In this video, I explore the powerful combination of meta-prompting and chain prompting to help you get inside your AI's mind and improve its responses. Discover how to construct prompts that create a feedback loop, allowing your AI to express uncertainties, concerns, and missing information, ensuring you get the best possible answers. I break down the process into four main components: setting profile and expertise, assigning responsibilities, structuring the prompt, and providing simulated examples. By the end of this tutorial, you'll be equipped to tailor prompts for any use case and enhance your AI's performance. Perfect for AI enthusiasts and developers aiming to refine their conversational AI capabilities.

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👋 About Me: Hello! I'm Mark, a seasoned Data Science Manager by day and an AI automation agency owner by night, hailing from Canada with a decade in the AI space. At Prompt Advisers, we specialize in cutting-edge AI solutions, helping individuals, businesses, and agencies fully harness applied AI. Having been featured in interviews and recognized for our innovative contributions, we're dedicated to guiding you through the AI landscape.

🚀 My Goal: My mission is to empower you with the knowledge to explore AI technology in your ventures, whether you're an individual, a business, or an agency. I aim to help you leverage applied AI to its fullest potential, providing insights, sharing experiences, and offering partnerships to bring your visions to life.

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#Metaprompting #ChainPrompting #AIEnhancement #TechTutorial #ArtificialIntelligence #PromptEngineering #GPT4 #AIAgents #ConversationalAI #FeedbackLoop #airesponses

TIMESTAMPS ⏳

0:00 - Introduction: Frustration with AI responses.
0:07 - Combining meta prompting and chain prompting.
0:16 - Meet Mark: AI agency and experience.
0:30 - Conceptual overview: Feedback loop for better AI responses.
0:50 - Understanding what your AI needs.
1:00 - Four main components of a good prompt.
1:05 - Component 1: Setting profile and expertise.
1:19 - Component 2: Responsibility assignment.
1:30 - Component 3: Prompt response structure.
1:50 - Component 4: Simulated examples for better understanding.
2:17 - Prompt structure breakdown.
2:24 - Requesting clarification for vague user inputs.
2:34 - Direct answers for simple questions.
2:51 - Outlining reasoning for detailed answers.
3:06 - Example prompt overview.
3:36 - Step-by-step breakdown of example prompt.
4:00 - Key sections: Profile, expertise, and reasoning.
5:00 - Creating a transparent feedback loop with AI.
6:00 - Providing example interactions to improve AI responses.
6:43 - Importance of varied examples for AI generalization.
7:10 - Demo: Creating a study buddy for Canadian history.
8:10 - Using GPT to generate five example conversations.
8:30 - Final prompt overview: Tailored AI interactions.
9:30 - Testing the prompt with GPT.
10:00 - Understanding AI reasoning and doubts in responses.
11:00 - Conclusion: Improving AI interaction over time.

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