Prompt Engineering

✅ What is a Prompt?

A prompt is any input or instruction given to an AI system to get a response.

• Examples:

○ Asking Alexa: “How’s the weather?”

○ Asking ChatGPT: “Summarize a research article”

○ Asking DALL·E: “Generate image of a yellow car”

○ Asking Copilot: “Write Python code to add two numbers”

✅ What is Prompt Engineering?

Prompt engineering is the art of designing clear, specific, and context-rich prompts to get accurate and relevant AI outputs.

• The more context and clarity you give, the better the response.

• It's not just about asking; it’s about asking smartly.

🔍 Examples in Action

• Asking “What is AI?” gives a generic reply.

• But “I am a healthcare professional. Explain AI with relevant examples from healthcare.” gives a more relevant and focused response.

Similarly:

• Vague: “Tell me about solar energy”

• Better: “Imagine you're a journalist. Write a 500-word bullet-point summary of solar energy between 2020–2030.”

Result: More customized, structured, and domain-specific outputs.

✍️ Best Practices for Prompt Engineering

1. Be Clear: Say exactly what format/output you want (summary, bullets, tone, etc.).

2. Provide Context: Tell the model who you are or what role it should play.

3. Balance Simplicity & Detail: Don’t be too vague or overly complex.

4. Iterate & Refine: Trial and error is key. Adjust and improve prompts over time.

⚠️ Limitations & Challenges

• Small changes in phrasing can drastically change the results.

• Too much information in one prompt may confuse the model.

Consistency is not guaranteed.