AI Agent Architect

Building Intelligent Automations for Specific Needs

🧠 What Does “Comprehensive” Mean in This Context? This course is designed to provide you with a deep, practical understanding of AI Agents, covering three major levels of learning and skill development:

  • 📗 Level 1: Foundation – What Are AI Agents?
    • Definitions and core concepts (autonomy, tool use, memory, goals).
    • Examples of different Agent types (Custom GPTs, LangChain-inspired, AutoGPT concepts, embedded copilots).
    • Understanding where Large Language Models (LLMs) fit in – as the “brain” for language understanding, task planning, and tool invocation.
  • 📘 Level 2: Practice – Build Your Own (No-Code to Low-Code)
    • Step-by-step guidance to build your first AI Agent, specifically a Client Intake + Onboarding Assistant, using no-code platforms.
    • Accessible exploration of how agents are configured within frameworks like LangChain (via templates or simplified platforms) for a conceptual understanding of low-code builds.
    • Practical demonstrations of how Agents call and use external “tools” (e.g., browser for web search, simple API calls, internal calculators).
    • Hands-on exercises, visual walkthroughs, and prompt libraries to guide your building process.
  • 📙 Level 3: Application – Solve Real Problems
    • Strategies to design and apply Agents for specific real-world roles, leveraging lessons from our Client Intake + Onboarding Assistant build.
    • Guided examples demonstrating how to approach an Agent project from initial concept to a working solution.
    • Essential debugging tips, architectural planning considerations, and advanced LLM prompting best practices for Agent control and reliability.

🎯 Learning Outcomes By the end of this course, you will be able to:

  • Understand the anatomy of an AI Agent, recognizing the critical interplay of the LLM, memory, tools, and defined goals.
  • Confidently design, build, and iterate a purpose-built AI assistant, with a focus on the Client Intake + Onboarding Assistant as a practical example.
  • Master the use of:
    • ChatGPT’s Custom GPT builder for no-code Agent creation.
    • Conceptual understanding and practical application of simple Agent templates within accessible platforms (e.g., via Replit, Google Colab environments, or user-friendly Agent-building platforms).
    • Advanced LLM prompt chaining, system instructions, and effective tool setup for Agent control.
  • Effectively troubleshoot and evolve your Agent through iterative testing and refinement loops.
  • Apply Agent principles to solve a real-world business or creative task, transforming your approach to automation.

🧾 Course Modules

📘 Module 1: AI Agents Unveiled – Beyond the Conversational AI

  • Definition & Core Traits: What truly makes an AI an “Agent” (autonomy, goal-orientation, tool use, memory) compared to a simple chatbot.
  • The Agent’s “Brain”: Understanding the foundational concepts of memory, planning, and self-correction (reflection) in Agent systems.
  • Real-World Agent Examples: Exploring diverse applications from personal assistants to complex data analysis bots, including how an Intake Assistant would fit.
  • Why Agents Matter Now: Identifying the transformative potential for automation and problem-solving in various professional contexts.

🌐 Module 2: The Agent Ecosystem – Types, Architectures & Core Components

  • Categorizing AI Agents: A clear overview of different Agent types and their suitable use cases.
  • Core Agent Architectures: An accessible look at how Agents are structurally designed (e.g., sequential, iterative, modular designs).
     
  • LLM-Based Agent Frameworks (Overview): Introduction to major frameworks like LangChain, AutoGen, and CrewAI – focusing on their purpose and what they enable, not coding.
     
  • ChatGPT Custom GPTs: Deep dive into creating and configuring your own specialized GPTs (knowledge files, custom instructions, action-calling) – your primary no-code building environment.
  • Plugin & Connector-Based Agents: Introduction to platforms like Zapier or Voiceflow that enable agents to connect with other apps for more complex workflows like data storage for an Intake Assistant.
  • Embedded Agents: Understanding AI capabilities in familiar tools like Microsoft Copilot and Google Duet AI as nascent agents that could perform simple intake tasks.

💡 Module 3: Designing Your Agent – From Idea to Blueprint & Tools

  • Identifying Your Specific Use Case: Pinpointing a clear problem or task you want an Agent to solve – focusing on the Client Intake + Onboarding Assistant as our core example.
  • Defining Goals and Constraints: Setting precise objectives (e.g., “gather client contact info,” “explain service options”) and necessary boundaries (e.g., “do not offer medical advice”) for your Agent’s behavior.
  • Tool Selection & Integration Planning: What tools your Intake Assistant will need to interact with (e.g., a simple spreadsheet for data storage, an email sender) and how to prepare for those connections.
  • Data Flow & Processing: Understanding how data moves through an Agent, from intake to storage or action.

🛠️ Module 4: Hands-On: Building Your No-Code Agent (The Client Intake Assistant)

  • Creating a Custom GPT (Step-by-Step): Guided walkthrough on using ChatGPT’s interface to build the foundation of your Client Intake + Onboarding Assistant.
  • Populating Knowledge for Intake: Uploading relevant files (e.g., service brochures, FAQ documents) and defining custom instructions to give your Agent specific expertise.
  • Enabling Tool Use (Browse, Code Interpreter, File Upload): Configuring built-in tools within your Custom GPT to allow it to gather information or process simple data related to client intake.
  • Giving Your Agent Personality & Memory: Crafting instructions for a consistent, professional, and friendly tone for the Intake Assistant, and ensuring it retains conversation context during dialogue.

