# AI Agents

> An AI agent is a system that uses a language model to plan and take actions — calling tools, querying systems, completing multi-step tasks — rather than only answering a question. Enterprise agents need tool integration, guardrails, evaluation, and human-in-the-loop controls to be trusted in production.

*Source: https://www.lazlosoftwaresolution.com/guides/ai-agents*

Agents turn an LLM from a text generator into a system that **gets work done**: it reasons about a goal, calls tools, observes results, and continues. The hard part is not the model — it's the tooling, guardrails, and evaluation around it.

## What a production agent needs

- **Tools** — typed, permissioned access to your APIs and data (the Model Context Protocol standardises this).
- **Guardrails** — input/output validation, allow-lists, and spend/rate limits.
- **Evaluation** — automated checks on real tasks before and after each change.
- **Human-in-the-loop** — approval gates for high-consequence actions.

## Where agents earn their keep

Support triage, operations automation, data processing, and internal copilots — anywhere a defined multi-step process can be delegated with oversight.