61–70 of 77 posts
> Some models (looking at you, GPT-5-Codex) seemed to mistake “more complex” for “better.” That's what working with GPT-5-Codex on actual code also feels like.
If Sonnet doesn't solve my problem, sometimes Codex actually does.
So it isn't like Codex is always worse. I just prefer to try Sonnet 4.5 first.
What I take from this is that LLMs are somewhat miraculous in generation but terrible at revision. Especially with images, they are very resistant to adjusting initial approaches. I wonder if there is a consistent way to force structural revisions. I have found Nano Banana particularly terrible at revisions, even something like "change the image dimensions to..." it will confidently claim success but do nothing.
Ask for multiple solutions?
I tried an experiment like this a while back (for the GPT-5 launch) and was surprised at how ineffective it was. This is a better version of what I tried but suffers from the same problem - the models seem to stick close to their original shapes and add new details rather than creating an image from scratch that's a significantly better variant of what they tried originally.
Maybe there’s a bias towards avoiding full rewrites? An “anti-refucktoring” bias I’d be curious if the approach would be improved by having the model generate a full pelican from scratch each time and having it judge which variation is an improvement. Or if something should be altered in each loop, perhaps it should be the prompt instead
Iterating a Markov chain does not make it any more or less "agentic". This is yet another instance of corporate marketing departments redefining words b/c they are confused about what exactly they're trying to build & sell.
No this is obviously not corporate marketing, this individual is doing many things wrong by their own choice: "creating an svg is surprisingly revealing" No it is not. They all do the same thing, they add suns and movement lines, and some more details. Like they were all trained on the same thing. he makes up his own definition of "agent" there are at least 6 different definitions of this word now in this space. And…
> Danielle Del, a spokeswoman for Sasso, said Dudesy is not actually an A.I.
> “It’s a fictional podcast character created by two human beings, Will Sasso and Chad Kultgen,” Del wrote in an email. “The YouTube video ‘I’m Glad I’m Dead’ was completely written by Chad Kultgen.”
> Some models (looking at you, GPT-5-Codex) seemed to mistake “more complex” for “better.” That's what working with GPT-5-Codex on actual code also feels like.
I love this experiment and am surprised that the Claude models performed that much better than the competition. Opus was particularly impressive both in the quality itself and the ability to iterate meaningfully. Now... Was this article LLM written? This part triggered all my LLM flags: ``` Adding a bicycle chain isn’t just decoration—it shows understanding of mechanical relationships. The wheel spokes, the adjusted…
Did not feel LLM written to me - at least not overtly so. LLM editing/assisted perhaps? It was a fun little post that felt accurate (ie confirmed my own biases ;)) about the current state of LLM models in a silly, but real, use-case. The continual drive to out "llm written" articles feels a bit silly to me at this point. They are now part of the tools and tech we use, for better or worse. And to be clear, I think in…
I already spend too much time reading LLM outputs on my own interactions. And I get sick of their style because of it. So when I read it during leisure time, it just triggers a gut rejection.
Especially because they are so formulaic / template-y.
Earlier quoted context omitted.
Did not feel LLM written to me - at least not overtly so. LLM editing/assisted perhaps? It was a fun little post that felt accurate (ie confirmed my own biases ;)) about the current state of LLM models in a silly, but real, use-case. The continual drive to out "llm written" articles feels a bit silly to me at this point. They are now part of the tools and tech we use, for better or worse. And to be clear, I think in…
No, I don't have anything against using LLMs to write. My problem is that I enjoy reading people in part for diversity of style. I already spend too much time reading LLM outputs on my own interactions. And I get sick of their style because of it. So when I read it during leisure time, it just triggers a gut rejection. Especially because they are so formulaic / template-y.
What about structuring the agentic loop to do a simple genetic algorithm -- generate N children (probably 2 or 3), choose the best of the N+1 options (original vs. child A vs. child B vs. child C, and so-on) and then iterate again?
This wasn’t just “add more details”—it was “make this mechanically coherent.” The overall text doesn’t appear to be AI written, making this all the more confusing. Is AI making people write this way now on their own? Or is it actually written by an LLM and just doesn’t look like it?
I write like that and I'm not an LLM.
Earlier quoted context omitted.
I mean at some point you have to evaluate the content on its merit and they have a point — a chain is functional not just decorative in its precise placement.
If you give it credit for the chain, you need to also notice that that bike has a fixed front wheel. It literally can not be turned.