The article highlights the shortcomings of current large language model (LLM) streaming implementations, particularly in chat applications. It compares Google's Gemini and Claude, noting that both struggle with maintaining active streams during user navigation or interruptions, forcing users to refresh pages to continue conversations. Stardrift aims to improve this experience by implementing resumable streams that remain active despite tab switches, page refreshes, or temporary internet drops. The authors emphasize that seamless streaming is essential for user experience in chat applications, as poor stream handling can lead to lost users. Stardrift's development process began with a minimal viable product (MVP) that lacked resumable streams, which quickly led to user complaints during demos. To address this, they integrated Streamstraight, a plug-and-play solution that allowed streams to continue over WebSockets if the client connection dropped. However, as the need for a demo arose, they restructured their architecture by decoupling the conversation code from the FastAPI backend and utilizing Redis streams for real-time message handling. This setup enabled them to manage streams more effectively, though it also led to the realization that they were closer to building a robust in-house resumption feature than initially anticipated. The final implementation required a deep understanding of both backend systems and React. By creating a custom transport class for their chat interface, Stardrift could manage stream reconnections when users returned to a chat. This process posed challenges, particularly in tracking active streams and ensuring that the system did not attempt to reconnect to completed streams. The authors explored various strategies for maintaining state without compromising the stateless nature of their backend, ultimately refining their approach to stream management.