Why Your AI Prompts Fail-A Taxonomy of LLM Prompting and Defect Strategies.

Is your AI assistant giving you unreliable, insecure, or just plain wrong answers? The problem might not be the model—it's your prompt. Great prompt engineering is the key to unlocking AI product success, but it's more than just "Chain-of-Thought" or telling the AI to "act as an expert".
This video goes beyond the basics to reveal the hidden world of prompt defects—recurring errors that cause Large Language Models (LLMs) like GPT-4 to fail. Drawing on systematic research, we'll explore a comprehensive taxonomy of these defects and give you actionable strategies to fix them.
???? WHAT YOU'LL LEARN IN THIS VIDEO:
• The 6 Critical Dimensions of Prompt Failure: We break down the official taxonomy of prompt defects, including flaws in Specification & Intent, Input & Content, Structure & Formatting, Context & Memory, and more.
• Real-World Examples of Bad Prompts: See concrete examples of how ambiguous instructions ("Make it better"), conflicting directives, and poor organization can confuse an LLM and lead to useless outputs.
• Advanced Prompting Strategies (Backed by Research): We'll touch on cutting-edge techniques like Tree of Thoughts (ToT), which enables exploration and lookahead reasoning, and Self-Consistency, which improves reliability by sampling diverse reasoning paths.
• Actionable Mitigation Techniques: For every defect, we provide proven remedies. Learn how to explicitly define output formats, use delimiters to prevent prompt injection, and manage context to avoid "forgotten instructions".
• From "Trial-and-Error" to Disciplined Engineering: Understand why prompt development must mature from an ad-hoc craft into a rigorous engineering discipline, complete with testing, debugging, and maintenance.
This isn't just another "Top 10 Prompts" list. This is a deep dive into the software engineering principles that make AI systems dependable by design. Whether you're a developer, a product manager, an AI enthusiast, or just tired of getting bad answers from your AI, this guide will change the way you think about prompt engineering.