me: probably because I encountered that syntax first.
Between C++, Java and TypeScript I think it's the most common too.
List[Int] seems to be next most common (Scala, Python) but TIL Gleam uses List(Int)!
Agentic programming workflows rather remind me of genetic programming. The agent has a validation step that looks like a fitness function, and both run iterative trials.
I'm still not sure whether a language should include a "kitchen sink linter" like Rust's clippy or have a package oriented "thousand flowers bloom" linter like eslint for JS and TS.
Clippy is delightful out of the box but eslint makes it so easy to have project specific lints.
Is there a good term for "after using this feature we realised that the best design is different from the current design"?
In casual conversation I generally hear "bug" but there was nothing wrong with the original implementation.
I'm super impressed by how many lint rules can be implemented with just eslint's no-restricted-syntax and selectors. Example:
{
selector: "ExportNamedDeclaration[declaration=null][source=null]",
message: "Add `export` directly to the function instead of a block export."
}
There's something pleasingly self-referential about configuring an agent by talking to it.
> Remember that [fact about data formats].
Agent: Noted.
... realise nothing happened ...
> Write to your rules file that when I say "remember", I want you to write to the rules file.
Should lint suppressions be first class syntax or comments?
Adding a proper metadata system (e.g. Clojure or Rust) is a big design space but it's clear which expressions are affected.
Comments are much easier to implement but it's easy for users to get them wrong.
Thoughts?
I enjoyed this article about personal project programming, but I particularly liked this definition:
"Production code has a phone number to call when it breaks"
hannahilea.com/blog/housepl...
Looks great!
Have you considered reducing the size of the images? E.g. highly-expressive-macros.png is nearly 1 MiB on its own and I can see the images gradually load on my current limited wifi.
One fun way of testing new AI models: take an existing codebase you have and just ask them to "review it and fix bugs".
In principle this should find more issues over time as models get smarter. I've found a few bugs this way at least.
Cleaned up an old git repo of Ansible playbooks and it's amazing how much is just Docker now.
Docker handles process supervision, centralises logging, and containers coexist without issues. It's nice when things get simpler.
After further playing with my LLM project, I'm surprised how hard it is to tune with system prompts.
My agent kept saying "obviously" even though my prompt said "helpful, professional". Eventually I found that a "courteous" prompt gets "of course" which is better but not ideal.
I've been tinkering with an LLM interface with my calendar and it's really nice to use.
"Delete my April trip" is a lot less fiddly than opening calendar, switching to the month view, scrolling to April and so on.
I should probably build an undo as well though.
Today I learnt about "bypass charging", a phone feature where it can run directly off the mains without using the battery at all. No battery charging, less heat, less battery wear. Nifty.
www.androidauthority.com/phones-with-...
I'm considering using WebP more: for example, my websites would load faster and browsers have supported it since 2020: caniuse.com/webp
That said, GitHub just added support in August 2025, so I suspect I'd still find use cases that don't work yet: github.blog/changelog/20...
Test code is total: we require it to always terminate or it's a failure! It also typically has 100% line and branch coverage.
I feel way less nervous about refactoring tests, you can always just run them.
I certainly see the appeal of an LLM system with full context and tool use (OpenClaw), but the lethal trifecta puts me off deploying it.
I do like the idea of an agent with a heartbeat though. A bunch of nice cron-style workflows can be built on top.
Date picker showing today
Date of birth pickers are a surprisingly nuanced UI problem.
What do you pick as the initial value? How do you allow users to easily move by large amounts (years) as well as small amounts (the exact day)?
Defaulting to today and even allowing future dates is funny though.
I've written a website that archives all my posts/tweets/toots/skeets across different microblogging platforms!
It's fun to be able to see similar posts that I wrote at completely different times. It also lets me edit links that have bitrotted.
miniblog.wilfred.me.uk
When I moved back to the UK, I ordered SIMs for both myself and my wife. We ended up with consecutive numbers!
It's really convenient sometimes.
An AI benchmark website that tries to run comparable benchmarks regularly to discover when LLM performance is degrading:
aistupidlevel.info
Futhark's design is deliberately trying to stay simple to keep long term design sustainable.
The author also has an interesting discussion of relative versus absolute paths in import syntax, and how relative paths can make local analysis easier.
futhark-lang.org/blog/2018-06...
The vast majority of libraries have a single maintainer. Even if you weight by downloads, roughly half of downloaded libraries have a single maintainer too.
opensourcesecurity.io/2025/08-oss-...
Show, don't tell: effective advice for writing for both LLMs and people! www.haskellforall.com/2026/01/prom...
I've been working on a search tool for a website with 9K items and a dumb implementation works just fine. I'd normally gravitate to a library or tool like elasticsearch (ES).
Adding custom filters etc is trivial on handrolled code. I wonder what scale requires actual search infra like ES.
I see people advocating for writing a FAQ, but I really struggle to write one from scratch.
The best FAQs are written as a response to, well, frequent questions.
How do you populate the initial FAQ?
Wonderful post from the lead LLVM maintainer reflecting on how the project is run, the design issues in LLVM today, and opportunities to make it better:
www.npopov.com/2026/01/11/L...
My default assumption is that external libraries are better than what I (or an LLM) would write in a v1.
The extra effort to publish a project generally signifies that the author has spent a good amount of time on the problem. I end up prompting LLMs to prefer external code.
LLMs are great at style transfer, and this works surprisingly well for syntactic transformations too.
I rewrote a small website's EJS templates to 1500 LOC of TSX with a oneshot in Claude. It took ~12 minutes, but it just worked.
(TSX seems nicer than EJS for static analysis.)
It seems really odd to me that git uses 'cached' terminology for staging. For example, `git add somefile.rs; git diff --cached`.
Caching implies state that you don't mind losing. There's very little state I want to lose in version control!