⚙️ Module 5: Running & Refining Your Agent – Monitoring, Debugging & Practical Applications

  • Monitoring Agent Behavior: Understanding how to observe and evaluate your No-Code Client Intake Assistant’s actions and conversational flows.
  • Troubleshooting & Debugging: Identifying common reasons why Agents (like our Intake Assistant) might get stuck or fail during a conversation, and how to fix them.
  • Iterative Improvement: Strategies for fine-tuning instructions, tools, and goals to optimize Agent behavior for smoother client interactions.
  • Real-World Applications (Case Studies): Analyzing additional successful Agent implementations beyond intake, including:
    • Email Triage & Draft Response Agent.
    • Automated Scheduling Assistant.
    • Product Research & Comparison Agent.

🚀 Module 6: Advanced Agent Concepts – Multi-Agent Systems & Conceptual Frameworks

  • Multi-Agent Systems: An introduction to how multiple Agents can work together to achieve more complex goals.
     
    • Concepts like Agent communication, collaboration, and roles within a team.
    • Examples of multi-agent systems in action (e.g., a team of Agents researching a topic from different angles).
  • Introduction to Agent Frameworks (Conceptual Dive): A deeper look at how tools like LangChain enable more complex Agent behaviors, using the Client Intake + Onboarding Assistant as a case study for potential advanced features.
     
  • Setting Goals & Planning Steps within a Framework: Understanding the underlying logic of how these Agents break down tasks, especially for multi-stage processes.
  • Adding Advanced Tools: Concepts of integrating specific external APIs for the Intake Assistant (e.g., direct CRM integration, sending automated welcome emails after intake).
  • The Human-in-the-Loop: Designing Agents that know when to ask for human intervention or confirmation, particularly crucial for sensitive client interactions.

⚖️ Module 7: Responsible Agent Use – Risks, Ethics, and The Future

  • When Not to Use Agents: Identifying scenarios where Agents (including our Client Intake Assistant) are inappropriate or too risky, especially with sensitive client data.
  • Understanding Agent Limitations: Hallucinations, unexpected behavior, and resource consumption, with examples relevant to data collection.
  • Ethical Considerations in Agent Deployment: Bias, privacy, accountability, and transparency, specifically in the context of collecting and processing client information.
  • Security & Privacy: Safeguarding data when agents interact with personal information or systems.
  • The Evolving Landscape of AI Agents: Emerging trends, future possibilities, and responsible innovation in automation.

🎓 Module 8: Capstone Project – Building Your Custom Agent

  • Project Definition: Guidance on choosing a suitable personal or professional task for your own Agent build.
  • Agent Planning & Design: Applying all learned principles to blueprint your unique Agent.
  • Independent Build & Testing: Hands-on development and rigorous testing of your custom Agent.
  • Refinement & Presentation: Iterating on your Agent’s performance and showcasing its capabilities.
  • Certification: Completing your capstone project to earn your “AI Agent Architect” certificate.

🔧 Bonus Materials

  • Prompt templates for building effective task-based agents.
  • Agent planning worksheet/template.
  • Video walkthroughs of key setup processes (e.g., creating a Custom GPT).
  • Template Custom GPT JSON files (for the Client Intake + Onboarding Assistant example).
  • Conceptual walkthroughs of low-code agent creation environments.
  • Recommended Software and Tools: A curated list of platforms and resources.
     
  • Key Frameworks: Further reading/exploration on frameworks like LangChain, AutoGen, CrewAI.
     

🙋‍♀️ Who This Course Is For

  • Experienced AI users who have completed introductory AI courses (like your “GentleTech” or “Office Administrators” courses).
  • Office professionals, small business owners, entrepreneurs, and team leads looking to automate complex, multi-step tasks.
  • Tech-savvy seniors who are eager to explore the cutting edge of AI beyond simple chatbots.
  • Early-career tech learners curious about practical, hands-on LLM applications and Agent development.
  • Anyone looking to leverage AI to perform multi-step, autonomous tasks and simplify complex workflows.

💡 Bonus: AI Co-Building with Iris

Throughout this course, Iris, your trusted AI guide and brand’s digital companion, will be right by your side. She’s not just a concept; she’s your AI co-pilot in this learning journey. You’ll work with Iris to understand how Agents think, and she’ll provide insights and feedback as you build your own working Agent, including your Client Intake + Onboarding Assistant. It’s a unique co-creation experience that brings the learning to life!

💡 Why This Course Matters

The ability to build AI Agents is rapidly becoming a defining skill in the modern workplace and for personal productivity. This course empowers you to:

  • Automate entire workflows, not just single tasks, saving significant time and resources.
  • Deepen your understanding of how advanced AI systems are designed and function.
  • Transform complex, multi-step tasks into efficient, AI-driven solutions.
  • Position yourself at the forefront of AI adoption and innovation, becoming a key driver of efficiency and intelligent solutions in your domain.

You’re not just using AI; you’re learning to architect intelligent partners that work tirelessly on your behalf.

Enroll now