How to create AI agents? Complete guide

The term artificial intelligence agent has evolved from sounding futuristic to becoming an increasingly common tool in businesses, technological projects, and even in daily life. 

From virtual assistants on websites to systems that automate internal tasks in a business, AI agents have moved from being an experiment to a real resource with great growth potential.

However, when it comes to creating AI agents, many questions arise: What technical knowledge is needed? Which platforms facilitate the process? Can anyone really learn to develop them?

In this guide, we’ll attempt to answer these questions in a simple and practical way, focusing on those who want to take the next step on their journey towards innovation.

What is an AI agent and why is it growing?

An AI agent is simply a program capable of perceiving its environment, processing information, and making decisions to perform a task autonomously. In other words, it’s software that acts intelligently without the need for a human to tell it every step to take.

Examples of AI agents are already visible in our daily lives: chatbots in customer service, assistants like Alexa or Google Assistant, or even algorithms that manage the logistics of large companies in real-time.

Its rise can be explained by several factors:

• Easier access to AI tools and models through cloud platforms.
• Reduced costs for training and deploying models.
• Increased demand for personalized business experiences.

All of this has led many professionals to ask how to create AI agents to apply them in their business or even as part of their professional development.

First steps to create an AI agent

1. Define your agent’s goal

Before diving into the technical details, the most important thing is to know what you want the agent to do. An AI agent doesn’t make sense if it doesn’t solve a specific problem. For example:

• Do you want to improve customer service in your business?
• Do you need to automate repetitive internal processes?
• Are you looking for an assistant to filter data and prepare reports?

Having a clear goal will determine everything else: what type of agent you need, which platform you’ll use, and how you’ll train it.

2. Gather the necessary data

AI agents work with data. Without it, performance will be limited. Review the available data and how you could structure it. For example, a customer service chatbot will need data such as frequently asked questions, your business’s products or services.

3. Choose the right platform 

Here’s where another big question arises: What are the best platforms for creating AI agents? There are different options depending on your technical knowledge and the type of project you have in mind.

What are the best platforms for creating AI agents?

Today, there are platforms that make creating agents much easier without needing to be an expert in programming. Some of the most popular include:

Dialogflow (Google Cloud)

Very commonly used for creating chatbots and virtual assistants. It integrates natural language recognition and easily connects to external applications.

Microsoft Bot Framework

Ideal if you’re already working with the Microsoft ecosystem. It offers tools to build complex and scalable agents.

IBM Watson Assistant

Focuses on conversational experiences and stands out for its ability to integrate with various communication channels (web, apps, social media).

LangChain + OpenAI

For those with more technical experience, this combination is perfect. LangChain allows connecting language models with databases, APIs, or external tools, creating very versatile agents.

No-code platforms like ManyChat or Landbot

If programming is not your thing, these options allow you to create conversational agents visually, dragging blocks and designing conversation flows.

The best platform will depend on the balance between your goals, resources, and technical knowledge.

Do you need to be a programmer to create AI agents?

The answer is: not necessarily. While programming and machine learning knowledge open many more doors, the reality is that there are now no-code and low-code platforms that make it possible for business profiles to experiment with AI agents too.

That said, if your goal is to create more advanced projects, it’s recommended to train in artificial intelligence and innovation. Understanding the technical fundamentals, ethical limitations, and AI’s potential will not only allow you to use tools but also to design custom solutions.

At this point, Founderz’s AI & Innovation certificate program is very useful. Our program is designed for professionals from various sectors who want to learn how to implement AI solutions in their projects without needing a purely technical profile.

Challenges and best practices when creating AI agents

Creating an AI agent is not just about building a chatbot and calling it done. To work well and add value, there are key aspects to consider:

1. Continuous training 

The agent must learn and improve over time. It’s not enough to configure it once; you’ll need to review how it responds and adjust its data.

2. User-centered design

A common mistake is designing overly complex agents. The key is to ensure the experience is smooth and natural for the person interacting with it.

3. Ethics and privacy

According to PwC’s “Responsible AI” report, one of the biggest current challenges is ensuring AI systems respect privacy and avoid biases. Before launching an agent, make sure to comply with regulations like GDPR and review how data is handled.

4. Scalability

If your agent works well and you want to expand it, consider platforms that can support a larger number of users or future integrations from the start.

Is it worth learning how to create AI agents?

Absolutely. Companies are increasingly looking for profiles that know how to create AI agents that bring real value to their business. And we’re not just talking about programmers: we’re also talking about people who understand customer needs, can translate a problem into an intelligent solution, and can lead innovation projects.

AI is not a passing trend. According to Stanford’s “AI Index 2024” report, investment in AI reached record levels in recent years, with a large part of that investment going towards practical applications like intelligent agents.

Creating AI agents is no longer a challenge reserved for large tech corporations. With current tools, any professional or business can start experimenting and building useful solutions. The key is to define the goal clearly, choose the right platform, and train to take it further.

If you want to dive deeper into this field and learn how to design AI solutions with a real impact on your sector, we invite you to discover our Online AI & Innovation certificate program. A practical, close, and results-oriented training designed to bring AI into your professional daily life.

The best time to start creating AI agents is now. Are you ready to take the first step? Get in touch with us!

This post is also available in: Español