An agent is dispatched on a task it cannot complete. The spec is broken. The dependency is missing. The credentials are wrong. What happens next determines whether you have an autonomous fleet or a fleet that quietly fails.

The most common answer — instructing the agent in its prompt to “ask for help if stuck” — does not survive contact with production. Agents either keep grinding and produce broken work, or output text that looks like a question but never reaches a human, or politely “complete” the task by writing nothing and reporting success. None of these failure modes are visible from the outside until the dashboards have been lying for hours.

Human-in-the-Loop Patterns#

The most common failure mode in agent-driven work is not a wrong answer – it is a correct action taken without permission. An agent that deletes a file to “clean up,” force-pushes a branch to “fix history,” or restarts a service to “apply changes” can cause more damage in one unauthorized action than a dozen wrong answers.

Human-in-the-loop design is not about limiting agent capability. It is about matching autonomy to risk. Safe, reversible actions should proceed without interruption. Dangerous, irreversible actions should require explicit approval. The challenge is building this classification into the workflow without turning every action into a confirmation dialog.