What Are AI Agents and How to Create Them? Benefits and Overview

Have you ever dreamed your customer service team could respond quicker without sacrificing that personal touch? AI agents make this possible. AI-powered customer service is transforming customer service by providing quick, personalized responses to customers, all while keeping things efficient and stress-free. Today, AI agents use AI models to understand tasks, figure out what needs to be done, and get them done often on their own. They can be used to automate work and handle complex tasks, almost like robotic coworkers working alongside humans.

What is an AI agent?

An AI agent is an entity that can act on its own in a particular environment. It gathers information from its surroundings, makes decisions based on that info, and takes actions to change things whether in the real world, digital spaces, or both. Some AI agents can also learn and improve over time, experimenting with new ways to achieve their goals.

You do not need to be continually telling them what to do. once you give them a goal, they can figure out how to achieve it for themselves, problem-solving and adjusting as they go.
You may need to give them feedback or additional directions for certain jobs, but mostly they are capable of doing them on their own.

Unlike traditional software, which follows fixed instructions, AI agents can learn from experience. They can adjust their actions based on what they’ve learned. AI agents use context awareness to better understand their surroundings and continuously improve by interacting with data, their environment, and even receiving feedback from humans.

Components of an AI Agent

AI agents consist of several key parts:

• Sensors: These let the agent "sense" or collect information from the environment (e.g., cameras, microphones, or web search tools for software agents).
   
• Actuators: These allow the agent to take action in the world, such as moving a robot or creating a file on a computer.
   
• Processors and Decision-making: These are like the "brain" of the agent. They process information from the sensors, decide what action to take, and control the actuators.
   
• Learning and Knowledge: These store information the agent needs to improve its performance over time, such as how it handled past tasks and problems.

Some AI agents have all of these parts, while others may only have a few depending on what they are designed to do.

Related topics you may enjoy: OpenAI Launches $50M Grant Program to Support AI Research

Types of AI Agents

AI agents follow four basic rules: autonomy, perception, decision-making, and adaptability. They are designed to function independently, interpret data from their environment, make decisions, and improve over time.

Here are some types of AI agents:

1. General AI Agents

These are AI systems that can perform various tasks, like a robotic vacuum cleaner. Some have simple AI that detects obstacles, while others can recognize objects around them.

2. Basic-Reflex Agents

These agents respond to specific signals or stimuli they detect. Once they notice something, they make a decision and take action. For example, a smart thermostat or a robot vacuum that avoids furniture.

3. Model-Based AI Agents

These agents keep track of the world around them, learning how their actions affect things. This helps them make better decisions over time. You might see these in self-driving cars or systems predicting inventory needs in warehouses.

4. Goal-Oriented AI Agents

These agents are all about achieving a specific goal. They create a plan, take steps to reach that goal, and check if they’re on the right track. Examples include AI in chess games or apps that complete tasks to reach certain objectives.

5. Utility-Driven AI Agents

These agents evaluate different options and choose the best one based on their goals. They decide which action is the most efficient, cheapest, or fastest. You might see these agents helping with things like traffic optimization or TV show recommendations.

6. Learning and growing Agents

As the name suggests, learning agents improve by interacting with their environment and learning from their experiences. They use feedback to adjust their actions and get better over time. These are used in things like spam filters or systems that recommend products based on past behavior.

Examples of AI Agents
 

• Agentic AI chatbots: These are upgraded versions of chatbots like ChatGPT. They can connect to live data sources, better understand user intent, and interact with other systems (e.g., web searches). Unlike older chatbots, they can handle multi-step tasks and improve over time.
   
• Computer Use Agents (CUAs): These AI agents use your computer to perform tasks like ordering food or scheduling appointments. They can either have full access to your machine (which can be risky) or work in a separate, controlled environment (which is safer).
   
• Multi-Agent Systems: To handle complex tasks, like managing a business, multi-agent systems use multiple AI agents working together. One agent oversees the system, while others handle specific tasks, learning and improving over time. Though developer tools exist, it's still early for no-code solutions.

key benefits of AI Agents

Customers today expect quick, accurate, and personalized responses. AI agents help businesses meet these demands without spending a lot of money. Here are some key benefits of  AI agents :

• Non-stop Availability: AI agents are always available to assist customers, no matter the time of day or night.
   
• Scalability: They can handle many interactions at once, which reduces delays during busy times.
   
• Cost efficiency:  AI agents automate repetitive tasks, reducing the need for extra staff and lowering operational costs.
   
