Laravel Horizon in production looks deceptively simple until your first LLM inference job times out silently and your users start receiving empty responses. Standard queue jobs (sending emails, processing images, syncing records), complete in milliseconds. AI inference jobs do not. A cold claude-sonnet-4-6 call with a dense system prompt can run for 45 seconds. A gemini-2.5-pro batch summarisation job can breach two minutes under load. Horizon’s defaults were not built for this, and the failure modes are nasty: jobs that disappear without landing in failed_jobs , rate limit retries that exhaust the tries budget in under 30 seconds, and expensive inference work discarded mid-completion. This guide is part of the AI Deployment & Production Operations module , which covers the full surface area of running Laravel AI applications in production. If you are still wiring up the surrounding deployment infrastructure, the complete production deployment guide is the right starting point.…