# Zero-Shot Chain-of-Thought

> Unlock step-by-step reasoning with a single prompt addition — no examples needed.

- **Category**: Agentic AI
- **Subcategory**: Reasoning
- **Canonical URL**: https://designpattern.fyi/patterns/zero_shot_cot/

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## Description
**Intent**: Elicit multi-step reasoning from a model with a minimal prompt modification — useful when you don't have few-shot examples or want a lightweight CoT trigger.

**Context**: Original CoT research used few-shot examples with worked reasoning traces. Zero-Shot CoT showed that a single instruction phrase reliably triggers similar behavior on modern LLMs — democratizing CoT without the overhead of curating examples.

**Solution**: Append a reasoning trigger to your prompt: "Let's think step by step.", "Think through this carefully before answering.", or for structured output, "Reason step by step, then give your final answer in the format: [format]." For models with native thinking (Claude, o1), this may be redundant — native thinking is more reliable. Zero-Shot CoT is a great default for models without native reasoning. See also: chain-of-thought, extended-thinking, large-reasoning-model-paradigm.



## Use Cases
- Quick CoT activation on any model without prompt engineering overhead.
- Prototyping — add one phrase to any prompt and immediately get better reasoning.
- Fallback when few-shot examples aren't available or don't generalize.






## Trade-offs


### Advantages

- Zero implementation overhead — one phrase, instant CoT activation.

- Works across models and tasks without task-specific examples.

- Reliable accuracy improvement on reasoning tasks with near-zero cost.




### Considerations & Drawbacks

- Less reliable than few-shot CoT on specialized or complex domains.

- Output format can be inconsistent — model chooses its own reasoning structure.

- On native reasoning models (o1, Claude extended thinking), adds unnecessary verbosity.







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**Reference**: [Original Source](https://www.agentpatternscatalog.org/patterns/zero-shot-cot/)