How to Build Async AI Apps with Convex and TypeScript

Building asynchronous AI applications requires decoupling long-running tasks, like LLM calls, from the user interface to create a robust experience. Using a reactive database like Convex allows developers to persist state, such as prompts and responses, enabling background processes to run independently of the client's connection. This architectural pattern ensures that when a background AI task completes or updates its state, the changes are automatically pushed to all connected clients for real-time updates. This approach handles failures and retries more gracefully, as the state is durably stored and the background job can be restarted. Developers can further enhance the user experience by batching UI updates, creating the illusion of smooth streaming while using a more resilient, chunk-based data transfer method.