From Oops to Awesome: 5 Common Prompting Mistakes with LLMs
Getting the most out of Large Language Models (LLMs) like ChatGPT, Gemini, or LLaMA is like knowing the secret recipe for perfect cookies — one wrong move and it’s a mess! Even the best data scientists can make mistakes that turn great questions into confusing answers.
So, let’s have some fun and learn how to avoid five common mistakes. I will show you how to turn your prompts from “oops” to “awesome” with easy examples.
1. Being Too Vague
Mistake: Being too vague is like asking a friend, “What’s up?” and expecting a life story. LLMs need details to give you a good answer..
Ineffective Prompt: “Tell me about healthcare.”
Effective Prompt: “Provide a summary of the latest advancements in telemedicine for chronic disease management.”
Explanation: The first prompt is too vague and could lead to a broad discussion covering various aspects of healthcare, while the second prompt specifies the area of interest (telemedicine) and context (chronic disease management), leading to a more targeted and useful response.
2. Using Complex Language
Mistake: Using fancy words can confuse LLMs. Keep it simple, and you’ll get better answers.
