IndyDevDan | MASTER the Prompt: TOP 5 Elements for Reusable Prompts, AI Agents, Agentic Workflows @indydevdan | Uploaded June 2024 | Updated October 2024, 3 hours ago.
Is your prompt even GOOD? Unlock the Secrets to High-Quality Prompts: WITH 20% EFFORT.
Ever wondered which parts of your prompts ACTUALLY MATTER? Let's simplify the sea of prompt engineering tips and tricks with this concise guide on the five essential elements that gives you 80% of the results with 20% of the effort. I've crafted thousands of prompts, and today, I'm sharing the key elements that consistently deliver top-notch outcomes with minimal effort.
🚀 Discover the five crucial components: model, purpose, variables, examples, and output. These elements form the backbone of effective prompt engineering, helping you achieve 80% of the results with just 20% of the effort.
🔗 These elements enable composability between prompts, allowing you to chain together outputs and inputs to build powerful prompt chains. By focusing on the underlying technology and understanding the prompt at its core, you'll be well-equipped to create AI Agents and agentic workflows.
🔥 In this video, we break down each element with clear examples and practical tips:
Model: Learn why the model you choose has the most significant impact on your prompt's performance.
Purpose: Understand how a clear goal enhances your prompt's effectiveness.
Variables: Master the use of dynamic and static variables to make your prompts adaptable and reusable.
Examples: See how concrete examples can guide your AI to produce the exact output you need.
Output: Explore the importance of structured outputs, like JSON, for building reliable and consistent AI workflows.
🛠️ We'll showcase practical applications of these elements through detailed examples, including a Nuxt.js component and a comprehensive Omnicomplete prompt. Whether you're a developer, AI enthusiast, or product builder, this video is packed with actionable insights to enhance your prompt engineering skills.
🌟 Hit the like and subscribe for more tips on AI agents, agentic workflows, and prompt chains. Stay ahead of the curve and stay plugged into the latest models like GPT-4o, Gemini 1.5 Pro, and other state-of-the-art models to use their full potential for your prompts, AI Agents, and agentic workflows.
Keep prompting, keep building and stay ahead of the curve.
🔗 Resources
Llama-3 70b Omnicomplete: youtu.be/28zuliyLd5Q
LLM OS: youtu.be/8wSH4XukcH8
7 Prompt Chains: youtu.be/QV6kaNFyoyQ
📖 Chapters
00:00 Maximizing Prompt Value
00:34 The Five Key Elements of Prompts
01:24 E1 - Model - Why the Model Matters Most
01:59 E2 - Purpose - Defining Your Goal
02:25 E3 - Variables - Dynamic and Static
03:32 E4 - Examples - Concrete Examples for Clarity
05:49 E5 - Output - Structured and Reliable JSON
07:16 Concise, valuable, reusable prompts
08:00 Building Prompt Chains and AI Agents
08:56 Recap - The 80-20 of Prompt Engineering
09:48 Real Example Prompt - OmniComplete - Static Variables
12:20 Real Example Prompt - Nuxt / Vue Component
13:53 Top 5 Elements for Reusable Prompts
14:30 Focus on the groundwork - the prompt
#promptengineering #aiagents #aiengineering
Is your prompt even GOOD? Unlock the Secrets to High-Quality Prompts: WITH 20% EFFORT.
Ever wondered which parts of your prompts ACTUALLY MATTER? Let's simplify the sea of prompt engineering tips and tricks with this concise guide on the five essential elements that gives you 80% of the results with 20% of the effort. I've crafted thousands of prompts, and today, I'm sharing the key elements that consistently deliver top-notch outcomes with minimal effort.
🚀 Discover the five crucial components: model, purpose, variables, examples, and output. These elements form the backbone of effective prompt engineering, helping you achieve 80% of the results with just 20% of the effort.
🔗 These elements enable composability between prompts, allowing you to chain together outputs and inputs to build powerful prompt chains. By focusing on the underlying technology and understanding the prompt at its core, you'll be well-equipped to create AI Agents and agentic workflows.
🔥 In this video, we break down each element with clear examples and practical tips:
Model: Learn why the model you choose has the most significant impact on your prompt's performance.
Purpose: Understand how a clear goal enhances your prompt's effectiveness.
Variables: Master the use of dynamic and static variables to make your prompts adaptable and reusable.
Examples: See how concrete examples can guide your AI to produce the exact output you need.
Output: Explore the importance of structured outputs, like JSON, for building reliable and consistent AI workflows.
🛠️ We'll showcase practical applications of these elements through detailed examples, including a Nuxt.js component and a comprehensive Omnicomplete prompt. Whether you're a developer, AI enthusiast, or product builder, this video is packed with actionable insights to enhance your prompt engineering skills.
🌟 Hit the like and subscribe for more tips on AI agents, agentic workflows, and prompt chains. Stay ahead of the curve and stay plugged into the latest models like GPT-4o, Gemini 1.5 Pro, and other state-of-the-art models to use their full potential for your prompts, AI Agents, and agentic workflows.
Keep prompting, keep building and stay ahead of the curve.
🔗 Resources
Llama-3 70b Omnicomplete: youtu.be/28zuliyLd5Q
LLM OS: youtu.be/8wSH4XukcH8
7 Prompt Chains: youtu.be/QV6kaNFyoyQ
📖 Chapters
00:00 Maximizing Prompt Value
00:34 The Five Key Elements of Prompts
01:24 E1 - Model - Why the Model Matters Most
01:59 E2 - Purpose - Defining Your Goal
02:25 E3 - Variables - Dynamic and Static
03:32 E4 - Examples - Concrete Examples for Clarity
05:49 E5 - Output - Structured and Reliable JSON
07:16 Concise, valuable, reusable prompts
08:00 Building Prompt Chains and AI Agents
08:56 Recap - The 80-20 of Prompt Engineering
09:48 Real Example Prompt - OmniComplete - Static Variables
12:20 Real Example Prompt - Nuxt / Vue Component
13:53 Top 5 Elements for Reusable Prompts
14:30 Focus on the groundwork - the prompt
#promptengineering #aiagents #aiengineering
