Designing agent loops
An agent is a loop with a job. The trick is knowing where the loop ends.
Connecting a language model to tools gives it more ways to act. It also gives it more ways to repeat an unhelpful step. A useful agent needs a clear job, a check on its actions, and a reason to stop.
Four parts of a useful loop
- An input: the request and relevant context.
- An action: the step taken in response.
- A check: evidence that the step achieved its intended result.
- A decision: continue, stop, or hand the task to a person.
Without a check and a stopping rule, an agent can keep taking actions until it exhausts its budget. Define both before putting it into use.
Write the stopping rules
State what counts as completion and what requires a handover. For example:
- Stop after the approved label has been applied to the support ticket.
- Stop when the required output passes validation and the task-specific checks.
- Hand over after three failed attempts at the same step.
Set limits on time, attempts and cost as well. A valid JSON structure is one check; it does not establish that the answer is correct.
Reviewing an answer and taking action are different jobs
A sequence of model calls can draft and critique an answer. An agent that uses tools must also check what happened outside the conversation. Did the record update? Was the correct document retrieved? Is the task complete? An improved draft does not answer those questions.
An illustrative example
Consider a fictional email-triage agent. Input: one unread message. Action: propose one of six approved labels. Check: validate the output structure and confirm that the label is allowed. Decision: route ambiguous or sensitive messages to a human queue; apply a label only within the agreed rules. Stop after the label is applied or the item is handed off.
Test these rules against representative messages before using them in production. A model’s self-reported confidence is not proof that a decision is correct.
Define how the agent finishes, fails safely, and asks for help.
Those decisions make the loop easier to test, explain and trust.