The Science of Prompt Engineering

Prompting is often misunderstood. We either just type a one line instruction with no details, or create a large markdown file that is bloated. In this video, we're taking a deep dive into Prompt Engineering. We will see why it is essential, how it has evolved, and why prompts change the outputs. Understanding how prompts work, and mastering it is a skill for everyone working with Large Language Models (LLMs), irrespective of your role. I am Sathiesh Veera, I am an AI Solutions architect and I build solutions that use AI. Key points we discuss today: Under the Hood: Exactly how prompts influence a model's response. Common Prompting Techniques: An honest look at what works today, including: -- Few-Shot & Clear Zero-Shot -- Persona-based & General Knowledge -- Chain-of-Thought (CoT) & Zero-Shot CoT -- Complexity-based & Least-to-Most -- Directional Stimulus -- Self-Refine & Chain of Verification (CoVe) -- ReAct & Meta Prompting Best practices and misconceptions of Prompting Jump straight to the topic or technique you want to master using the timestamps below! Chapters: 00:00 Introduction 00:30 What is Prompt Engineering 01:35 How Prompts influence the Model Response 04:10 Family of Models 06:56 Common Techniques and their effectiveness 14:53 Best Practices for crafting Prompts 18:07 Misconceptions - What is not true about Prompting #promptengineering #LLM #learnai #aifundamentals #TechnologyDebunk #bestpractices