Ee-Peng Lim
Whether asking a language model to make a plan before solving a problem produces better reasoning than telling it to think step by step.
The dominant zero-shot prompting trick for reasoning has been "Let's think step by step" — open-ended, no enforced structure, hope the model finds its own path. Plan-and-Solve Prompting (2023, with Lim as senior author) added a small but consequential structural change: first ask the model to articulate a plan for solving the problem, then execute that plan step by step. The empirical result was a modest but consistent improvement on math and reasoning benchmarks, and a methodological one — explicit planning leaves an artifact in the trace, so you can examine what the model thought it was about to do and where it deviated.