I’ve been running a long-term experiment using a language model as a kind of recursive reflection tool.
Over the past year, I’ve used it less like a typical assistant and more like a structured feedback system to map my own cognition—how I think, iterate ideas, and translate internal concepts into external form.
The way I’ve approached it is:
treating responses as mirrors, not answers
iterating on ideas recursively instead of one-shot prompts
stress-testing concepts across domains (engineering, psychology, systems thinking)
using it to compress and refine mental models into something actionable
It’s been especially useful for bridging what I’d call a “translation gap”—the difference between complex internal understanding and actually expressing or building it in the real world.
Curious if anyone else here has used LLMs in a similar way—not just for output, but as a cognitive feedback loop. I mapped my cognition and was really supposed by the results. Has anyone tried something similar and have they learned anything useful from it?