WhoBuilt

AI SDK 5: What’s New and What’s Next

Oct 7, 2025· 14 min· 1.1K views·Watch on YouTube

Speaker

Lars Grammel, who works on the AI SDK at Vercel, explains the SDK’s redesign and roadmap at Callstack’s AI Meetup in Wrocław.

Why AI SDK 5 needed a redesign

As models gained reasoning, tools, and multimodal input and output, applications became more complex too. Incremental changes made provider abstractions harder to maintain: Anthropic’s signed reasoning and OpenAI’s newer reasoning APIs were difficult to fit into the existing specification. The team started the three-month AI SDK 5 project in April.

A foundation for newer model APIs

AI SDK 5 moves the provider specification to version two, with more room for provider-specific information. Grammel describes ordered multimodal outputs, provider-executed tools such as OpenAI web search, and preserving response IDs so longer conversations work with APIs such as OpenAI Responses. The SDK also adds transcription and speech generation APIs.

Typed chat for richer interfaces

The chat redesign lets applications define typed message metadata, data parts, and tool calls across both server and front end. A travel app, for example, could stream typed hotel bookings or activities and render them with custom components. Chat is independent of a particular UI framework, and developers can replace the default Server-Sent Events transport or use `streamText` directly in a React Native app.

More control over tool loops

The SDK adds controls for agentic tool-calling loops without requiring a full agent framework. With `prepareStep`, developers can adjust the model, prompt, messages, or temperature for each step. With `stopWhen`, they can set limits such as a maximum number of steps or implement custom conditions based on tool calls or spending.

What is planned next

Grammel says version 5.1 is expected around October, with improved telemetry to help developers observe model calls and support evaluation loops. The team is also working on image editing, which has multiple use cases such as selecting and refining an area. Streaming speech generation and other capabilities may come later.

Takeaways

  • Treat provider abstractions as a design challenge when model APIs change faster than common patterns emerge.
  • Preserve the order of reasoning, tool, text, and media outputs when building multimodal interactions.
  • Type application metadata, streamed data, and tool calls across both server and UI to make complex chat interfaces easier to maintain.
  • Use per-step preparation and custom stop conditions to control tool loops, including limits tied to cost.
  • Choose chat transports and UI integrations that fit the app; the SDK’s chat abstraction can work beyond React.

Mentioned in this talk

Search inside this talk

What was claimed 12

Related talks