How AI Chat Interfaces Handle Prompt History and Streaming Without Freezing the UI

A developer explains why AI chat apps can feel sluggish when a long reply streams in, pointing to the cost of repeatedly copying or re-rendering large prompt history arrays. Naive implementations that update the whole transcript on every token can block the main thread, causing input lag and page stalls. A more efficient approach updates only the content of the latest assistant message as tokens arrive, limiting re-renders to the affected component. The write-up also covers consuming streamed responses through async iterators and batching tokens to reduce update frequency. The author shares prototypes and code examples drawn from popular open-source AI chat frontends.