My name is Joey and I AM A PRMPTENGINEER !!!

Dear Readers....and fellow PrmptEngineers !

I’m writing this blog to both educate and inspire you, the reader. What I hope you’ve gathered so far is that I’m a true AI enthusiast. Most of my evenings are spent either learning about AI or, when my brain needs a break, creating content with AI tools. That said, it’s important to me that this blog isn’t just about my AI journey—it’s about helping you on yours too. So, I’d be remiss if I didn’t provide a structured learning path for you to follow.

Below, I’ve laid out a proposed course that I’ll be taking you through step by step. Along the way, we’ll take breaks to explore other relevant topics, but I truly believe that if you're reading this blog and you're passionate about AI, we need to "up-skill" together.

Without further ado, I present to you... a not-so-mini course in AI mastery.

Why focus on agents?

Because prompt writing doesn’t exist in a vacuum. Sure, you can throw in your AirPods and chat with AI for hours (trust me, I’ve done that), but if we’re not building a strong foundation, pushing the boundaries of what’s possible, or exploring the latest cutting-edge platforms, we’re missing out. And yes, by the time we complete this course, some of the tools may be outdated or replaced by something better—that’s okay! The value lies in the learning process and the skills we’ll develop.

Now, before you say, “But Joey, this looks like a tough curriculum!” let me stop you right there. I’ll be doing this with you. And yes, by the end of the course, we will all be PromptEngineers, equipped with an amazing skill set that’s ready for whatever comes next.

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An AI Agent Builder Course Curriculum

Module 1: Introduction to AI Agents and No-Code Tools

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Introduction to AI Agents:

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Define AI agents and explain their key characteristics, such as autonomy, goal-orientation, and ability to interact with their environment

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Explore different types of AI agents, including task-oriented agents, conversational agents, and multi-agent systems.345

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Discuss real-world applications of AI agents, emphasizing their potential impact on businesses and industries.1345...

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Introduction to No-Code AI Agent Platforms:

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Introduce platforms like Relevance AI, Make.com, and Replit as tools for building AI agents without writing code.

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Explain the benefits of using no-code platforms, including faster development, reduced complexity, and accessibility for non-programmers.

Module 2: Building Basic AI Agents

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Understanding Prompts and Agent Roles:

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Explain the concept of prompts and how they define an AI agent's behavior and objectives.

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Explore the different types of prompts, including system prompts, role prompts, and task prompts.

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Practice crafting effective prompts that clearly communicate the agent's role, context, and desired actions.

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Creating Simple Agents with Relevance AI:

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Walk through the steps of creating a basic agent in Relevance AI, including defining the agent's profile, system prompt, and flow.

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Introduce the concept of tools and how they extend an agent's capabilities.

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Build a simple agent with basic functionality, such as responding to user queries based on a predefined knowledge base.1

Module 3: Integrating Tools and External Services

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Connecting Agents to Softwares:

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Explain how to connect AI agents to external services using tools and APIs.

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Introduce Make.com as a platform for creating custom integrations between AI agents and various softwares.

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Walk through examples of integrating agents with tools like Google Docs, Google Calendar, Notion, Slack, and social media platforms.

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Discuss the importance of software integrations for building agents that can automate real-world tasks.

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Building Agents with Multiple Tools:

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Demonstrate how to build agents that leverage multiple tools to accomplish more complex tasks.

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Explain how to chain tools together to create sequential workflows.

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Build a more sophisticated agent that integrates with multiple tools, such as an agent that can research leads, scrape competitor data, and generate reports.

Module 4: Advanced Agent Building Techniques

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Multi-Agent Systems:

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Introduce the concept of multi-agent systems, where multiple agents collaborate to achieve a common goal.

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Explain the benefits of using multi-agent systems, such as improved reliability, modularity, and ability to handle complex workflows.

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Walk through the process of creating and managing a team of agents in Relevance AI, including assigning roles and responsibilities to each agent.

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Build a multi-agent system for a real-world use case, such as a content repurposing team that can automatically generate and post content across different social media platforms.

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Retrieval Augmented Generation (RAG):

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Explain the concept of RAG and how it allows agents to access and process information from external knowledge bases.

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Introduce LangChain as a library for implementing RAG functionality in Python.

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Walk through the steps of building a RAG-powered agent, including creating a vector database and integrating with tools for document retrieval.

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Build an agent that can answer user queries based on information from a specific set of documents.

Module 5: Pushing the Boundaries of AI Agent Development

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Custom Function Calling with OpenAI's o1:

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Explain the limitations of the o1 beta preview, particularly the lack of native tool calling and function calling support.

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Demonstrate how to implement custom function calling for o1 using Python and LangChain, enabling the agent to interact with external APIs.

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Discuss the potential of o1 as a powerful reasoning engine for AI agents, highlighting its ability to handle complex tasks and troubleshoot errors.

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Flow Engineering and the Future of AI Agents:

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Introduce the concept of flow engineering as the strategic combination of different AI agent building techniques.

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Explore how to combine system one and system two level thinking LLMs, tools, logic, and multi-agent systems to create robust and scalable agent workflows.

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Discuss the potential of flow engineering for building AI agents that can automate increasingly complex processes and contribute significantly to business automation.

Throughout the course, students would be encouraged to develop their own AI agent projects, starting with simple applications and gradually progressing to more complex systems. The course would also provide guidance on how to identify potential use cases for AI agents in various business settings, highlighting the practical applications of the skills learned.

PS. At the time of writing this, I am in Tampa Florida, it's 10/10 and we just got hit by Hurricane Milton. For those of you who read my blog Milton is one of my favorite therapists one of my super therapists. So it is an important name to me personally. I believe that when life gives you lemons make lemonade, and so at the height of the hurricane when we had no power or water (we still have no power or water) I thought I would create images of the hurricane and at the very least create an instagram post... and you can check out my instagram account : https://www.instagram.com/joey_powers8 . With respect to those who've lost their lives, been damaged or suffered because of Hurricane Milton - I dedicate this blog post. Take adverse conditions or events and if you can make something good out of them. An adverse event doesn't always only result in adverse outcomes !