seniorLLMs

How do agentic LLM systems work?

Updated May 16, 2026

Short answer

Agentic LLM systems extend language models with planning, memory, reasoning, and tool-usage capabilities so they can autonomously perform multi-step tasks.

Deep explanation

Traditional LLMs generate a single response from a prompt, but agentic systems introduce iterative decision-making loops. An agent receives a goal, reasons about required actions, invokes tools such as APIs or databases, evaluates results, and continues until the objective is completed.

The architecture usually includes:

Planner → decomposes tasks into subtasks.
Memory system → stores previous context and intermediate state.
Tool execution layer → allows API calls, search, calculators, or code execution.
Reflection/evaluation module → checks whether results satisfy objectives.

5.…

Unlock with a Pro subscription to view this section.

View pricing