I think at the moment that's indeed the case...

But also maybe that will change — LLMs can learn new languages faster than people, and can _write_ new languages much faster than people. So wide confidence bounds for the future!

Indeed we're doing fewer new features (and haven't posted to the posts page in a long time, as you noticed).

But it's still maintained, folks are still using it, if anyone finds bugs in simple-to-moderate queries then we'll fix them.

LLMs probably took a bit of the wind out of our sails for making this "the new standard". But I still think it's a really nice language and interface; if the world changed again such that it became more widely useful, I'd jump to spending lots of time on it again.

(I don't _love_ his vibes on Twitter, but he seems like a very reasonable guy generally, and the project seems awesome)

Gotta start somewhere!

You can just ask people for things! And you will become a better person for it.

Since agents have become good enough to run in parallel, I've found git worktrees to be, in the words of Juliet "my only love sprung from my only hate" — an awesome productivity multiplier, but with a terrible UX...

Worktrunk is designed to fix that: 1) it's a wonderful layer on top of git worktrees and 2) it adds a lot of optional QoL improvements focused on parallel agents.

Those Qol improvements include a command to show the status of all worktrees/branches (including CI status & links to PRs), a great Claude Code statusline, a command to have an LLM write a commit message, etc.

Like my other projects (PRQL, xarray, insta, numbagg), it's Open Source, no commercial intent. It's written in rust, extensively tested; crafted with love (no slop!)

Check it out, please let me know any feedback, either here or in GH. Thanks in advance, Max

- https://github.com/max-sixty/worktrunk

- https://worktrunk.dev/

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Then, if the AIs are positive, the human principals can talk

Seems quite reasonable!

but this seems to be a totally asynchronous service with extremely liberal latency requirements:

> On a regular interval, Password Monitoring checks a user’s passwords against a continuously updated and curated list of passwords that are known to have been exposed in a leak.

why not just run the checks at the backend's discretion?

I haven't productized it though; uzi looks great!

though what does "static cpu" vs "dynamic cpu" mean? it's one thing to be pointer chasing and missing the cache like OCaml can, it's another to be running a full interpreter loop to add two numbers like python does

One benefit of PRQL [disclaimer: maintainer] is that it's simple to add additional logic — just add a line filtering the result:

  from users
  derive [full_name = name || ' ' || surname]
  filter id == 42           # conditionally added only if needed
  filter username == param  # again, only if the param is present
  take 50

The US consumes 500 gigawatts on average, or 5000 watts per household.

So if every household bought an 8K TV, turned it on literally 100% of the time, and didn't reduce their use of their old TV, it would represent a 10% increase in power consumption.

The carbon emissions from residential power generation have approximately halved in the past 20 years. So even with the wildest assumptions, it doesn't "throw away all the progress we've made on Global Warming for the past 20 years ...".