Master modern LangChain 1.x and LangGraph for building sophisticated LLM applications with agents, state management, memory, and tool integration. Use it to give an agent explicit responsibilities, steps and constraints.

List files the agent wrote to /mnt/session/outputs/ during a session, then. Use it to ground design choices in named patterns, trade-offs and examples.

Anthropic can POST to your HTTPS endpoint when a Managed Agents resource changes state — an alternative to holding an SSE stream or polling. Payloads are thin (event type + resource IDs only); on receipt, fetch the resource for current state. Every delivery is HMAC-signed. Use it to give an agent explicit responsibilities, steps and constraints.

Override defaults for individual tools. This example enables everything except bash:. Use it to ground design choices in named patterns, trade-offs and examples.

With config.type: "self hosted", the agent loop stays on Anthropic's orchestration layer but tool execution moves to infrastructure you control — bash, file ops, and code run inside your container, so filesystem contents and network egress never leave your environment. Use it as a repeatable review, validation or hardening pass.

A scheduled deployment runs an agent on a recurring cron schedule — each firing creates a session autonomously. Use it for predictable-cadence work: nightly triage, weekly compliance scans, hourly monitors. Use it as a repeatable review, validation or hardening pass.

Managed Agents provisions a container per session as the agent's workspace. The agent loop runs on Anthropic's orchestration layer; the container is where the agent's tools execute — bash commands, file operations, code. You create a persisted Agent config (model, system pr. Use it to ground design choices in named patterns, trade-offs and examples.

An outcome elevates a session from conversation to work : you state what "done" looks like, and the harness runs an iterate → grade → revise loop until the artifact meets the rubric, hits max iterations, or is interrupted. A separate grader (independent context windo. Use it to ground design choices in named patterns, trade-offs and examples.

Claude Managed Agents is a hosted agent: Anthropic runs the agent loop and provisions a sandboxed container per session where the agent's tools execute (or your own worker, with a self hosted environment — see shared/managed-agents-self-hosted-sandboxes.md). You supply an a. Use it to ground design choices in named patterns, trade-offs and examples.

A coordinator agent can delegate to other agents within one session. All agents share the container and filesystem ; each runs in its own thread — a context-isolated event stream with its own conversation history, model, system prompt, tools, MCP servers, and skills (from. Use it to ground design choices in named patterns, trade-offs and examples.

Sessions are ephemeral by default — when one ends, anything the agent learned is gone. A memory store is a workspace-scoped collection of small text documents that persists across sessions. When a store is attached to a session (via resources[]), it is mounted into the cont. Use it as a repeatable review, validation or hardening pass.

Send events to a session via POST /v1/sessions/{id}/events. Use it to ground design choices in named patterns, trade-offs and examples.

Creating a session requires an environment id. Environments are reusable configuration templates for spinning up containers in Anthropic's infrastructure — you might create different environments for different use cases (e.g. data visualization vs web development, with diff. Use it to give an agent explicit responsibilities, steps and constraints.

Every session has a live trace view in the Anthropic Console at https://platform.claude.com/workspaces/{workspace}/sessions/{session id}. Print this URL immediately after creating a session so the user can watch tool calls and messages stream in real time. {workspace} is th. Use it to ground design choices in named patterns, trade-offs and examples.

Patterns you'll write on the client side when driving a Managed Agent session, grounded in working SDK examples. Use it to ground design choices in named patterns, trade-offs and examples.

All endpoints require x-api-key and anthropic-version: 2023-06-01 headers. Managed Agents endpoints additionally require the anthropic-beta header. Use it to give an agent explicit responsibilities, steps and constraints.

This file covers decision heuristics for building agents on the Claude API: which primitives to reach for, how to design your tool surface, and how to manage context and cost over long runs. For per-tool mechanics and code examples, see tool-use-concepts.md and the language-spe. Use it as a repeatable review, validation or hardening pass.

List files the agent wrote to /mnt/session/outputs/ during a session, then. Use it to ground design choices in named patterns, trade-offs and examples.

A compilation of language agents using the Cognitive Architectures for Language Agents (🐨CoALA) framework. - CoALA Paper (16 pages of main content): https://arxiv.org/abs/2309.02427 - CoALA Tweet (6 threads): https://twitter.com/ShunyuYao12/status/1699396834983362690 - CoALA. Use it to navigate the topic and choose relevant methods, papers or tools.

At the core of every agent is a neural network -- a Transformer, an RNN, a trained function -- shaped by billions of gradient updates on sequences of perception, reasoning, and action. Agency was never bestowed by the surrounding code. It was learned during training. Use it to ground design choices in named patterns, trade-offs and examples.