Streaming

Streaming is when AI sends its response incrementally — word by word or chunk by chunk — rather than waiting until the entire response is generated. This creates the typing effect you see in ChatGPT and other AI interfaces. For developers building AI products, streaming reduces perceived latency and creates a more responsive user experience.

Example

Without streaming, a user asks a question and stares at a blank screen for 5 seconds before the full response appears. With streaming, text starts appearing within milliseconds and flows in naturally — the same total time, but it feels instant.

Streaming is a UX pattern that makes AI feel fast. Even though the total generation time is the same, seeing words appear immediately transforms the experience.

Why Streaming Matters

Without StreamingWith Streaming
Wait... wait... full responseWords appear immediately
Feels slow and unresponsiveFeels fast and interactive
User wonders if it's workingUser sees progress in real time
All-or-nothingCan stop early if off-track

How Streaming Works

  1. User sends a prompt — Request goes to the AI API
  2. AI starts generating — Tokens produced one at a time
  3. Tokens sent immediately — Each token streamed to the client
  4. Client renders progressively — Text appears as it arrives
  5. Stream completes — Final token signals the end

Implementing Streaming

Most AI SDKs support streaming natively:

const stream = await ai.streamText({
  model: "claude-sonnet",
  prompt: "Explain vibe coding",
})

for await (const chunk of stream) {
  // Display each chunk as it arrives
}

Streaming Considerations

  • Error handling — Errors can occur mid-stream
  • Rate limiting — Streaming connections count toward API limits
  • Server load — Long-lived connections consume server resources
  • Token counting — Track usage as tokens stream in

When to Stream

Stream: Chat interfaces, long responses, creative content Don't stream: API calls expecting structured data, background processing, batch operations

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