Describe the typical agent execution loop.

An **agent loop** is the engine that turns a one shot LLM call into a multi step problem solver. Instead of asking the model for a single answer, you put it inside a loop that runs until the task is finished. The steps repeat in roughly this order. First, **observe**, the agent reads the current state, which starts as the user's request and grows over time. Second, reason, the model decides what to do next and which tool to use. Third, act, the runtime executes that tool call, for example a search, a database query, or a code snippet. Fourth, observe again, the tool's result is appended to the agent's context. Fifth, check, the model decides whether the goal is reached. If the goal is reached, the agent emits a final answer and exits. If not, the loop runs again with the new observation in context. A guard rail caps the number of steps and the total cost so a confused agent cannot spin forever. The key insight is that the model never plans the whole trajectory up front. It plans one step, sees what happened, and then decides the next step from the actual result.

An **agent loop** is a five step cycle that wraps an LLM into an autonomous task runner. The loop is: observe state, reason about the next action, choose and call a tool, capture the observation, then decide whether to stop or continue. The canonical iteration looks like this: $$\text{state}_{t+1} = \text{state}_t \;\cup\; \{\text{action}_t, \text{observation}_t\}$$ State is the running transcript of everything the agent has seen so far. It includes the original goal, every prior tool call, and every tool result. At each step the model receives this transcript and emits either a tool call or a final answer. Termination has three exits: the model emits a final answer, a step budget (typically 10 to 40 iterations) is exhausted, or a cost or wall clock budget is hit. Production loops also include retry logic for transient tool failures and a circuit breaker for repeated identical actions, which is the classic symptom of a stuck agent.