Prompt Engineering Strategies   26-slide PPT PowerPoint presentation slide deck (PPTX)
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Prompt Engineering Strategies (PowerPoint PPTX Slide Deck)

PowerPoint (PPTX) 26 Slides FlevyPro Document

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This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
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This product (Prompt Engineering Strategies) is a 26-slide PPT PowerPoint presentation slide deck (PPTX), which you can download immediately upon purchase.

"Prompt Engineering" is the art and science of writing the prompt to elicit the desirable or useful results from the Artificial Intelligence (AI) tool you are using. In Prompt Engineering, the description of the task is embedded in the input, e.g., as a question instead of it being implicitly given.

Like in most processes and systems, the quality of the inputs determines the quality of the outputs—i.e., garbage in, garbage out. With ChatGPT, other generative AI applications, and similar prompt-based AI models, the input is the prompt. Thus, it is imperative that the user write a well-crafted and articulated prompt to generate the highest quality, most desired output. Designing effective prompts increases the likelihood that the model will generate the most favorable and contextual response.

Prompt Engineering typically works by converting one or more tasks to a prompt-based dataset and training a language model with what has been called "prompt-based learning" or just "prompt learning."

This PowerPoint presentation explains 5 Prompt Engineering Strategies you can leverage to maximize the effectiveness of your prompts (when using ChatGPT and other prompt-based AI tools):

1. RTF (Role-Task-Format)
2. Chain of Thought (CoT)
3. RISEN Framework
4. RODES Framework
5. Chain of Density (CoD)

These Prompt Engineering frameworks allow for personalized and adaptive AI interactions, leading to superior Customer Experiences and increased Customer Satisfaction. Well-crafted prompts reduce the need for repetitive adjustments or manual interventions, leading to decreased operational costs.

Using standardized frameworks facilitates training and onboarding, allowing businesses to scale ChatGPT or other AI implementations smoothly across various departments or functions. Within this presentation, each Prompt Engineering Strategy is discussed in detail, including use cases and examples.

For background and context, this presentation also includes introductions to ChatGPT and Prompt Engineering. It also includes slide templates for you to use in your own business presentations.

This presentation also offers a comprehensive Slide Structure & Design Guide to enhance your business presentations. Utilize these guidelines to maintain consistency and professionalism across all your slides.

Got a question about the product? Email us at flevypro@flevy.com.

Source: Best Practices in ChatGPT, Prompt Engineering PowerPoint Slides: Prompt Engineering Strategies PowerPoint (PPTX) Presentation Slide Deck, LearnPPT Consulting

PPT SLIDE DEEP DIVES

Optimizing AI Interactions: Five Prompt Engineering Frameworks

Optimizing AI Outputs through Effective Prompt Engineering

Optimizing ChatGPT: The RISEN Framework Explained

Optimizing ChatGPT: The RISEN Framework Explained

This PPT slide presents the RISEN framework, a structured approach designed to optimize the utilization of ChatGPT's capabilities. It outlines 5 key components: Role, Instructions, Steps, End Goal, and Narrowing. Each element serves a specific purpose in guiding the AI to produce relevant and focused outputs.

The Role section emphasizes the importance of clearly defining ChatGPT's persona, which dictates the tone and depth of the responses. This clarity ensures that the AI aligns with the user's expectations and context. Instructions follow, where detailed guidance is provided on how to approach the task at hand. This step is crucial for setting the parameters of engagement.

Steps outline a chronological breakdown of the problem-solving process, ensuring that the AI follows a logical progression. The End Goal specifies the desired outcome, which is essential for measuring the effectiveness of the interaction. Finally, the Narrowing component introduces constraints that help filter out unnecessary information, refining the focus of the output.

Case examples illustrate the practical application of the RISEN framework. For instance, using ChatGPT for competitive analysis involves directing it to assess market strengths and weaknesses, while operational efficiency tasks may require a focus on supply chain processes. Strategy formulation showcases how the framework can guide the AI in crafting comprehensive growth plans.

The prompt example further contextualizes the framework by demonstrating how to engage ChatGPT in developing an entry strategy for a specific market. Overall, the RISEN framework is positioned as a meticulous blueprint that ensures AI outputs are aligned with overarching business objectives, enhancing decision-making processes.

Optimizing ChatGPT Interactions with the Chain of Density


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