Apple’s recent paper on the limits of AI reasoning is an uncomfortable but important read.
Instead of relying on standard benchmarks, the authors designed controlled environments—like Tower of Hanoi and River Crossing puzzles—to test how models handle increasing compositional complexity. The results: performance doesn’t taper off, it collapses. And even when the models fail, they continue to produce fluent, structured reasoning traces that sound convincing but fall apart logically.
If you’re building on top of LLMs or reasoning-augmented models, it’s well worth a look.