# Claude Managed Agents — Multi-Agent Sessions and Outcomes Hit Public Beta

> Coordinator agents, specialist roles, and rubric-graded iteration land as a single API surface for production agent stacks.

- Org: Anthropic
- Date: 2026-05-06
- Category: tool, ecosystem
- Source: https://platform.claude.com/docs/en/managed-agents/multi-agent
- Canonical page: https://ai-tldr.dev/releases/anthropic-managed-agents-multiagent-outcomes/

## In short

Anthropic moves multi-agent orchestration and outcome-driven sessions to public beta for Claude Managed Agents. A coordinator delegates to up to 20 specialist agents; outcome rubrics let agents self-evaluate and iterate.

## What it is

Two new public-beta features for Claude Managed Agents — Anthropic's hosted agent harness — landed on May 6, alongside the Code w/ Claude 2026 keynote in San Francisco. Multi-agent sessions let a coordinator agent delegate to a roster of up to 20 specialist agents, each with its own model, system prompt, tools, and isolated context. Outcomes let you attach a markdown rubric to a session and have a separate grader judge each iteration until the rubric is satisfied.

## How it works

All agents share one container and filesystem but run in separate session threads with independent conversation history. The coordinator emits cross-thread events on a primary stream and can spawn up to 25 concurrent threads. For outcomes, a user.define_outcome event attaches a rubric (inline text or via the Files API) and a max_iterations cap that defaults to 3 and tops out at 20. A grader runs in a separate context window and returns per-criterion pass or fail; failed criteria feed back to the agent for the next loop. Both features ship under the existing managed-agents-2026-04-01 beta header. The same release also adds webhooks for session and vault lifecycle events plus background refresh for mcp_oauth vault credentials.

## Why it matters

These were the missing primitives for production agent stacks on Claude. Without coordinator and specialist split, teams had to bolt their own orchestration around a single agent. Without outcomes, the only stop signal was the model's own judgment, which doesn't survive long-horizon work. Together they turn Managed Agents from a single-agent harness into a configurable platform with built-in self-evaluation, putting Anthropic on a more direct collision course with Mistral Workflows and Google's Gemini Enterprise Agent Platform.

## Who it's for

Teams building autonomous agent products on the Anthropic API

## Try it

anthropic-beta: managed-agents-2026-04-01

## Links

- [Multi-Agent Docs](https://platform.claude.com/docs/en/managed-agents/multi-agent)
- [Outcomes Docs](https://platform.claude.com/docs/en/managed-agents/define-outcomes)
- [Platform Release Notes](https://platform.claude.com/docs/en/release-notes/overview)
- [Webhooks](https://platform.claude.com/docs/en/managed-agents/webhooks)