The No Nonsense Deep Dive Into Llm Prompt Engineering For People Who Don T Know Sh T About It


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The No-Nonsense, Deep Dive into LLM Prompt Engineering for People Who Don’t Know Sh*t About It


The No-Nonsense, Deep Dive into LLM Prompt Engineering for People Who Don’t Know Sh*t About It

Author: Timothy E. Bates The Godfather of Tech

language: en

Publisher: GrowBig Digital

Release Date:


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Alright, let's cut to the chase. The No-Nonsense, Deep Dive into LLM Prompt Engineering for People Who Don’t Know Sh*t About It is your all-access pass to understanding AI. This guide isn’t some techie jargon-filled manual for coders—it’s for the real backbone of our world: the skilled workers, the tradespeople, the folks who get things done. If you can flip a burger, fix a pipe, or cut a mean fade, you’ve got the skills to handle AI. I’m here to show you how. I break down prompt engineering—the art of asking AI the right way—to help you unlock serious power, whether you want to supercharge your side hustle or streamline your workday. Think of it as learning the ten levels of AI jiu-jitsu, from basic prompts like “tell me a joke” to full-blown, multitasking commands that make the AI work for you. You’ll be using tools like prompt chaining and context-priming (don’t worry, I make it all crystal clear) to take your AI interactions from basic to boss-level. And yeah, I throw in a lot of real-talk, because AI doesn’t have to be complicated. Imagine telling AI to “fetch” like a well-trained dog or asking it to juggle tasks like a circus performer. It’s about making AI work the way you need it to, not the other way around. By the end, you’ll know how to make AI practically sing your tune, and you’ll be equipped to sidestep common pitfalls, from vague prompts to ethical missteps. This guide is built to grow with you, just like AI itself. So, roll up your sleeves, get comfortable, and let’s dive into making AI your next go-to tool.

LLM Prompt Engineering For Developers


LLM Prompt Engineering For Developers

Author: Aymen El Amri

language: en

Publisher: Independently Published

Release Date: 2023-09


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A practical approach to Prompt Engineering for developers. Dive into the world of Prompt Engineering agility, optimizing your prompts for dynamic LLM interactions. Learn with hands-on examples from the real world and elevate your developer experience with LLMs. Discover how the right prompts can revolutionize your interactions with LLMs. In "LLM Prompt Engineering For Developers," we take a comprehensive journey into the world of LLMs and the art of crafting effective prompts for them. The guide starts by laying the foundation, exploring the evolution of Natural Language Processing (NLP) from its early days to the sophisticated LLMs we interact with today. You will dive deep into the complexities of models such as GPT models, understanding their architecture, capabilities, and nuances. As we progress, this guide emphasizes the importance of effective prompt engineering and its best practices. While LLMs like ChatGPT (GPT-3.5 and GPT-4) are powerful, their full potential is only realized when they are communicated with effectively. This is where prompt engineering comes into play. It's not simply about asking the model a question; it's about phrasing, context, and understanding the model's logic. Through chapters dedicated to Azure Prompt Flow, LangChain, and other tools, you'll gain hands-on experience in crafting, testing, scoring and optimizing prompts. We'll also explore advanced concepts like Few-shot Learning, Chain of Thought, Perplexity and techniques like ReAct and General Knowledge Prompting, equipping you with a comprehensive understanding of the domain. This guide is designed to be hands-on, offering practical insights and exercises. In fact, as you progress, you'll familiarize yourself with several tools: openai Python library: You will dive into the core of OpenAI's LLMs and learn how to interact and fine-tune models to achieve precise outputs tailored to specific needs. promptfoo: You will master the art of crafting effective prompts. Throughout the guide, we'll use promptfoo to test and score prompts, ensuring they're optimized for desired outcomes. LangChain: You'll explore the LangChain framework, which elevates LLM-powered applications. You'll dive into understanding how a prompt engineer can leverage the power of this tool to test and build effective prompts. betterprompt: Before deploying, it's essential to test. With betterprompt, you'll ensure the LLM prompts are ready for real-world scenarios, refining them as needed. Azure Prompt Flow: You will experience the visual interface of Azure's tool, streamlining LLM-based AI development. You'll design executable flows, integrating LLMs, prompts, and Python tools, ensuring a holistic understanding of the art of prompting. And more! With these tools in your toolkit, you will be well-prepared to craft powerful and effective prompts. The hands-on exercises will help solidify your understanding. Throughout the process, you'll be actively engaged and by the end, not only will you appreciate the power of prompt engineering, but you'll also possess the skills to implement it effectively.

Prompt Engineering for LLMs


Prompt Engineering for LLMs

Author: John Berryman

language: en

Publisher: "O'Reilly Media, Inc."

Release Date: 2024-11-04


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Large language models (LLMs) are revolutionizing the world, promising to automate tasks and solve complex problems. A new generation of software applications are using these models as building blocks to unlock new potential in almost every domain, but reliably accessing these capabilities requires new skills. This book will teach you the art and science of prompt engineering-the key to unlocking the true potential of LLMs. Industry experts John Berryman and Albert Ziegler share how to communicate effectively with AI, transforming your ideas into a language model-friendly format. By learning both the philosophical foundation and practical techniques, you'll be equipped with the knowledge and confidence to build the next generation of LLM-powered applications. Understand LLM architecture and learn how to best interact with itDesign a complete prompt-crafting strategy for an applicationGather, triage, and present context elements to make an efficient promptMaster specific prompt-crafting techniques like few-shot learning, chain-of-thought prompting, and RAG