Should we prioritize chain‑of‑thought prompting over zero‑shot prompting for complex tasks?

25 Eki 07:45

Prompt engineering has evolved rapidly, and two strategies keep surfacing: chain‑of‑thought prompting, where the model is guided to generate intermediate reasoning steps, and pure zero‑shot prompting, which relies on the model’s innate knowledge without explicit scaffolding. In my recent experiments, chain‑of‑thought often yields higher accuracy on math‑heavy or logic puzzles, but it also lengthens the prompt and can introduce unnecessary verbosity. Zero‑shot keeps things concise and works well for straightforward classification, yet sometimes it falters on multi‑step problems. I’m curious how the community balances these approaches. Do you default to one style depending on the task, or blend them? What guidelines have you found reliable?