This was from official Microslop documentation https://web.archive.org/web/20260216165612/https://learn.microsoft.com/en-us/training/modules/introduction-to-github/3-components-of-github-flow
This was from official Microslop documentation https://web.archive.org/web/20260216165612/https://learn.microsoft.com/en-us/training/modules/introduction-to-github/3-components-of-github-flow
To be honest, what I’m most mad about isn’t the typoes, it’s that someone generated this image and figured, yeah alright, that will clear things up.
On some level you want to believe that even if someone does not come up with a proper concept for a visualization, that they still check what the AI shat out, so that it’s at the very least not conceptually wrong and not confusing.
This image isn’t just shitty, it’s actively worse than having no visualization. They could’ve generated that, chuckled, and not used it. Just how do you blunder your perception check so badly that you decide to include it anyways?
In a proper PnPRPG/Tabletop RPG game, a truly spectacular blunder feels like a success to the person who failed. Walk into a bar and critfail both your Communications check, and the “Oh crap, I failed that badly. Can I save this by doing ______?” follow-up Communications check? You think you did fine, but now the entire bar thinks you are a truly crazy person, and treat you with respect only because they think you’re going to shiv them in the neck if they get out of line.
There is the decades-old adage:
That’s why I never comment my code. The documentation is in the
.hfiles. The “h” means “help”.In my company the h means “haha, what were you expecting?”
That is exactly the problem. I understand people using AI to make things. I don’t understand blindly publishing AI slop without verifying it’s correct.
Everybody using genAI has to understand that AI will often be wrong, and frequently ridiculous, and that it’s up to you to ensure that what you deliver is correct.
And because nobody likes to review other people’s work (most people are terrible and sloppy reviewers), it’s better to put yourself in the center: have AI propose ideas or review the result, but you make the thing. That’s how you ensure everything passes through your hands.