Automation · AI agents
AI agents without the magic: goals, tools and control
An agent becomes useful when it receives a bounded goal, a limited set of actions and feedback that can be checked—not because it acts without supervision.
What an AI agent contains
A practical agent combines a model, instructions, context, tools and a loop that observes results. Memory and retrieval can add relevant knowledge, but they also introduce stale data and access risks.
When an agent is appropriate
Use a deterministic workflow when the steps are known. Agents are more useful when the system must select among a small set of permitted tools. Limit iterations, cost, credentials and irreversible actions.
Human approval is a feature
Require confirmation before sending messages, publishing, spending money, deleting data or changing permissions. Log decisions, validate structured output and maintain a manual fallback. The n8n automation guide shows a concrete workflow pattern.