• constant progress: AI agents learn from customer interactions and get better at their jobs over time.
   
• Productivity enhancement: By handling simpler tasks, AI Agents free up human employees to focus on more complex issues. They also help support teams save time on tasks like analyzing feedback, suggesting answers, summarizing conversations, and more.

Understanding how to build AI agents that suit your business can bring all these benefits, allowing you to offer better service while saving time and resources.

How AI Agents Work?

AI agents might sound complicated, but they’re just designed to learn, adapt, and take action to make work easier. Here’s how they operate:

• Data-driven training: AI agents begin by learning from past data, like chat logs and FAQs. This helps them understand customer needs and improve over time.
   
• Analyzing patterns: Once trained, AI agents identify patterns, such as frequently asked questions or customer sentiments, to respond more effectively.
   
• Performing operations: After recognizing patterns, AI agents take actions like answering questions, making recommendations, or escalating issues to the right person.

This process helps businesses improve customer interactions and deliver smarter service.

How to create an AI Agent?

Follow these five steps from Coinbase to create your AI-based agent:

Step 1: Set Up Your Development Environment

Start by creating a workspace on Replit. By forking the Based Agent template, you’ll get a copy of the project with all the tools and files needed. You can modify this project to set goals and make decisions. New users may need to sign up for Replit first. This is where you’ll set up everything to work with blockchain and crypto.

Step 2: Get Your API Keys

Once your workspace is ready, you can connect your agent to the blockchain. This will let it access live data, such as market conditions or transaction verification. Real-time information is essential for the agent to operate smoothly.

• Go to Coinbase's CDP portal and create a new project. Generate and save both your API key and private key.
   
• Visit the OpenAI platform, log in or sign up, and create a new API key. Fund your account with $1-2 for testing purposes.

Important: Don’t expose your API keys publicly. Use Replit’s environment variables to keep them secure.

Step 3: Secure Your API Keys

In this step, you’ll store your API keys safely in Replit:

• Go to Tools in the left sidebar of your Replit project and choose Secrets.
   
• Add your API keys as secrets, so they remain private and secure.

Now, your agent is ready to access the blockchain safely and manage crypto assets using its wallet.

Step 4: Understand the Code Structure

To make your agent effective, you need to understand how the code works. The Based Agent template has two main files:

• agents.py: This file contains core functions for interacting with the blockchain, like sending and receiving funds. You can add extra functions here to give the agent more abilities.
   
• run.py: This file sets how the agent operates in three modes:
   

1. Chat mode: You can interact with the agent using the command line.
    
2. Autonomous mode: The agent runs on its own based on preset instructions.
    
3. Two-agent mode: This mode lets the OpenAI model and the Based Agent communicate with each other.
    

By understanding these files, you’ll know where to add new functions and how to set the right mode for the agent’s tasks.

Step 5: Add More Capabilities to Your Agent
 

Now, you can give your agent new functions and test it to make sure it works smoothly with blockchain tasks.

• Add new functions: For example, you could add a function to check market prices or send alerts.
  Link the new functions: After adding them, connect them to the agent in the agents.py file.
   
• Test and improve: Run tests to see how the agent performs. This helps identify areas to fix and fine-tune the agent for better accuracy, autonomy, and response to blockchain conditions.

AI Agent vs. AI Chatbot

AI agents and chatbots may seem similar, but they are quite different:

• Chatbots: Follow predefined rules and are good at answering simple, repetitive questions like “What are your business hours?”
   
• AI Agents: More advanced, they use machine learning to understand context, learn from interactions, and handle more complex tasks like recommending products or routing issues to the right department.

While chatbots handle straightforward tasks, AI agents provide smarter, more personalized experiences.

AI Agent Examples & Use Cases

Here are some examples of how AI agents are used in the real world:

• Multilingual Lead Generation: BAS World, a large truck dealer, uses AI agents to handle customer inquiries in 13 languages, boosting lead generation by 70%.
   
• E-commerce: Online retailers use AI agents to recommend products based on customer preferences, improving sales and customer loyalty.
   
• Financial Services: Banks use AI agents to answer customer questions, guide them through processes, and detect fraud.
   
• Healthcare: AI agents help manage patient records, schedule appointments, and answer health-related queries, improving efficiency.
   

Getting Started with AI Agents

Learning how to create AI agents is a great first step if you want to automate tasks or improve customer support. With the right data and tools, you can build AI agents that make your business more efficient and enhance your customer service.
AI agents get smarter over time, continuously improving and adapting to meet your business needs.