AI agent guide
AI Agents Explained: Architecture, Evaluation, and Safety
A practical definition of AI agents, the components behind them, and the checks to perform before using an agent in a real business process.
Reviewed and updated September 6, 2026 · Tubato Editorial Team
What is an AI agent?
An AI agent is a software system that interprets a goal, uses available context, selects permitted tools, and takes one or more actions within defined limits.
An agent usually combines a model with instructions, context or memory, tools, and an execution loop. Unlike a fixed workflow, it can choose among allowed actions based on the current situation. That flexibility also makes boundaries, evaluation, and observability essential.
AI agent vs. chatbot vs. workflow
- A chatbot primarily exchanges messages with a user.
- A workflow follows a defined sequence of triggers, rules, and actions.
- An AI agent can interpret an objective and decide which permitted action or tool to use next.
- A production system can combine all three: chat as the interface, an agent for bounded decisions, and workflows for dependable execution.
What a production AI agent needs
- A narrow purpose and an explicit definition of success.
- Only the tools and data permissions needed for that purpose.
- Reliable context with clear source and freshness boundaries.
- Structured outputs that downstream systems can validate.
- Limits for cost, time, iterations, and irreversible actions.
- Logs and evaluations that reveal errors, tool use, and outcome quality.
How to evaluate an AI agent template
Evaluate the complete operating system around the model—not only the prompt.
Confirm which model providers, data sources, connectors, and runtime services are required. Test common tasks, ambiguous inputs, hostile instructions, missing context, tool failures, and attempts to access unauthorized data. Review whether the documentation states limitations and when a person must approve an action.
Safety and governance checklist
- Keep secrets outside prompts and restrict each tool to least-privilege access.
- Treat retrieved web pages, files, and messages as untrusted input.
- Require approval for payments, deletion, external publishing, and other high-impact actions.
- Minimize personal data and define retention rules for conversations and logs.
- Continuously evaluate quality after changing prompts, models, tools, or source data.
Frequently asked questions
Does an AI agent always act autonomously?
No. Autonomy is a design choice. Many useful agents only recommend actions or require approval before using a tool.
What is agentic workflow automation?
It is a system where a workflow provides orchestration and controls while an AI agent handles one or more bounded decisions within that process.
How is an AI agent tested?
Use a repeatable evaluation set covering normal tasks, edge cases, unsafe requests, tool failures, authorization boundaries, cost, latency, and final outcome quality.