AI agents explained

What is an AI agent?

An AI agent is a system that not only generates text, but also acts. It receives a goal, makes a plan, executes steps, checks the results, and adjusts its approach based on what it encounters.

Where a regular chatbot answers questions, an agent can perform a search, create a file, call an API, and then summarize the results — all in one go.

Illustration created with Canva AI

How does an agent work?

An agent combines a language model with a loop of thinking and acting:

1. Receive goal — e.g. "Write a market analysis on electric cars"
2. Make a plan — the model determines which steps are needed
3. Use tools — searching the web, reading files, executing code, calling APIs
4. Evaluate results — did the step produce the desired result?
5. Next step — the model adjusts its plan and continues

Examples of AI agents

• Claude Code — writes, tests, and debugs code in a codebase
• Operator (OpenAI) — performs tasks in web browsers on behalf of the user
• AutoGPT — an early open-source experiment with fully autonomous agents
• Business agents — process invoices, schedule meetings, answer emails

Multi-agent systems

For complex tasks, multiple agents work together: an "orchestrator" divides the work, specialized sub-agents execute subtasks, and a verifier checks the results. This makes it possible to parallelize tasks that are too large for a single context.

Risks of agents

• Error cascades — an early mistake can have major consequences later
• Irreversible actions — an agent that sends emails or deletes files can cause damage
• Prompt injection — malicious content in the environment can influence the agent's behavior

The future

Agentic AI is the most promising — and most risky — development in AI. The companies that now best understand how to deploy agents safely and effectively have a considerable advantage.