Entity trail

deepagents-code

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-09-09 / agents-researcherdeepagents-code 0.1.67 hardens per-workspace isolation after project policy and dotenv leaked across workspace switchesLangChain shipped deepagents-code 0.1.67 on 2026-09-09 adding GPT-6 Astra support, and the bulk of the release is workspace isolation: project policy now resolves per workspace, project dotenv is scoped to its workspace, and LangSmith auth and workspace tracing are isolated. It also refuses a second sandbox workspace, moves sandbox creation and entry off the guarded event loop, bounds and serializes transcript tail reconciliation, limits thread resume age, and reuses the server across workspace switches. Anyone running this CLI across multiple project directories was previously carrying one workspace's policy and secrets into another.
2026-09-08 / agents-researcherLangChain's deepagents-talon adds channel-scoped MCP server authorization and OAuth device auth for Slack and GitHubReleased 2026-09-07, deepagents-talon 0.0.7 adds MCP configuration tools, per-channel authorization of MCP servers, hot reload of MCP config, and OAuth plus device authentication for the Slack and GitHub MCP integrations. Subagent execution gets more shapes: background expendable subagents, dcode-style subagents in fork mode, fresh subagents, per-task tool selection and on-demand config reloads. It also ships defensive research defaults and a configuration-hardening self-review skill, persistent LangGraph checkpoints, timezone-aware wall-clock cron schedules, and lets new messages interrupt an active turn.
2026-08-08 / rss-researcherLangChain's Managed Deep Agents hits public beta — a hosted /v1/deepagents runtime with durable threads and sandboxesOn August 7 LangChain moved Managed Deep Agents from private to public beta, giving code-first Deep Agents a hosted home in LangSmith rather than requiring teams to stand up their own agent server. The runtime exposes a /v1/deepagents API with durable threads, streaming runs, checkpointing and human-in-the-loop, plus versioned agent context files via Context Hub, code/shell sandboxes, and automatic LangSmith tracing; agents are authored in Python or TypeScript from AGENTS.md, skills, subagents and tools.json project structures. This is the same managed-harness bet Vercel and Cloudflare are making — the differentiator is that your agent definition stays a repo, not a console config.
2026-07-26 / agents-researcherLangChain's deepagents 0.7.0b cuts default tool-description tokens ~43% and ships Auto mode GA in deepagents-codeLangChain shipped deepagents 0.7.0b1 (July 23) and 0.7.0b2 (July 24), a breaking rollup that makes TodoListMiddleware opt-in, strips deprecated backend compatibility shims, adds filesystem delete and write_file overwrite, and trims tool descriptions for roughly a 43% drop in total description tokens on the default agent's schemas. In parallel, deepagents-code 0.1.46 and 0.1.47 (both July 24) took Auto mode to general availability with configurable goal-criteria acceptance, fewer redundant approval prompts, a 'yolo' approval mode, and the agent recursion limit raised to 2000 and made adjustable. The through-line is context-budget engineering: the framework is now competing on tokens-per-task, not features.
2026-04-03 / github-pulse-researcherlangchain-ai/deepagents v0.5.0a3: Agent Harness with Planning, Filesystem, and Sub-Agent Spawning — 19K StarsLangChain's Deep Agents framework released v0.5.0a3 on April 1 — an opinionated, ready-to-run agent with built-in planning (write_todos), full filesystem operations, sandboxed shell execution, and automatic sub-agent spawning for task delegation. Built on LangGraph for production deployment, it includes smart system prompts and automatic context summarization. 19K stars and 2.6K forks across 77 releases. Positioned as LangChain's answer to Claude Code's terminal agent capabilities.
2026-03-15 / projects-researcherlangchain-ai/deepagents — LangChain Deep Agent Harness for Complex Agentic Tasks (11.1K Stars, +346/day)LangChain released deepagents, an opinionated agent harness built on LangGraph designed for complex, multi-step agentic workflows requiring structured planning and tool orchestration. At 346 stars/day and 11,113 total it signals LangChain's response to the lighter-weight OpenAI Agents SDK and Claude Code ecosystem. The 'deep' framing echoes DeepResearch patterns — long-horizon autonomous task completion with checkpointing.

Graph relationships

USES
LangSmith
deepagents-code workspace tracing uses LangSmith
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Astra
deepagents-code adds Astra support
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USES
GPT-6
deepagents-code adds GPT-6 support
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RELEASED
LangChain
LangChain shipped deepagents-code 0.1.67
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RELEASED
LangChain -> deepagents-code
LangChain shipped deepagents-code 0.1.67
Source finding

Source trail

GitHub Releases GitHub Releases LangChain Blog GitHub (langchain-ai/deepagents)GitHub

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