How Agentic AI Works

Building an agent requires more than just a Large Language Model (LLM). It requires a framework that allows the LLM to interact with the world.

1. The Reasoning Engine (The Brain)

The LLM serves as the central controller. It uses techniques like Chain-of-Thought to break a large goal into smaller, manageable sub-tasks.

2. Planning and Reflection

Modern agents don't just "guess." They use loops to check their own work. If a plan fails, the agent reflects on the error and tries a different approach.

3. Memory (Short & Long Term)

• Short-term: The immediate conversation context.
• Long-term: Vector databases (RAG) that allow the agent to remember facts or past interactions over months or years.