What does Model selection / judgment mean in this evidence set?
Source-backed creator statements and evidence excerpts related to Model selection / judgment.
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Model selection / judgment
Source-backed creator statements and evidence excerpts related to Model selection / judgment.
Questions this topic answers
iWhat do creators repeatedly say about Model selection / judgment?
For strategy or content work, a model that infers intent and handles exceptions can be preferable to one that follows rules too literally.
What should an SEO or AI visibility operator inspect first?
For strategy or content work, a model that infers intent and handles exceptions can be preferable to one that follows rules too literally.
How strong is the public evidence?
This topic currently has 1 source records, 1 public insight cards, and 1 creators in the public Base2026 export.
Top Creators
Public Insight Cards
For strategy or content work, a model that infers intent and handles exceptions can be preferable to one that follows rules too literally.
rowsing or finding things on the internet, although that's one of the few areas where both Gemini and ChatGPT are still ahead. In my experience, 4.6 just has better judgment or intuition. 4.7 is known to take everything literally. If you give it instructions, it will follow it to the tea. And at first I thought this would end up being a good thing...
OpenRelated Source Records
The complaints about Claude getting worse? Actually valid this time. Here's why I still...
Typically when people complain that the AI models are getting worse, I think it's just a case of them misremembering how bad they used to be. However, the recent criticism of Anthropic's Claude models getting worse actually has some teeth to it...
OpenEvidence Passages
Short public snippets grouped with their source record, creator, and date.
Typically when people complain that the AI models are getting worse, I think it's just a case of them misremembering how bad they used to be. However, the recent criticism of Anthropic's Claude models getting worse actually has some teeth to it.
I want to talk about why I find myself using 4.6 more than Opus 4.7 these days, and if the models are actually getting worse. So about a week ago anthropic came out and admitted that they found a few bugs and a few default settings that were in fact causing the models to sometimes perform worse than they were in the past.
That explains some of the sentiment. There's also the unfortunate fact that anthropic is currently compute constrained.
They don't have quite as much compute as OpenAI or Google, and they're struggling to keep up with demand. This has LED some to speculate that maybe anthropic is being a little conservative with their token usage.
This is definitely true for at least some prompts on the new models. You can no longer enforce extended thinking...
rowsing or finding things on the internet, although that's one of the few areas where both Gemini and ChatGPT are still ahead. In my experience, 4.6 just has better judgment or intuition.
4.7 is known to take everything literally. If you give it instructions, it will follow it to the tea.
And at first I thought this would end up being a good thing. As long as we could clearly articulate what we wanted to do, it would follow that more closely.
And it does. Too closely.
Ultimately. It ends up obsessing over any guidance we give it.
While 4.6 will easily notice when there's an obvious exception to a rule we've provided, 4.7 will religiously follow our rules, completely abandoning reasonable judgment and common sense. And when your work is nebulous, like strategy or content creation, you can't itemize every single exception to every rule.
You want a model that can infer the intent behind the guidance, and that's what 4.6 is really good at.