Step-by-Step Problem Solving (Chain-of-Thought) › Limitations and When Not to Use Chain-of-Thought
Michael BrenndoerferJune 17, 20251 min read
AI Agent HandbookAll chapters Part 4 of 15Reasoning - Teaching the Agent to Think
Step-by-Step Problem Solving (Chain-of-Thought) › Limitations and When Not to Use Chain-of-ThoughtOne section · Sections in this chapter9 / 13 ↓
Sections in this chapter13
Chain-of-thought reasoning is powerful, but it's not always the right tool:
It's slower: Generating reasoning steps takes more time than jumping to an answer. For simple questions, this overhead isn't worth it.
It uses more tokens: More generated text means higher API costs. Use chain-of-thought when accuracy matters more than speed or cost.
It can be verbose: Sometimes you just want a quick answer, not a detailed explanation. Match the technique to your needs.
It doesn't guarantee correctness: Chain-of-thought improves accuracy, but the model can still make errors in its reasoning. Always verify critical results.
The key is knowing when the benefits (better accuracy, transparency, debuggability) outweigh the costs (time, tokens, verbosity).