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What Reasoning Actually Means (and Why It Matters for Your Architecture)
It Started with a Saturday Morning Experiment
I recently ran a simple test. I asked a small language model the same questions three times, with zero, one, and three rounds of self-reflection, and published the results. The pattern was clear: self-reflection helped when the model already knew the topic. It did nothing when it didn’t. And on bleeding-edge questions, more thinking just produced more confidently wrong answers.
That experiment raised a question I couldn’t shake: if “thinking harder” only works sometimes, what exactly is happening when a model reasons, and when is it just pretending?