Prompt Engineering

AI Agents Explained: LLM + Tools + Memory Loop

March 4, 2026

AI Agents Explained — Why Your LLM Isn’t Actually “Doing” Anything (Yet)

You’ve probably used ChatGPT to draft an email or Claude to summarize a paper. You ask, it answers. Simple, right? But here’s what most people miss: that’s not an agent—that’s just a chatbot.

The misconception I see constantly in research circles: people think “AI agent” is just marketing speak for “a really good LLM.” The reality? An agent is an architecture, not a model. It’s the difference between a brain in a jar and a brain connected to hands, eyes, and a notebook.

Tool Calling Explained: Turn Your LLM into an AI Agent

March 4, 2026

Tool Calling Explained — How to Turn Your LLM into an AI Agent That Actually Does Things

Out-of-the-box LLMs can’t check your calendar, pull live weather data, or query your database. They’re brilliant conversationists trapped in a sensory deprivation chamber, completely isolated from the real world. The result? You get impressive prose about what to do, but zero ability to actually do it.

Tool calling (also called function calling) changes everything. It’s the bridge that transforms a chatbot into an agent—an LLM that can invoke external functions and APIs. Yet most explanations overcomplicate it.