Chatvolt

The speaker read, studied, and tested techniques from 35 scientific articles from various well-known companies and researchers to create effective prompts. The research involved analyzing language models and creating automated tasks for his company and students.

The speaker utilized the learned techniques in his company to automate tasks, resulting in thousands of uses. He became the first AI advisor for companies in Brazil, combining extensive research and practical application in the field of artificial intelligence.

The speaker promises to teach participants how to maximize language models effectively in a simple, direct, and practical manner, catering to beginners and advanced users alike. The masterclass aims to enhance understanding and application of prompt engineering.

The speaker outlines the seven modules of the masterclass, recommending sequential completion but allowing for flexibility. The modules cover basic principles of prompt engineering, recommended processes, techniques, practical examples, and recommended tools.

Prompt engineering is highlighted as a crucial meta-skill that unlocks other abilities in tasks involving language models. The speaker emphasizes the importance of prompt engineering in achieving desired results and building confidence in using language models effectively.

The speaker explains the significance of starting with simple prompts before gradually advancing to more complex ones. He emphasizes the importance of starting with high-quality models and gradually refining prompts to optimize results.

The speaker introduces a basic structure for prompts using the acronym 'PROMPT,' covering Persona, Scenario, Objectives, Model type, Panorama, and Transform. This structure serves as a foundation for developing effective prompts.

The speaker emphasizes the importance of clear instructions and starting with expensive models for better performance. He recommends developing test cases to refine prompts, iteratively improving prompt quality, and transitioning to production once refined.

Markdown is introduced as a valuable tool for structuring text effectively, enhancing communication with language models, and improving response accuracy. The speaker demonstrates various Markdown formatting options and their impact on prompt effectiveness.

Explaining the importance of modifying prompts for better model results by providing examples and tips on formatting for easier manipulation and interpretation.

Discussing the challenges of working with long documents and providing tips on structuring them effectively using XML tags and position placement for model instructions.

Exploring the concept of system prompts to guide model behavior and improve results, emphasizing the importance of providing specific instructions and examples.

Introducing the zero shot technique where models are prompted without examples, highlighting the effectiveness of using this approach to improve responses.

Explaining the concept of training models with directional prompts to enhance results, showcasing how providing examples and guidance helps in generating better outcomes.

Delving into research studies on prompt techniques, specifically focusing on directional prompts and their impact on model performance.

The speaker discusses applications and advanced testing utilizing the concept of a thought skeleton for real-life applications.

Exploration of the thought skeleton concept applied by researchers from China, the United States, Belgium, and other countries, focusing on structured thinking and decision-making processes.

Using the thought skeleton technique in marketing implementation to enhance decision-making processes and brainstorming for developing better ideas and arguments.

Utilizing the thought skeleton to explore ideas and generate suggestions, enhancing brainstorming sessions and improving argumentation with factual evidence and information.

Continual improvement and development using the thought skeleton to detail technical definitions, develop metaphors, and suggest branding strategies.

Integrating language programming techniques into language models for text creation, using variables and structured templates for efficient copywriting.

Developing sophisticated agents to execute complex tasks by breaking them down into multiple steps and subtasks for enhanced decision-making processes.

Strategies to prevent hallucinations in AI-generated content, including setting temperature levels, requesting citations or insights, and ensuring consistency in responses.

Demonstration of creating a complex prompt for generating landing pages using conversational AI agents and customizing prompts for detailed outputs.

Application of programming language techniques in language models for text generation, using variables and structured templates to streamline content creation.

Programming actions and observations in language prompts to guide AI agents in sequential decision-making processes for tackling complex tasks.

Discussion on adding external knowledge sources to language models for enhanced responses, focusing on incorporating external data to improve AI-generated content.

Strategies for preventing hallucinations in AI-generated content, such as providing factual content, using citations, and prompting for accurate responses to enhance content quality.

Techniques for personalizing AI responses and ensuring consistency by requesting multiple responses and developing a consensus for accurate outputs.

Detailed explanation of the structure of the prompt used, including its length, protection methods, and key components for interaction with the user.

Discussion on a commonly used GPT Store template without protection, highlighting the importance of basic protection measures for prompts.

Explanation of basic protection measures implemented in the prompt, such as avoiding specific actions and instructions to maintain confidentiality.

Introduction of an extra file for knowledge reference within the prompt structure to enhance response quality and accuracy.

Detailed breakdown of the step-by-step process followed in the prompt, emphasizing user interaction and problem-solving approach.

Explanation of using markdown formatting in the prompt, including creating clickable links and incorporating images for visual enhancements.

Guidelines for improving response generation quality by providing detailed client information, verifying offer details, and structuring responses systematically.

Transition to JSON format for organizing information in prompts to ensure accuracy, consistency, and facilitate better understanding for the AI model.

Benefits of converting long prompts into JSON format for improved AI model comprehension and effective response generation.

Guidance on utilizing external files, such as converting markdown to JSON format to enhance AI model performance and response accuracy.