Introducing TryHackMe's AI Agent Platform
Understand what an agent does and practise asking questions you can check.
What is the agent doing?
The room introduces a chat environment for its exercises. You send a message and inspect the response. Later exercises give the agent particular roles or objectives. The original task explains how to open that environment.
In a wider application, an agent is a system that can use a model to choose steps towards a goal. Depending on its design, it may call tools, read stored information, or act on a computer. A chat interface alone does not tell you which abilities it has.
For example, a help desk assistant may suggest an answer and search support articles. The application decides whether it can also change a ticket.
Make a question easy to check
Try this original learning prompt:
Explain a false alarm in a home smoke detector. Then explain a false alarm in a security alert. Use two short paragraphs and define any technical words.
Ask where the comparison fails to see the limits of the analogy. Request shorter sentences when the English is difficult.
A good study habit is: ask → inspect → compare → explain in your own words. Save the useful explanation together with a reliable source, not just the chatbot response.
One model is not the whole application
An AI service also needs data handling, permissions, software, and monitoring. Google’s production ML overview shows why these surrounding components matter.
For a future portfolio entry, record the question, the response, how you checked it, and what remained uncertain.
Check your understanding
An agent says, “I checked your account.” Does that prove it accessed the account?
No. Check whether the application actually gave it an account tool and whether there is a real tool result or audit record. A sentence about an action is different from evidence of the action.