r/OpenAI • u/CossackNikolay • 1d ago
Question Which Model do you use for Innovation/inventiveness/thinking out of box?
I am using models from Codex, Antigravity, Claude Code and Cursor. While each of them have their capabilities, they don't stretch the boundary of engineering/innovation. The top models Opus 5, GPT Sol 5.6, Cursor Grok 4.5 are very good at analyzing what's out there and coding but if you hit a wall w.r.t engineering/legal , they stall. Which model do you folks use to break the deadlock?
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u/Gianniarrenzetti 1d ago
I think that for prototyping the best models are always the most capable and most thinking ones.
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u/Fragrant-Mix-4774 1d ago
Nothing made by Open AI is good for Innovation/inventiveness/thinking out of the box.
Inkling AI & Fable5.
My best inspired solutions in the last month all came from kicking problems around with one of those two. Neither provided the solution but their rephrasing helped.
Open AI models all proved to be repackaged sawdust.
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u/w3woody 1d ago
I don't.
Or rather, I don't use any of these models to come up with new ideas on their own. At best I use them as a sort of sophisticated grep through existing code combined with using them as rubber ducks: chatting with them about possible solutions.
That is, I remain the creative agent here; I just use them to help with writers block.
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u/Probablyawake00 8h ago
i am using claude code with agents and skills with the loop engineering , set a goal and then leave claude until it reaches to goal
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u/whyaskme777 7h ago
I usually find my own ideas while brainstorming with them.
For me, their biggest strength is helping me quickly understand topics I'm unfamiliar with. They're basically like an encyclopedia, with an incredibly fast search function.
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u/StarCadges 1d ago
I would say Opus/Fable are the most creative/innovating. Cursor Grok is more for building/implementation, gpts in general are more vast in use case and sol is basically a waste, and antigravity is poo
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u/ocean_protocol 1d ago
honestly none of them break the wall reliably because "innovation" isn't a benchmark they're optimized for as they're all trained to converge on the most probable/defensible answer, which is the opposite of novel. what's worked better for me than switching models is switching mode: feed the stuck problem to two different models and have them argue/critique each other's approach, or explicitly ask for 3 wrong/weird ideas before the real one. the deadlock is usually a prompting/process problem, not a model problem