What Are AI Agents?

An AI agent perceives its environment, makes decisions, and takes action to achieve a goal.
Unlike a standard LLM that only responds to prompts, an agent acts with purpose, persistence, and awareness of its surroundings.

Think of an LLM as a skilled doctor with deep theoretical knowledge, and an AI agent as that doctor using instruments, labs, and hospital systems to examine patients and act in real time.
The agent uses the LLM for reasoning but extends it with tools, APIs, and live data sources to plan and execute tasks autonomously.

Introduction

When large language models (LLMs) first emerged, they revolutionized text generation but lacked true instruction-following capabilities.
Early LLMs often responded based on statistical likelihood rather than following clear commands.

For example:
User: “Write an email stating that I will be on leave today.”
LLM Response: “And then send it to my manager.”

To improve this, researchers introduced Supervised Fine Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF):

• SFT trains models with explicit instruction-following data to improve response accuracy.
• RLHF fine-tunes models based on human preferences for better relevance and coherence.

These methods enabled models to generate appropriate responses like: