How to Talk to AI: Prompting Techniques That Actually Work

Large Language Models like ChatGPT are powerful, but their output quality depends heavily on how you ask the question. Prompting is not about tricks, but it is about clear intent, structure, context, and constraints. Poor prompts lead to vague, hallucinated, or unusable answers, while well designed prompts can turn the same model into a highly reliable assistant for problem solving, coding, analysis, writing, and decision-making.

In this webinar, we will break down practical prompting techniques used by professionals to get consistent, high-quality results from LLMs. You’ll learn how models interpret instructions, why prompts fail, and how to design prompts using patterns like role-based prompting, step-by-step reasoning, constraints, and examples. The session is hands-on, example driven, and focused on real world use cases rather than theory.

• Why prompt quality directly impacts accuracy, reliability, and usefulness of LLM outputs
• How LLMs interpret instructions and common reasons prompts fail or hallucinate
• Practical prompt design patterns such as role-based prompts, constraints, examples, and step-by-step reasoning
• How to apply prompting techniques to real-world tasks like coding, analysis, writing, and decision-making