Why AI Agents Outliving HTTP Requests Break Your Backend Architecture

When a user triggers an AI agent via an HTTP request, the agent may continue running long after the request times out, causing gateway errors while the agent keeps consuming tokens and executing actions. This mismatch creates a dangerous scenario where a user retry can spawn duplicate agents performing overlapping work with no clear authority. Unlike a standard HTTP request, which has a short, predictable lifecycle, an AI agent run behaves as a long-lived state machine that can span seconds, minutes, or even days. To handle this reliably, engineers are advised to return a 202 Accepted response immediately, assign durable run IDs, store state outside process memory, and use idempotency keys to prevent duplicate executions. Additional concerns include expired auth tokens, cooperative cancellation protocols, and durable execution patterns for workflows that involve human approval steps.