AI agents are systems capable of planning and executing multi-step tasks to achieve a goal, without the need for human supervision at every action. Unlike a language model that only responds to a query, an agent decides what to do, in what order, and which tools to use to achieve it.
Their operation is typically based on three key capabilities:
- Reasoning: they break down a complex goal into manageable subtasks.
- Tool use: they invoke APIs, search engines, databases, or execute code.
- Memory: they retain context between steps to maintain coherence.
They matter because they expand the scope of AI from simple text generation toward autonomous action, allowing for the automation of entire workflows. A practical example would be an agent tasked with organizing a trip: it searches for flights, compares prices, books accommodation, and creates an itinerary, chaining decisions on its own. The relevant nuance is that this autonomy also introduces risks of accumulated errors, so it is advisable to define boundaries and checkpoints.