Temporal

MCP Tasks (async): Why Aren't Any Agents Supporting Them? — Cornelia Davis, Temporal

Aug 2, 2026 · 23:54

Cornelia Davis, a distributed systems veteran and technologist at Temporal, argues that MCP Tasks remain unsupported because the V1 spec was experimental and deeply involved, and she walks through the V2 redesign that makes long-running, durable tool calls practical. Using an invoice-processing flow with human-in-the-loop approval, she demonstrates that a task survives client disconnects, server crashes, and network blips because the spec says once launched, a task must be durable. She explains V1's pain points: a stateful task_list endpoint with no filtering that cannot scale to a million tasks, and a task_result tunnel that requires a long-lived connection to deliver input-required events. V2 replaces that with a stateless core, makes tasks an extension, removes task_list, and lets clients send updates into a task via a new endpoint, while keeping the lifecycle state machine unchanged. She warns that the spec only says clients 'should' persist task IDs, and without that there is no way to recover a task; her ongoing work covers a notifications protocol for scale and shipping all of this in Fast MCP.

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

Jan 6, 2026 · 1:09:49

Peter Wielander from Vercel introduces the Workflow DevKit, an open-source library that adds durability, observability, and resumability to AI agents by wrapping them in a workflow pattern. He demonstrates converting a coding agent into a workflow-supported agent, showing how steps like LLM calls and tool executions become isolated, retryable units. The toolkit enables long-running agents that can sleep for days, resume streams after disconnection, and integrate human-in-the-loop via webhooks. Deployable on Vercel or any cloud, it provides built-in observability through a local UI. The Workflow DevKit is currently in beta with general availability targeted for January.

Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal

Jul 28, 2025 · 15:01

Preeti Somal, SVP of Engineering at Temporal, argues that the platform is the right choice for building reliable, scalable agentic AI applications. Temporal provides battle-tested orchestration through workflow abstractions, handling state, retries, and failure transparency so developers can focus on business logic. She cites customers like Dust and Gorgias running AI agents on Temporal in production, achieving up to 6x faster feature delivery. The platform uses signals and queries for human interaction, stores full workflow history for debugging and compliance, and offers Temporal Cloud for managed scalability. Somal emphasizes that agents are complex distributed systems requiring robust orchestration, and Temporal’s decade of production use in mission-critical applications proves its reliability.