Why This Cheat Sheet Matters for AIF-C01
This cheat sheet covers the most important Prompt Engineering concepts tested on the AIF-C01 (AWS AI Practitioner) certification exam. It contains 4 sections with 21 key points that you should memorize before exam day. Prompt engineering is the practice of designing effective inputs for foundation models. Master zero-shot, few-shot, chain-of-thought prompting, system prompts, and prompt optimization techniques. Use this as a quick-reference guide during your final review sessions.
4Sections
21Key Points
Prompting Techniques
- Zero-shot: ask the model directly without examples.
- One-shot: provide one example before the actual query.
- Few-shot: provide multiple examples to guide the model.
- Chain-of-thought: ask the model to reason step by step.
- System prompts: set the model's persona, constraints, and behavior.
Best Practices
- Be specific and clear — vague prompts produce vague outputs.
- Provide context and constraints to narrow the response.
- Use delimiters (###, ```) to separate instructions from content.
- Specify the output format (JSON, bullet points, table).
- Iterate and refine — prompt engineering is an iterative process.
- Test with diverse inputs to ensure robustness.
Common Pitfalls
- Hallucinations: model generates plausible but incorrect information.
- Prompt injection: malicious inputs that override system instructions.
- Context window limits: too much input causes truncation.
- Over-reliance on temperature: too high = nonsense, too low = repetitive.
- Not validating outputs: always verify critical AI-generated content.
When to Use What
- Zero-shot for simple, well-defined tasks.
- Few-shot when the model needs examples of the desired format.
- Chain-of-thought for complex reasoning or math problems.
- System prompts to enforce consistent behavior across conversations.
- RAG when the model needs access to current or proprietary data.
Practice Prompt Engineering Questions
Put your knowledge to the test with practice questions.