Using AI Models as a ‘Conceptual Sonar’ for Idea Coherence

• develop an idea—abstract, complex, layered.
• throw it at multiple AI models.
• observe the variance in response.
• If they diverge wildly → your idea may be incoherent or ambiguous.
• If they converge → the idea may possess structural integrity.
• use this feedback loop as a kind of convergence-detection sonar.

Basically, I’ve been using the different probability generation spaces that different AI models ( represents as a way to figure out convergence/divergence for any ideas I might have. I’m sort of abstracting the notion of Moiré interference to see if any patterns pop out semantically, and building up a stochastic picture of whatever I’m considering. There’s a weird back and forth where I’ll range over ideas for a while before landing on something solid. It weirdly feels like I’m looking through a microscope or telescope.