Building durable Agents with Workflow DevKit & AI SDK – Peter Wielander, Vercel

Peter Wielander, an engineer at Vercel, leads a live coding workshop at AI Engineer on making AI agents production-ready using Vercel’s open-source Workflow DevKit alongside the AI SDK. Starting from a working coding agent in the public vercel/examples repository, Wielander incrementally transforms it into a durable, fault-tolerant, observable system — deployed live to Vercel during the session.

The core concept is the workflow pattern: splitting agent code into discrete steps that are individually cached, retriable, and state-persisted, with an orchestration layer managing the overall agent loop. This architecture directly addresses the most common production failures for long-running agents — serverless timeout limits, state loss on crashes, and the operational complexity of manually wiring message queues and databases. The Workflow DevKit wraps all of that in a single TypeScript library compatible with any cloud stack.

The workshop demonstrates resumable streams out of the box, suspending and resuming agent execution at arbitrary checkpoints (enabling use cases like daily cron agents that sleep for days between steps), and human-in-the-loop webhook integration for approval workflows. A key highlight is Vercel’s workflow inspection UI running identically in local development and deployed preview environments, eliminating the environment parity gap that typically complicates agent debugging. All workshop code is available on GitHub with per-step checkpoint branches, making the material fully reproducible after the session.

📺 Source: AI Engineer · Published January 06, 2026
🏷️ Format: Hands On Build