Zero-Shot and Few-Shot Prompting
Steer behavior with examples.
Zero-Shot and Few-Shot Prompting is a free NLP Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the NLP Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Prompting Is Programming
With LLMs, your main control is the words you send. The art of shaping those words is called prompting. ✍️
Zero-Shot Prompting
In zero-shot prompting you just describe the task in plain words, with no examples, and trust the model to figure it out.
prompt = "Classify this review as positive or negative: I loved it!"When Zero-Shot Works
Zero-shot is great for common tasks the model has seen often, like summarizing a paragraph or answering a simple question.
Show, Do Not Just Tell
When the task is unusual, examples help. Giving the model sample inputs and outputs is called few-shot prompting.
A Few-Shot Example
You list a couple of worked examples, then leave the final input blank so the model continues the same pattern.
Review: Great! -> positive
Review: Awful. -> negative
Review: I loved it! ->Examples Set the Format
Few-shot does more than teach the task; it also fixes the output format, so the model answers in exactly the shape you showed.
Pick Clear Examples
Choose examples that are correct, varied, and unambiguous. Sloppy or biased examples quietly teach the model the wrong pattern.
More Is Not Always Better
Each example eats into the context window and adds cost, so use the fewest examples that reliably get the job done.
Be Specific
Vague prompts give vague answers. Spell out the role, the task, the format, and any constraints you care about.
Think Step by Step
For tricky reasoning, ask the model to work it out step by step. This chain-of-thought hint often improves the final answer.
prompt = "Solve this and show your reasoning step by step: ..."Iterate and Test
Prompting is empirical. Try a version, check the outputs, then refine the wording until results are consistent.
Quick Check
What is the key difference between zero-shot and few-shot prompting?
Recap
Start zero-shot for common tasks. Add a few clear examples when you need a specific pattern or format, then iterate. ✅
Frequently asked questions
Is the “Zero-Shot and Few-Shot Prompting” lesson free?
Yes — the full text of “Zero-Shot and Few-Shot Prompting” is free to read here on the web, and the NLP Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the NLP Academy course, upgrade to CoddyKit PRO.
What will I learn in “Zero-Shot and Few-Shot Prompting”?
Steer behavior with examples. You practise NLP Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start NLP Academy?
No prior experience is required. NLP Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Zero-Shot and Few-Shot Prompting” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this NLP Academy lesson?
Yes. Every NLP Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- What Makes a Model Large
- Calling an LLM From Python
- Zero-Shot and Few-Shot Prompting
- Structured Output and Guardrails