This AI Skill Will Put You Ahead of 98% of People
AI Nuggets
Detailed Instructions, CLI Commands, Website URLs, and Tips from the Video Transcript
Must-Know Principles
- Context: Provide enough context for the AI.
- Relevance: Avoid including irrelevant information.
- Persistence: If the first prompt fails, try again.
- Simplicity: Break complex tasks into smaller steps.
- Clarity: Use visual clarity in prompts, such as Markdown formatting.
- Repetition: Repeat important elements within the prompt.
- Role-Playing: Assign the AI a role to improve results.
- Emotional Stimuli: Add an emotional story to influence the AI’s responses.
How to Implement This in Your Prompt
- Pre-Made Prompts: Access pre-made prompts in the community (link in the description).
- Role-Playing Example: Instead of a generic request, assign the AI a role, like a doctor, to get more relevant answers.
- Repetition Example: Highlight important rules multiple times within the prompt.
- Formatting Example: Use Markdown to organize the prompt into sections like task, information, rules, and AI personality.
- Multiple Choice Tip: Avoid giving the AI multiple choices to prevent hallucinations; let it reason out the answer.
Fundamentals of Prompting
- Few-Shot Learning: Provide examples to guide the AI.
- Zero-Shot Learning: Avoid not providing examples.
- Chain of Thought: Break down complex problems into intermediate steps.
- Prompt Chaining: Decompose a task into manageable subtasks with individual prompts.
Level Up Your Prompts
- Few-Shot vs. Zero-Shot: Provide context and examples for better recommendations.
- Chain of Thought: Add a step-by-step reasoning request to improve complex problem-solving.
- Prompt Chaining Examples: Use multiple prompts for tasks like code review or writing help.
Intermediate Prompt Engineering
- Rephrase and Respond: Have the AI rephrase your question before answering.
- Generate Questions: Ask the AI to generate questions to better assess a situation.
Tree of Thought
- Tree of Thought: Explore multiple thought processes and backtrack to find unique solutions.
Retrieval Augmented Generation (RAG)
- RAG Steps: Search, Understand, and Generate using external information.
Tool Use with LLMs
- External Tools: Allow the LLM to use external tools or programs to enhance its capabilities.
- Examples of Tools: Code interpreter, document readers, and more.
Directional Stimulus Prompting (DSP)
- DSP: Add subtle elements to guide the AI’s response style and format.
Advanced Modules
- Modules 7 and 8: Exclusive to community members (link in the description).
Community and Further Learning
- Join the Community: For access to advanced modules, prompt templates, courses, workshops, and a network of AI enthusiasts (first link in the description).
Please note that the video transcript did not contain any specific CLI commands or complete exact URLs. The instructions and tips provided are based on the principles of prompt engineering as discussed in the video. The community and additional resources are mentioned to be available through a link in the video description, which is not provided in the transcript.