Never Drop the Ball: Building Durable, AI-Powered Workflows in Django

Modern Django applications are evolving beyond basic CRUD. Autonomous agents, document processors, and multi-step AI assistants require complex orchestration across LLM APIs, vector databases, background tasks, and human-in-the-loop approvals. However, when relying on traditional Celery tasks and simple retries, rate limits, non-deterministic outputs, and third-party outages can easily lead to lost state, duplicate LLM calls, or orphaned operations.

This talk explores how to combine Django’s robust ecosystem with durable execution patterns to create fault-tolerant AI architectures. We will examine why traditional task queues fall short for complex AI pipelines and demonstrate how durable workflows allow execution to survive server crashes, worker restarts, and zero-downtime deployments without losing progress.