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Earlier quoted context omitted.
LLMs are really bad at anything visual, as demonstrated by pelicans riding bicycles, or Claude Plays Pokémon. Opus would probably do better though.
How could they be any good at visuals? They are trained on text after all.
Yes plausible text prediction is exactly what it is. However, I wonder if the author included benchmarking in their prompt. It's not exactly fair to keep hidden requirements.
My own experience using Claude Code and similar tools tells me that "hidden requirements" could include:
* Make sure DESIGN.md is up to date
* Write/update tests after changing source, and make sure they pass
* Add integration test, not only unit tests that mock everything
* Don't refactor code that is unrelated to the current task
...
These are not even project/language specific instructions. They are usually considered common sense/good practice in software engineering, yet I sometimes had to almost beg coding agents to follow them. (You want to know how many times I have to emphasize don't use "any" in a TypeScript codebase?)
People should just admit it's a limitation of these coding tools, and we can still have a meaningful discussion.
I tried to make Claude Code, Sonnet 4.6, write a program that draws a fleur-de-lis. No exaggeration it floundered for an hour before it started to look right. It's really not good at tasks it has not seen before.
I think some industries with mostly proprietary code will be a bit disappointing to use AI within.
Cherry picked AI fail for upvotes. Which you’ll get plenty of here an on Reddit from those too lazy to go and take a look for themselves.
Using Codex or Claude to write and optimize high performance code is a game changer. Try optimizing cuda using nsys, for example. It’ll blow your lazy little brain.
That's very impressive. Your LLM actually wrote a correct code for a full relational database on the first try, like it takes 2.5 seconds to insert 100 rows but it stores them correctly and select is pretty fast. How many humans can do this without a week of debugging? I would suggest you install some profiling tools and ask it to find and address hotspots. SQL Lite had how long and how many people to get to where it…
Just copy and paste from an open source relational db repo
Easy. And more accurate!
But my AI didn't do what your AI did. Cherry picked AI fail for upvotes. Which you’ll get plenty of here an on Reddit from those too lazy to go and take a look for themselves. Using Codex or Claude to write and optimize high performance code is a game changer. Try optimizing cuda using nsys, for example. It’ll blow your lazy little brain.
Related:
- http://archive.today/2026.03.07-020941/https://lr0.org/blog/...> (I'm not consulting an LLM...)
- https://web.archive.org/web/20241021113145/https://slopwatch...>
I tried to make Claude Code, Sonnet 4.6, write a program that draws a fleur-de-lis. No exaggeration it floundered for an hour before it started to look right. It's really not good at tasks it has not seen before.
Considering that a fleur-de-lis involves somewhat intricate curves, I think I'd be pretty happy with myself if I could get that task done in an hour. Given a harness that allows the model to validate the result of its program visually, and given the models are capable of using this harness to self correct (which isn't yet consistently true), then you're in a situation where in that hour you are free to do some other…
TBH I would have just rendered a font glyph, or failing that, grabbed an image.
Drawing it with vector graphics programmatically is very hard, but a decent programmer would and should push back on that.