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Agentic AI Foundations

What is an Agent vs LLM?

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The LLM vs Agent Distinction

You Are Not Building Chatbots

Before we write a single line of code, let's establish a critical distinction:

LLM (Language Model): A function that takes text in and produces text out.

Agent: A system that can take actions in the real world to accomplish goals.

The Key Difference

LLMAgent
Stateless (no memory)Stateful (remembers context)
Can only generate textCan call tools and APIs
Single turn: input → outputMulti-turn: observe → plan → act → repeat
Hallucinates without verificationCan verify against real data

Why Does This Matter?

At Alhena AI (and similar companies), you're building systems that:

  • Query order databases to answer customer questions
  • Process refunds by calling payment APIs
  • Check inventory before recommending products
  • Escalate to humans when confidence is low

None of these are possible with a raw LLM. You need an agent.

The Agent Loop

Every agent follows this fundamental loop:

This is the foundation everything else builds on.