Unlock the Secret: The A.G.E.N.T. Framework for AI Builders (+ 3 Essential n8n Templates)

Unlock the Secret: The A.G.E.N.T. Framework for AI Builders (+ 3 Essential n8n Templates)

Artficial Intelligence·

The Secret Sauce of AI Agents: A Framework You Need to Know

Only a fraction of AI builders are aware of this, but a particular framework combined with a complementary GPT is quietly reshaping how we operate internally at Robolabs. Today, I’m excited to share this framework with you, along with some practical examples to help you implement it immediately.

If you’re new to AI, don’t worry. I promise that even if you’re just getting started with low-code tools, you’ll find this accessible and valuable.

A Quick Introduction

In case we haven’t met yet, I’m Jay, and I run Robolabs—our agency dedicated to helping content businesses leverage AI meaningfully. I also lead the RoboNuggets community, where we aim to simplify AI learning for everyone, regardless of their background or skill level.

With the demand for AI solutions skyrocketing, as reflected in Google Trends, understanding AI agents is not only relevant; it’s essential.

Understanding System Prompts

Before we dive into the framework, let’s quickly clarify a term you might hear frequently: system prompts. Think of a system prompt as the fundamental purpose or role of your AI agent.

Why is this important? A well-defined system prompt can drastically enhance the quality of output your AI generates. If you’re unsure about why this matters, a fantastic piece by Pete Kumman discusses how revising the system prompt of Gmail’s AI assistant results in better functionality and user experience.

Introducing the AGN Framework

Here’s where things get interesting. We use a framework known as AGN—an acronym that stands for the essential elements your system prompt should include. The framework consists of:

  1. Ask: What is your primary request?
  2. Guidelines: What are the rules or constraints?
  3. Notation: In what format should the output be?
  4. Examples: What do good and bad outputs look like?
  5. Tools: What tools will the AI agent have at its disposal?

Let’s break this down.

What It Looks Like in Practice

Let’s say we want to create an AI agent called News Robo. Its role? To send daily updates about AI tools.

Using the AGN framework, here’s how I’d define it:

  1. Ask: “Summarize 3 impactful AI launches.”
  2. Guidelines: Limit each summary to 100 words and avoid redundant economic news.
  3. Examples: Good examples might include updates on AI launches; bad examples would be generalized trends.
  4. Notation: Outputs formatted in JSON for easy processing.
  5. Tools: Access to Google Sheets to track previously covered stories.

With this structured approach, we ensure that our AI agent is clear on its tasks, resulting in high-quality outputs.

Building in N8N

Now, let’s connect the dots with a popular low-code tool—N8N. It’s user-friendly and allows anyone to create complex workflows by simply dragging and dropping components.

In our News Robo example, when we execute the workflow:

  • The AI accesses current AI news via Internet tools.
  • It generates a cleanly formatted email with summaries, sources, and relevance reasoning.
  • All outputs respect the specifications set in our system prompt defined earlier.

This straightforward setup demonstrates just how powerful a well-structured system prompt can be.

More Examples

I’ve been playing around with different agents built using this framework, and the flexibility has been eye-opening. Here are two examples:

  1. Meeting AI Agent: Imagine needing a quick background check on someone before a call. You can simply prompt it with a name, and it summarizes their professional background, key talking points, and even recent activities—making your conversation more engaging.

  2. Creative Design Agent: What about crafting shirt designs? This agent can generate creative prompts for various themes, saving you loads of time. The structured output is perfect for platforms like Printify or Merch on Demand.

What I’d Do If I Started Today

If I were to start from scratch today, I’d:

  1. Learn the AGN framework: It simplifies system prompt creation enormously.
  2. Explore N8N: Spend a bit of time experimenting with the platform.
  3. Join communities: Platforms like RoboNuggets can provide support, resources, and inspiration as you learn.

A Thoughtful Conclusion

In a world increasingly dominated by AI, simple yet powerful frameworks can set you apart. The AGN framework is a helpful tool to construct your AI agent’s system prompts, while N8N provides the foundation to bring those agents to life.

If you’re curious about building systems that save you from burnout and free up your time, I created something that might help. It’s a small online course called Automation by RoboNuggets, where I share the exact tools and workflows I wish I knew earlier. You can check it out here, only if it feels right for you.

I hope this insight into AI frameworks enriches your journey into artificial intelligence. Let’s continue to learn and innovate together!

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