Overview The 5C Framework for prompt engineering is designed to guide users in crafting effective prompts that optimize AI model responses. It consists of five key components: Clarity, Contextualization, Command, Chaining, and Continuous Refinement. This framework helps in systematically approaching
Develop personalized and interactive digital doppelgangers with our comprehensive framework. Enhance customer service, executive communication, and consulting while ensuring security, privacy, and cultural sensitivity.
Learn how to inject domain-specific knowledge into LLMs for medicine, law, finance & more. Explore two powerful frameworks: fine-tuning + prompting and prompt engineering with examples.
Time's Secrets: The Temporal Knowledge Graph Prompt Engineering (TKGP) framework empowers language models to analyze time-dependent data in legal, medical, financial, and historical domains, uncovering hidden connections and generating deeper insights.
Discover the role of the prompt engineering layer in generative AI, optimizing interactions and workflows. See how Make.com and Zapier simplify integration, enabling scalable AI solutions with GPT-4 and Claude. Learn more at PromptEngineering.org.
Explore how AI, specifically language models like ChatGPT, is reshaping our work and creativity without replacing the unique qualities that make us human. Learn strategies for integrating AI ethically and effectively to enhance capabilities and maintain a human-centric approach.
Explore our innovative framework that utilizes LLMs for educational storytelling, designed to simplify complex concepts for non-experts.
Discover how the Emotional Intelligence (EI) Graph provides a structured approach to developing and regulating emotional intelligence skills. Learn about EI Clusters, Cognitive Chains, and Nodes, and how they work together to support personal growth and well-being.
The OPUS Framework enables the creation of high-quality, relevant AI-generated content through a structured approach to crafting effective prompts from initial observations.
Best practices for implementing AI in healthcare, drawing on lessons learned for a safe, effective, and patient-centered approach.
Guide to implementing AI for demand generation with steps to integrate tools, personalize engagement, map customer journeys, gather feedback and drive continuous optimization. Ideal for marketers aiming to boost efficiency.
The ADAPT methodology: an approach that can Large Language Models' performance in complex decision-making tasks through dynamic task decomposition and planning.