𝗧𝗮𝗺𝗶𝗻𝗴 𝗔𝗜 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 𝘄𝗶𝘁𝗵 𝗦𝗦𝗘
I built an AI autocomplete feature. Users hated it.
Every keystroke triggered an AI request. Users waited 2 to 3 seconds for a full JSON response. The UI felt broken. I tried debouncing and caching. Nothing worked. The core problem stayed the same: users saw nothing until the entire answer arrived.
I solved this using Server-Sent Events (SSE) to stream responses piece by piece.
The old flow looked like this:
- User types
- 300ms debounce
- HTTP POST request
- AI processes (1-2 seconds)
- Server returns full response
- Client renders
Users saw a blank screen for seconds. Even with a loading spinner, it felt slow.
I considered polling or WebSockets. Polling adds too much overhead. WebSockets are too heavy for a one-way stream.
I chose SSE because:
- It works one-way from server to client
- It uses simple text and JSON chunks
- It reconnects automatically if the connection drops
- It requires no extra libraries on your server
The results changed everything:
- Time to first visual response: 2.1s down to 0.3s
- User engagement: up 40%
- User complaints: zero
Streaming is about perception. A progressive UI feels faster than a static one. Users prefer seeing words appear one by one rather than waiting for a block of text.
If your AI responses are very short, stick to standard requests. If you need two-way talk, use WebSockets. But for most AI streaming needs, SSE is the best choice.
How do you handle AI latency in your apps? Do you stream or wait for full responses?