Why Your Prompts Fail (Transformers in AI) скачать в хорошем качестве

Why Your Prompts Fail (Transformers in AI)

🎥 ✅ 🔥 FREE Youtube Course to transitioning from a UX Designer → Design Engineer in the AI era. :    • UX Designer to Design Engineer in AI era   Many people struggle with AI tools like ChatGPT, Cursor, and other LLMs because their prompts produce generic or incorrect results. In this video, we explain why your prompts fail by breaking down the core concepts behind transformers in AI and self-attention, the architecture that powers modern large language models. If you’re a designer, developer, or product manager doing vibe coding or prompt engineering, understanding how AI reads context, tokens, and instructions will help you write better prompts and get more accurate responses from AI systems. ┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈┈ 📌 LINKS ▶️ Main Channel: / @designwithdonkeys 📸 Instagram: instagram.com/designwithdonkeys 𝕏 Twitter : x.com/designwithdnkys ⏱ Timestamps 0:00 Introduction 0:07 Why Designers Must Understand Transformers 1:02 What Is Self-Attention? (Simple Explanation) 2:03 How AI Decides Which Words Matter 2:32 How Transformer Architecture Works 5:03 Why Vibe Coding Often Fails 7:17 Why Word Order Matters in Prompts 9:44 A Bad Prompt Example 10:53 How to Write a Better Prompt 12:27 How Self-Attention Improves Prompts 14:15 Key Takeaways for Better Prompting