Zero-Shot vs Few-Shot Prompting — ChatGPT
Zero-shot means asking directly with no examples.
The prompt
Classify each review as Positive, Negative, or Neutral. Review: "Delivery was fast but the box arrived damaged." -> Neutral Review: "Absolutely love this, ordering again!" -> Positive Review: "Item never showed up, no refund." -> Negative Review: "It works fine, nothing special." ->
Pro tip: Few-shot prompting is the fastest way to lock in a consistent tone or output format across a whole batch of content.
How to use this prompt
- Copy the prompt using the button above.
- Add any context specific to your situation — the more specific you are, the better the output.
- Paste it into ChatGPT and run it.
- If the answer feels generic, add constraints: audience, length, tone, and what to avoid. That single change fixes most weak output.
Learn the technique
Zero-Shot vs Few-Shot Prompting
Module 1 — Anatomy of a Prompt · Prompt Engineering Fundamentals
Related prompts
The 5-Part Prompt Framework — ChatGPT
Every strong prompt combines five parts: Role (who the AI should act as), Context (background info it needs), Task (the specific ask), Format (how you want the output structured), and Constraints (length, tone, things to avoid).
ClaudeThe 5-Part Prompt Framework — Claude
Every strong prompt combines five parts: Role (who the AI should act as), Context (background info it needs), Task (the specific ask), Format (how you want the output structured), and Constraints (length, tone, things to avoid).
GrokZero-Shot vs Few-Shot Prompting — Grok
Zero-shot means asking directly with no examples.
ChatGPTChain-of-Thought Prompting — ChatGPT
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
ClaudeChain-of-Thought Prompting — Claude
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
ChatGPTStructured Output (JSON & Tables) — ChatGPT
When you need output your app or spreadsheet can actually use, explicitly request a schema.
Related across the site
Chain-of-Thought Prompting — ChatGPT
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
10 Prompt Mistakes That Make AI Output Generic
The specific, fixable reasons AI output comes back bland — and what to write instead. Each mistake includes a before-and-after example you can apply immediately.
Few-shot prompting
Few-shot prompting means including two to five worked examples of the input-output pattern you want before making your real request. It is the fastest way to lock in a consistent format, tone or edge-case behaviour.
Prompt Engineering Fundamentals
Learn the building blocks of a great prompt — role, context, task, format, and constraints — and how ChatGPT, Claude, Perplexity, and Grok each respond differently to the same instructions.
Zero-shot prompting
Zero-shot prompting means asking a model to do a task with no worked examples — just an instruction. It works well for common tasks the model has seen extensively in training.
ChatGPT vs Claude vs Perplexity vs Grok — Grok
The same task often needs a slightly different prompt style per model.