In the future, I expect different models from different firms behaving differently will become as obviously normal as different humans behaving differently. Those of us that have used agents a lot have already noticed this, but the general public still seems to consider AI to be plug-and-play.
The Opus 4.8 infatuation with being honest genuinely drove me nuts (honest take). The constant need for me to decipher and decide on something after its final message was tiring too.
GPT-5.6-Sol is refreshing that its replies start with "understood." instead of flattering me for my steering prompt. Now ... after a few weeks, will I get suck of "understood"? I dunno :)
And the fact that this article’s story is basically “I prompted Fable with a goal and went to sleep and the model got it done” is telling me that the latest models have gotten past the need for Superpowers… even the creators of superpowers is just using a simple /goal!
That was fun, and the script on github looks hand-written which is refreshing after having been reading AI-written code for months.
I have 120k photos in iCloud that I'm sure have duplicates (I exported my library to Google Photos years ago and exported it back to iCloud). The iOS duplicate detection stopped flagging duplicates for me to merge a while back. I gotta do something like this script...
I see this post is from 2024. Maybe I would have enjoyed the hook and enjoyed reading along to figure out what this "harajuku moment" was back in 2024. But since being exposed to AI slop daily, and having to scan through so much verbose AI outputs during day-to-day "coding", I've now started skimming so much that I got annoyed that it meandered, then just couldn't bother reading the rest of the post after I've figured out what the harajuku moment is.
It's like my brain is responding to blog posts now in the same way that people scroll past tiktok videos in the first few seconds if there isn't enough of a dopamine hit.
Sometimes when I'm in the CLI and don't have a code editor open, I do this. Yes, it's lazy. But I also trust the model to check and update related things (tests, etc., while applying some judgement).
It's not unlike some managers who tell their teams to do something trivially easy that they could have done themselves.
(I'm not saying this is ideal and I'm not defending my laziness. It's just the current state of things.)
I'm user 7xx,xxx but I also believe I created a Github account while working on Rails projects (basically copying Ryan Bates and assembling things together. haha good times)
I asked GPT-5.4 High to draw up an architecture diagram in SVG and left it running. It took over an hour to generate something and had some spacing wrong, things overlapping, etc. I thought it was stuck, but it actually came back with the output.
Then I asked it to make it with HTML and CSS instead, and it made a better output in five seconds (no arrows/lines though).
SVG looks similar to the XML format of spreadsheets. I wonder if LLMs struggle with that?
I also liked that it didn't explicitly say how it decides when to play a note.
All the subway routes are normalized to 15 seconds long from beginning to end. The app then plays all 15 second routes together, playing the instrument assigned to the route when there's a train there.
Neat commentary on the instruments that were assigned to the route when you mouse over it.
I have a pet theory that the uptick in normal cybersecurity PRs you mention as a trend in your blog were done with Claude Code’s stealth mode and Mythos.