# How It Works

Tila uses a multi-agent architecture to expand the capabilities of artificial intelligence beyond a single request and give users tools for solving complex tasks in an interactive environment.

## What is the agent-based approach?

In the context of Tila, an agent is an autonomous AI component capable of:

- interpreting user tasks,
- making decisions based on context,
- interacting with other agents,
- accessing external knowledge sources (such as the internet or databases),
- performing specific actions: generating text, creating images, processing documents, writing code, and more.

## Multi-agent system

Instead of a linear query to a single model, Tila builds a chain of reasoning, where agents:

- break a task into subtasks,
- determine the optimal tools and models,
- coordinate execution based on the current context,
- form a final result that can be scaled or further refined.

Each tile on the canvas can represent a call to one or several agents, and the connections between them transfer knowledge, context, or data.

## Advantages of the approach

- **Contextual awareness:** agents see the entire chain, not just a single request.
- **Flexibility:** you can combine different models and tools.
- **Iterativity:** it’s easy to refine results, clarify requests, and develop branches of thought.
- **Collaboration:** the structure of agent interaction mimics the distributed work of a team of specialists.