I’m skeptical of the claim that Claude “plans” its rhymes. The original example—“He saw a carrot and had to grab it, / His hunger was like a starving rabbit”—is explained as if Claude deliberately chooses “rabbit” in advance. However, this might just reflect learned statistical associations. “Carrot” strongly correlates with “rabbit” (people often pair them), and “grab it” naturally rhymes with “rabbit,” so the model’s activations could simply be surfacing common patterns.

The research also modifies internal states—removing “rabbit” or injecting “green”—and sees Claude shift to words like “habit” or end lines with “green.” That’s more about rerouting probabilistic paths than genuine “adaptation.” The authors argue it shows “planning,” but a language model can maintain multiple candidate words at once without engaging in human-like strategy.

Finally, “planning ahead” implies a top-down goal and a mechanism for sustaining it, which is a strong assumption. Transformative evidence would require more than observing feature activations. We should be cautious before anthropomorphizing these neural nets.