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Introduction To AI Agents

This article introduces AI Agents.

AI Agent

An AI agent is a system that uses an AI model (usually an LLM) not just to answer questions, but to take actions toward a goal — planning steps, using tools, observing results, and adjusting its approach along the way.

Key Components Of An AI Agent

Component	Description
Model	usually an LLM like GPT-4 or Claude, responsible for reasoning about what to do next
Tools	functions the agent can call like searching the web, running code, querying a database, sending an email, calling an API. This is how the agent does things instead of just describing them.
Memory	Short-term (the current task's context) and sometimes long-term (facts or preferences remembered across sessions).
Planning/reasoning loop	The logic that breaks a big goal into smaller steps, decides which tool to use when, and evaluates whether progress is being made
Feedback/observation	After taking an action, the agent looks at the result (did the code run? did the search return useful info?) and decides the next step.

Example

Say you ask an agent: "Find the cheapest flight from Delhi to Tokyo next month and draft an email to my travel agent about it."

A plain chatbot might guess at flight prices from stale training data. An agent instead:

Recognizes it needs current flight data → calls a flight-search tool.
Reads the results, picks the cheapest reasonable option.
Drafts the email using that real data.
Might even check your calendar for conflicts before finalizing.

Each step involves a tool call and a decision, not just a single generated response.

Posted By -	Karan Gupta

Posted On -	Monday, September 28, 2026

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