What is the difference between an AI agent and a chatbot?

A chatbot responds to messages, while an agent plans and takes actions — like calling APIs or running code — to achieve a goal.

What is tool calling in AI agents?

Tool calling is when an agent’s model decides to use an external tool, such as web search or code execution, and supplies the inputs for it.

Intermediate🖼️ 20 slides⏱ 4 minAI Agents & Automation

🦾 AI Agents Explained

An AI agent is an AI system that uses a language model plus tools, memory, and planning to complete multi-step tasks on its own. This visual guide explains how agents reason, use tools, remember context, and where autonomous agents are used today.

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What Is an AI Agent?

An AI agent uses an LLM plus tools, memory, and planning to complete tasks autonomously.

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Agent vs Chatbot

A chatbot replies; an agent plans and takes actions to reach a goal.

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The Core Loop

Agents observe, think, act, and repeat until the goal is met.

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Reasoning and Planning

Agents break big goals into smaller, ordered steps.

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What Are Tools?

Tools let agents search, run code, call APIs, and use the real world.

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Tool Calling

The model decides which tool to use and with what inputs.

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Memory in Agents

Short-term context plus long-term memory keep agents on track.

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The ReAct Pattern

Reason then act — alternating thought and action steps.

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What Is an Agent Loop?

A controller runs the model repeatedly, feeding back results.

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Single vs Multi-Agent

Multiple agents can specialize and collaborate on tasks.

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Guardrails and Limits

Constraints stop agents from harmful or runaway actions.

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Human-in-the-Loop

Approvals keep humans in control of risky steps.

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Hallucination Risk

Agents can act on wrong assumptions — verification matters.

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Cost and Latency

More steps mean more tokens, time, and money.

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Popular Agent Frameworks

LangChain, LangGraph, and CrewAI help build agents.

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Real Use Cases

Research, coding, support, and workflow automation.

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Evaluating Agents

Test reliability, safety, and task success rates.

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Limitations Today

Agents still struggle with long, complex, open-ended tasks.

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Designing Good Agents

Clear goals, good tools, memory, and guardrails.

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The Future of AI Agents

More reliable, cheaper agents will automate real work.

Frequently Asked Questions

An AI agent is a system that combines a language model with tools, memory, and planning to autonomously complete multi-step tasks rather than just answering questions.