You have probably seen the phrase "AI agent" in the news and in Google Cloud's learning content. It sounds complicated, but the idea is simple.

Chatbot versus agent

A chatbot answers your question and stops. An AI agent is given a goal, decides which steps to take, uses tools to carry them out, and keeps going until the goal is done or it needs your help.

For example, a chatbot can explain how to book a meeting room. An agent could check the calendar, pick a free slot, send the invite and tell you it is done.

The main parts of an agent

  • A model: the language model that reads instructions and decides what to do next.
  • Instructions: a plain description of the agent's job and its limits.
  • Tools: things the agent is allowed to use, such as searching a database, calling an API or reading a file.
  • A loop: the agent thinks, acts, looks at the result, and repeats.

Why "multi-agent" matters

Bigger systems often use several agents with different roles. One agent might gather data, another might check it, and a third might write the final answer. Google Skills has skill badges on exactly this, including engineering agents with the Agent Development Kit, deploying multi-agent architectures, and orchestrating multi-agent workflows.

Keep agents on a short leash

Because an agent can take actions, it should only be given the access it truly needs. Read what it plans to do, test it on sample data first, and never share secrets you would not put in a document. Even the 2026 Arcade Facilitator bonus project asked learners to give access to a single verifier account rather than opening everything up.

How to start building

  1. Learn the basics with hands-on labs on Google Skills.
  2. Try the agent-related skill badges to see the tools in action.
  3. Use the Google Cloud free trial for your own small project. Google describes it as 90 days with $300 in credits, and says it will not charge your card automatically when the trial ends.
  4. Start with something tiny, like an agent that answers questions from a short document, and grow from there.

Read the next post to see how Google turned this into a real project for Arcade Facilitator learners: [Build your first AI agent on Google Cloud](first-ai-agent-google-cloud-bonus-milestone.html).