Programming Tutorials

  In 2025, the debate between FastAPI and Django is no longer just about "speed vs. batteries-included." It has shifted entirely toward concurrency models required by Generative AI. If you are building an MVP with standard CRUD (Create, Read, Update, Delete) requirements, Django remains the productivity king. However, if you are building AI Agents that require streaming LLM tokens, handling WebSocket connections for real-time reasoning, or managing high-throughput microservices, the synchronous history of Django becomes a bottleneck. This guide dissects the architectural differences, analyzes the root causes of performance divergence, and provides the exact code patterns needed to build AI-native backends today. The Core Conflict: Thread Blocking vs. Event Loops The friction between these frameworks stems from how they handle I/O-bound operations—specifically, the latency introduced by calling external Large Language Models (LLMs) like GPT-4 or Claude. The Django Bottleneck (...