Prompt Engineering

Prompt engineering is the art of crafting precise instructions (“prompts”) for generative AI models obtain optimal results. Instead of simply asking ChatGPT “write me text,” prompt engineering is “write me 200-word marketing text for AI startup, with confident tone, for LinkedIn”.

Examples of bad prompts: (1) “Write code”—too vague; (2) “Write me financial forecast”—AI won’t know context.

Examples of good prompts: (1) “Write Python code reading CSV file with 3 columns (first name, last name, email) generating email template ‘Hello [name], see your profile [email]’”; (2) “Write financial forecast for e-commerce startup with: current revenue 50k/month, 10%/month growth, 30k/month expenses.”

Techniques for good prompt engineering: (1) Clarity—be specific, not vague; (2) Context—explain background; (3) Format—state desired format; (4) Examples—provide desired output examples; (5) Role-playing—”Pretend you’re investor with 20 years experience.”

Good prompt engineering advantages: (1) Quality—better results; (2) Speed—no iterations needed; (3) Consistency—same prompt gives same results; (4) Automation—can automate with good prompts.

For startups: Prompt engineering is new skill—need learn proper AI use. Even small prompt differences drastically different results.