Leveling Up: Professional Techniques

Most people use "Zero-shot" prompting (just asking a question). But to get professional, stable results, you need to use Samples and Step-by-Step Logic.

1. Zero-shot Prompting

Just asking the AI to perform a task without any examples.

• "Translate this to French: 'Where is the library?'"
• Best for: Simple, factual asks.

2. Few-shot Prompting (The Power of Examples)

Giving the AI 2-3 examples of the style you want before asking your question.

• "Question: Happy $\rightarrow$ Answer: Positive
• Question: Sad $\rightarrow$ Answer: Negative
• Question: Excited $\rightarrow$ Answer:"
• Best for: Formatting, tone, and classification.

3. Chain-of-Thought (CoT)

Telling the AI to "Think step-by-step." This forces the model to write out its logic before giving the final answer.

• Why it works: By writing its logic, the model "reminds" itself of the context (Module 2) and is far less likely to hallucinate a wrong math answer.

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Visualizing Chain-of-Thought

graph TD
    Q[Complex Math Problem] --> A[Standard AI: WRONG ANSWER]
    Q --> B[CoT Prompt: 'Think Step by Step']
    B --> Logic1[Step 1: Calculate total...]
    Logic1 --> Logic2[Step 2: Apply tax...]
    Logic2 --> Logic3[Step 3: Subtract discount...]
    Logic3 --> Final[Correct Answer]

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💡 Guidance for Learners

If an AI gives you a wrong answer on a puzzle or math problem, don't just ask again. Type: "Think through this step-by-step and show your reasoning." It will get the answer right 80% of the time.

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Summary

• Zero-shot is a direct request.
• Few-shot uses examples to define the "Vibe" or format.
• Chain-of-Thought is the #1 way to solve logic and math errors.
• Giving context (even just a few examples) is always better than no context.