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🐺 A Compilation of AI Agent Resources

Everything you need to know to build one yourself.

Author

Paulo Dores
September 10, 2025

If you are interested in AI, you must definitely be interested in AI Agents. Because they have the power of ChatGPT, but they run on their own. You give them a task, and they will try their best to complete it.

There are different tools and frameworks to choose from. I personally prefer LangGraph to orchestrate a multi-system architecture, and n8n to build reliable AI workflows. Here is everything you need to know to start building one yourself:

The Core Components of an AI Agent

Before we dive into the tools, it's helpful to understand what makes an AI agent tick. At its core, an AI agent is a system that uses a large language model (LLM) like ChatGPT or Gemini to perform a series of actions. Think of it like this:

  1. The Brain (LLM): This is the core reasoning engine. It takes your instructions, breaks them down into smaller steps, and decides what to do next.

  2. The Eyes and Ears (Tools): This is how the agent "sees" the outside world. Tools are functions or APIs that the agent can call to get information or perform actions. For example, a search engine tool, a code interpreter, or a calendar tool.

  3. The Memory: To work on complex tasks, an agent needs to remember what it has already done. This memory helps it avoid repeating mistakes and stay on track.

To help you get started, here are some of the most popular frameworks and libraries for building AI agents. These tools provide the necessary structure, so you don't have to build everything from scratch.

LangGraph

LangGraph is a powerful and very popular framework that simplifies the entire process of building agents. It provides a toolkit of pre-built components that handle the most common parts of an agent's workflow.

You can learn more and get started here: https://langchain-ai.github.io/langgraph/

LlamaIndex

While LangChain is great for general-purpose agents, LlamaIndex specializes in data handling. If your agent needs to answer questions or act on a large amount of your private data—like documents, articles, or spreadsheets—LlamaIndex is an excellent choice. It’s designed to make it easy to load, index, and query your data so the agent can use it to generate smarter responses.

You can learn more and get started here: LlamaIndex Documentation

Microsoft's Autogen

Autogen is a framework developed by Microsoft that focuses on multi-agent systems. Instead of building a single agent, you can set up multiple agents with different roles that work together to solve a complex problem. For example, you could have a "Programmer Agent" that writes code, a "Critic Agent" that checks the code for errors, and a "Planner Agent" that manages the overall task. This approach is powerful for automating sophisticated workflows.

You can learn more and get started here: AutoGen Documentation

CrewAI

CrewAI is another framework for creating collaborative, multi-agent teams. It simplifies the process of giving each agent a specific role, a set of tools, and a defined task. What makes CrewAI unique is its focus on making the collaboration between agents feel more natural and intuitive.

You can learn more and get started here: CrewAI Documentation

Non-Code Tools

If you are not a developer and want to build your own AI agent, don't worry. There are tools for you, too. These tools are like Lego blocks; you can drag and drop different actions to automate tasks.

Zapier

Zapier is a powerful tool that connects thousands of different applications. For example, you can create a "zap" to automatically save a new email attachment to your Google Drive. Zapier now includes a special feature called "Zapier Central," which allows you to build AI agents that can perform tasks using these connected apps.

Read more here: https://zapier.com/agents

Make

Make (formerly Integromat) is a visual platform that lets you create, build, and automate tasks and workflows. It's similar to Zapier but gives you more flexibility and control. You can set up complex, multi-step scenarios that involve an AI agent and many different applications.

n8n

n8n is a free, open-source workflow automation tool. It has a visual interface that lets you connect different services and build automated workflows. Unlike the other two, you have the option to host n8n yourself, which is great for privacy and cost control.

Get started here: https://n8n.io/ai-agents/

Getting Started

The best way to learn is by doing. Here is a simple plan to get started:

  1. Start Small: Begin by building a simple agent that uses a single tool, like a calculator or a web search.

  2. Choose a Framework: Pick a framework that aligns with your goal. If you want to build a simple agent that uses multiple tools, LangGraph is a great starting point. If your project is heavily focused on using your own documents, check out LlamaIndex.

  3. Read the Documentation: All of these frameworks have excellent documentation and tutorials to guide you through the process.

  4. Experiment: Don't be afraid to try different things. Building AI agents is still a new field, and the best way to learn is by experimenting and seeing what works.

The world of AI agents is evolving quickly, with new tools and techniques emerging all the time. By understanding these core concepts and frameworks, you'll be well on your way to building the next generation of smart, autonomous systems.

Empower Your Whole Team With AI Knowledge

If you’d like to make sure your whole team learns how to build AI Agents that are production-ready, consider joining the waiting list for the AI Agent Development Training I am lecturing. It is fully remote, and we provide certificates upon completion.

In the training, your team will learn:

  1. LLMs and how to get the proper intuition to work with these tools

  2. Prompt Engineering to craft the best ways of asking AI to complete a task for your

  3. RAG to improve the context of the AI workflow you will create

  4. AI Agents with LangGraph to build solid, production-ready AI Agents

  5. Multi-Agent Systems to solve more complex problems

Know more about the training at the ReachMind webpage:

Thank you for reading, and I see you next time!