why you suck at prompt engineering (and how to fix it)
AI Summary
Summary: Prompt Engineering for AI Systems
Introduction
- Many people struggle with prompt engineering, which is crucial for building effective AI systems.
- The video aims to improve prompt engineering skills and understanding.
Common Mistakes
- People often overcomplicate AI tasks, falling into a “midwit” trap.
- Simple solutions are sometimes the best, as demonstrated by the “midwit” meme.
Importance of Prompt Engineering
- Good prompt engineering directly impacts the value derived from language models (LLMs).
- Mastery of prompt engineering can lead to success in the AI space.
Personal Context
- The presenter is a businessman, not just a YouTuber, using YouTube to attract clients.
- He emphasizes the importance of working on his business and building software.
Conversational vs. Single Shot Prompting
- Conversational prompting is forgiving and good for personal use.
- Single shot prompting is for automated systems and is less forgiving but more scalable.
The Perfect Prompt Formula
- The formula includes role, task, specifics, context, examples, and notes.
- Each component is backed by research, improving prompt accuracy and performance.
Components of the Prompt Formula
- Role: Assign an advantageous role to the AI, increasing accuracy.
- Task: Be descriptive, using verbs to define the AI’s task.
- Specifics: Provide additional instructions and emotional stimuli to enhance performance.
- Context: Give context about the business and system, reinforcing the role and task.
- Examples: Use input-output pairs to teach the AI the desired response format.
- Notes: Add reminders or tweaks at the end of the prompt.
Markdown Formatting
- Use markdown to structure prompts, making them more readable and understandable for both humans and AI.
Considerations
- Keep context length short to reduce costs, especially for high-volume tasks.
- Choose the cheapest and fastest model that can successfully execute the task.
- Adjust temperature and other model settings based on the task’s needs.
Application Examples
- AI agents, voice agents, AI automations, and AI tools can all benefit from the prompt formula.
- Modify the formula based on the specific use case.
Conclusion
- Effective prompt engineering is essential for creating valuable AI systems.
- The skills taught can lead to a significant increase in AI performance and success in the AI industry.