What distinguishes an AI agent from a plain LLM call?

The defining feature of an **AI agent** is iteration, not the model. A plain LLM call is one shot: you send a prompt, you get a completion, the conversation ends from the system's point of view. An agent wraps the same LLM in a loop. The loop has four moving parts. The model **reasons** about the next step. It chooses a tool, which is a function or API the runtime knows how to execute. The runtime executes the tool and captures the result. That result becomes a new observation in the model's context, and the loop runs again. This continues until the model declares the goal reached, or until a step budget or cost budget forces a stop. The model is allowed to change its plan mid-run based on what each tool actually returned. Notice that none of this requires a special model. Any modern LLM with function-calling support can drive an agent loop. The agent is the runtime plus the loop plus the tools, not the weights. That is why option B is correct: the answer hinges on architecture, not on training data or hardware.

An **agent** is an LLM placed inside a loop that lets it choose actions, observe results, and choose again until a goal is reached. A plain LLM call returns one completion and stops. An agent keeps going. The canonical loop has four moves: reason, act, observe, decide. The model reads the current state, emits a tool call, the runtime executes it, the result is appended to the state, and the model gets another turn. Termination happens when the model signals completion or a budget is hit. The critical insight is that this is a software architecture pattern, not a model property. The same `gpt-4o` or `claude-3.5-sonnet` can be a plain chatbot in one call. The same model can be an agent in another, depending on whether the runtime gives it tools and lets it iterate. Options A, C, and D miss this. There is no special training data that makes a model agentic, GPU class is irrelevant, and persistent memory is a feature some agents add but not the defining one.