I find it's surprising that people doubt the effectiveness of Pangram when I feel like its job has gotten easier ever since Claude models got RLHF to death with its bizarre punchy negatives and tortured analogies, making AI writing much more noticeable than the GPT 4o era.
> He described waking up to thirty PRs every morning, each one pulled overnight by someone's AI, and needing to make snap judgment calls on every single one. The temptation to delegate the review itself to an AI was enormous. But, as he put it: "at that point, what am I still doing here?".
It's so funny and somber to see programmers having an existential crisis when they get a glimpse of what work is like for business managers, the demographics many programmers detest.
I am also guilty of holding the business majors in contempt back in college, and now here I am, doing what they are doing in office in a much more indifferent and unenjoyable manner. At least I don't get into trouble with HR from calling my agents a stupid fuck (yet).
I used Better Auth for my mobile app backend. It works okayish. My biggest complaints are the OpenAPI specification gets little care, as it mainly caters for JS frontend, and breaking changes in patch version are more common than most packages.
I saw on Twitter that in an ML course at Tsinghua University, one of the tests asks students to write quizzes that fail the most LLM models as possible.
What if we create a benchmark that works like this and assigns ELO scores? Models fight head-to-head by writing a question, a bug, or an incomplete implementation, which the opponent has to answer, fix, or finish.
i like the COPY and logical replication improvements. Currently I back up my PG database with a sidecar Databasus instance that is heavier than my entire backend + DB + Caddy!
(LLM writing rant below)
---
> That alone tells you something: Users had a real need, and the ecosystem filled the gap.
> This sounds straightforward, but it solves a real operational problem.
> None of these change the world. All of them make day-to-day data workflows better.
> The easy thing to do here is list planner changes and call it done. But the more useful takeaway is this: Postgres keeps getting better at recognizing the shape of common queries and doing less unnecessary work.
> [Proceed to list planner changes]
If Orwell were alive today, he might declare himself illiterate in English and learn Klingon just to avoid having to read these.
Heck, mise has an HTTP backend that can install binaries from any URL. I use this to manage Atlassian CLI, whose official Windows binary is not on winget.
Never, ever, ever transform URIs and paths by string manipulation. If you think pulling in a library for this is overkill, it is not.
(Lesson learned from trying to quickly write my own function to make ".." to go back one URL segment that took 3 hours and discovering the URI spec contradicts my intuition depending on whether the URI is a URL or filesystem path.)
No worries, I don't mean to disparage your article. At least it avoids some of the most annoying LLMism I have seen, and given its length you must have put some effort into prompting, researching, or editing. Hope you will find your own voice as you write more and more.
Incredible, I have never heard of std::autodiff before. Isn't it rare for a programming language to provide AD within the standard library? Even Julia doesn't have it built-in, I wouldn't expect Rust out of all languages to experiment it in std.
First, you don't have to feel guilty of anything, since forking open source projects to make changes tailored to your use case is as old as open source itself. It is, in fact, the primary benefit of open source.
Second, it is not a given that your change would be accepted regardless of who wrote it. Maybe the feature is too niche for its complexity, maybe it is better implemented with more generality or extensibility that does not make sense for your own use. In those cases, your change might have been rejected upstream, so having it only locally is a perfect fine solution.
Third, if you believe it is actually useful for broader users, open an issue requesting that feature, and say LLM implemented it in an hour. Then the maintainers can prompt their own LLM to implement it with ease, or do whatever they want with their project.