AI agents explained

Mark Zuckerberg said recently that there will likely be more AI agents than people in the near future, and I personally don't think that it is an exaggeration. These intelligent systems have the potential to transform the way businesses operate, offering unprecedented value that go beyond traditional chatbots and voicebots. But what exactly are AI agents, and how can they be utilized by businesses to reduce manual effort and drive efficiency? Let’s break down this concept in a way that’s simple and actionable.

What are AI agents?

At its core, an AI agent is an intelligent system designed to perceive its environment, process information, and take action. The word "agent" comes from the Latin word "agere," meaning "to do." Like a real estate or insurance agent who acts on your behalf, an AI agent can take actions on your behalf in the digital space.

These agents don’t just respond to inquiries like chatbots; they actively interact with tools, platforms, and data to achieve specific goals or help users complete tasks. An AI agent can automatically book a meeting, retrieve crucial business data, or even make decisions based on the information it gathers, all without needing human intervention.

The anatomy of an AI agent

An AI agent isn’t just a simple program—it’s a combination of different parts working together to create an intelligent, action-oriented system. Here are the three key components:

?? Prompting

This is the foundation of how an AI agent operates. Prompts guide the Large Language Model (LLM) at the heart of the agent, instructing it on what actions to take. Whether it's scheduling an appointment, answering a complex query, or making a recommendation, prompting ensures the agent aligns with user objectives.

?? Knowledge

While some AI agents may only rely on language models, others are equipped with access to vast external knowledge bases. This allows the agent to draw from relevant information to provide more context-aware and accurate responses. For instance, an AI agent in a customer service role can pull up past orders or FAQs to assist customers in real time.

?? Tools

The real power of AI agents comes from their ability to interact with external tools and APIs. These tools act as the "hands" of the AI agent, enabling it to take concrete actions like sending emails, retrieving files, booking appointments, or making financial transactions. This interaction makes the agent a true assistant that can execute tasks based on user intent.

Examples of AI agents

AI agents come in many forms, but three of the most common and practical examples for businesses are voice agents, chatbots, and task automation agents. These agents are already making significant impacts across various industries, providing automation and efficiency in communication, customer service, and task management.

?? Voice agents

Voice agents are advanced AI systems designed to interact with users via spoken language. These agents go beyond basic voicebots like Siri or Alexa by performing tasks such as answering questions, making reservations, or even conducting initial customer support calls.

Example: A restaurant using an AI voice agent can have the system handle phone reservations. The agent can talk to customers, check availability, and book a table while integrating directly with a scheduling platform like Google Calendar. This not only saves time for staff but also provides customers with 24/7 booking capabilities.

?? Chatbots

AI chatbots are text-based agents that engage users in conversations, helping with queries, providing customer support, or guiding users through workflows. However, unlike traditional rule-based chatbots, modern AI chatbots powered by large language models (LLMs) like GPT can handle more complex interactions and make decisions based on context.

Example: An e-commerce business could use an AI chatbot to handle customer inquiries, suggest products based on previous purchases, and even process orders. The chatbot could seamlessly integrate with CRM systems to retrieve customer data, process orders, and even update inventory in real time.

?? Task automation agents

Task automation agents are designed to handle repetitive, rule-based tasks without requiring human intervention. These agents can integrate with various platforms and execute tasks based on specific triggers or rules, which makes them quite powerful.

Example: A finance department could use a task automation agent to automatically process invoices, cross-check them with purchase orders, and update payment records. The agent could seamlessly integrate with accounting software, reducing manual work and minimizing errors, while ensuring tasks are completed faster.

How to build an AI agent

In the past, building advanced AI agents required deep technical expertise and extensive programming skills, limiting their development to highly specialized teams. Today, thanks to no-code and low-code platforms, businesses can easily develop and deploy AI agents tailored to their specific needs. These platforms offer user-friendly interfaces and pre-built integrations, enabling even non-technical users (like myself!) to create sophisticated agents without needing to write a single line of code.

Here are the steps to build an AI agent using no-code and low-code tools:

1. Start with a problem

Identify the specific challenge or pain point in your business that you want the AI agent to solve. Whether it’s automating customer service, managing bookings, or streamlining workflows, having a clear problem in mind will help shape the functionality of your AI agent.

2. Choose the right tools

Depending on the agent you want to build, select the right no-code or low-code tools that supports its development. For examples, here are some of my favorites:

• Voice agents: Vapi, Synthflow
• Chatbots: Voiceflow, Voiceglow
• Automation: Make, Pipedream
• Tools builder: Relevance

3. Design the workflow

You can then map out how your AI agent will interact with users, handle different tasks, and trigger actions. Automation platforms like Make and Zapier, for instance, allow you to visualize these steps and logic in a very intuitive way, just by dragging and dropping components.

4. Integrate tools and APIs

AI agents are only as powerful as the tools they can access. No-code platforms make it easy to connect with external APIs and tools. For example, if you’re building an AI voice agent, you could connect it with a scheduling platform like Google Calendar, a CRM for customer data, or an email marketing tool to automate follow-ups. These integrations enable your agent to perform tasks such as retrieving data, booking appointments, or sending notifications.

5. Test and iterate

Once you’ve built your agent, most platforms provide ways to test it in a live environment. During this phase, you can refine the prompts, adjust the workflows, and ensure the agent interacts with tools as expected. Just like any other software, iterative improvement is key to ensuring the agent runs smoothly and effectively.

By using no-code and low-code platforms, business owners and entrepreneurs can create powerful AI agents without the need for a large development team. These platforms make AI accessible, enabling entrepreneurs to automate tasks and scale efficiently with minimal upfront investment in technology. Exciting times to be an entrepreneur ??

Here is an example of a powerful AI voice agent that I built completely with no-code tools!