Also doesn’t have those damn emojis 🎯️ ✅️
Those are right in with the em-dash, real people just don’t take the time…
LLMs were trained on writing by real people. So, yes, real people DO.
the books the LLM were trained on that used the most em dashes used like 1 every 200-500 characters. LLMs use em dashes at a rate of like 1 every 40-50 characters. It’s not even CLOSE to human behavior.
I’m still a fan of emoticons personally, can’t beat >:( to express irritation for example.
Remmber when Most Google products were marked Beta? those were the days when Google software was still great.
Google software was never great. It always was buggy, laggy and with horrendous UI.
GMail and GReader were great and way ahead of the other players.
Closing GReader was what radicalized me against Google.
Google Music was great. Stream my collection without any legwork other than uploading? Thank you! But fuck off for killing it.
fuck off for killing it.
Welcome to the c l o u d .
If there’s a readme, there’s documentation. It might not be enough, it might be out of date, it might be wrong, but it’s still documentation.
Humans understand that their work is unfinished.
I had a vibe coding coworker take over a project. Added 8,000 lines of documentation all dated 6 months in the future.
dated 6 months in the future.
That’s forward thinking! (and illegal in my industry.)
TODO: write TODO comments
Who needs TODOs when you can just forget about the things and have less to do?
Just create a Jira ticket in the backlog and forget about it. That way it becomes a team/company process failing, not a personal one.
Hey agent, make it look like its human written with speling erors And shit
I’m starting to see posts on social media that are clearly an AI bot based on the wording (e.g. shuffling a few key pieces of info around and slightly rephrasing the post they’re replying to), but written in all lowercase. They’re trying to make it seem like a lazy/sloppy human wrote it when it’s really just a sloppy bot.
TODO comments ARE documentation
README’s are documentation.
As an open source project maintainer I can always tell whenever a pull request is AI assisted because no human would ever write full tests for all their pull requests.
Libtcod? Cool project. Btw do those generated tests tend to be helpful or confusing?
The important part is that the tests track regressions and they’re helpful for that. After that, it’s okay if tests are mostly write-only.
I’ve noticed that AI commentary tends to describe what the code is doing verbatim which is better for naming tests and functions rather than writing code comments, docstrings, or change notes. I usually have to fix this public-facing documentation to not talk about library internals which no user of the library would ever care about.
So far I feel that AI assists are good when you have the time and effort to push back on them, but that isn’t an option for all projects, it works well for my own projects which have very few contributors in the first place. For the most part I can treat them with the same scrutiny as human written code. When the person submitting the code is obviously not checking their own code then that’s a problem.
