What Are AI Agents?
AI agents are smart systems that can work on their own to complete tasks for you or your team.
They don’t just follow fixed rules — they can plan, make decisions, and use tools to get things done, all without needing constant human input.
These agents can do more than just chat. They can:
Solve problems
Make decisions
Interact with software and systems
Take real actions — like sending emails, pulling reports, or even writing code
You’ll find AI agents being used across industries — from IT and software development to customer service and automation tools. They’re powered by advanced AI technology called large language models (LLMs), which allow them to understand your instructions and figure out the best way to respond — step by step.
They also know when to use other tools or apps to complete more complex tasks, making them far more capable than traditional chatbots.
How AI Agents Work
At the heart of every AI agent is a powerful technology called a large language model (LLM) — the same type of AI that powers advanced chatbots. That’s why these systems are often called LLM agents.
But unlike regular tools that can only give answers based on past training, AI agents can take action, use live tools, and break big tasks into smaller steps — all on their own.
Here’s how it works:
The agent listens to your request
It figures out the best plan to solve it
It uses other tools (like software, databases, or APIs) to get the job done
It learns from how you interact with it, so it gets better over time
These agents don’t just answer questions — they do the work, even pulling in real-time data or automating parts of your workflow without needing your input every time.
How AI Agents Think and Improve
AI agents are smart, but they still need direction. First, you set the goal, and the agent creates a plan by breaking that goal into smaller steps. The more complex the task, the more planning it does behind the scenes.
To get the job done, the agent doesn't rely only on what it already knows. It can connect to external tools — like APIs, databases, search engines, or even other AI agents — to gather fresh, relevant information. This allows it to make better decisions and solve problems in real time.
As it works, the agent constantly reassesses its plan, updates its knowledge, and adjusts based on what it learns — all without needing your input every step of the way.
And once the task is done, it doesn’t stop there. The agent remembers what it learned, including your feedback, so it performs better next time. Over time, this cycle of reflection and refinement makes the agent smarter, faster, and more aligned with your preferences.
Goal → Plan → Act → Learn → Improve
Agentic vs. Non-Agentic AI Chatbots
Most people are familiar with AI chatbots — they use natural language processing (NLP) to understand questions and respond in a conversational way. But not all chatbots are created equal.
Non-Agentic Chatbots
These are the basic, traditional bots. They can understand a question and give a reply, but they:
Don’t have memory
Can’t plan ahead
Can’t use tools or external data
Need constant user input
They’re fine for simple tasks — like FAQs or scripted conversations — but they fall short when asked to handle complex or personalized requests.
Agentic AI Chatbots
Agentic chatbots are more advanced. They’re designed to think, plan, and act like intelligent assistants. They can:
Learn and adapt to each user over time
Break down big tasks into smaller ones
Use tools, apps, and data to complete tasks
Self-correct when things don’t go as planned
Instead of just reacting, agentic chatbots solve problems, make decisions, and get smarter with every interaction. They’re built for real productivity, not just conversation.