01
What is an AI agent?
An agent is a system that perceives its environment and chooses actions in pursuit of objectives. In software, an AI agent often consists of a foundation model surrounded by memory, tools, state management, planning logic and execution code.
02
The agent loop
- Observe: inspect the current environment or task state.
- Reason: determine what information is relevant and what action should come next.
- Act: call a tool, modify state or produce an external action.
- Observe again: inspect the result and update the next decision.
The loop matters because many useful tasks cannot be completed in a single model call. Reliability therefore depends on both model quality and orchestration.
03
Tool use
Tools give a model capabilities it does not possess internally. Common examples include calculators, browsers, databases, code execution environments, APIs and robotic actuators.
Tool use also creates a systems-design problem: the agent must select the correct tool, form valid arguments, interpret the result and recover from failures.
04
Memory
A context window is not equivalent to durable memory. Agent systems may use short-term working context, conversation history, structured state or external retrieval systems to maintain information across longer workflows.
05
Reliability
- Incorrect plans
- Invalid tool arguments
- Hallucinated state
- Failure to recover from errors
- Runaway execution loops
- Security failures caused by untrusted external instructions