@LangChain: Deep Agents explained in <90 seconds by @sydneyrunkle
Summary
A short explanation of Deep Agents by Sydney Runkle, presented by LangChain.
View Cached Full Text
Cached at: 06/08/26, 11:29 PM
Deep Agents explained in <90 seconds by @sydneyrunkle https://t.co/G7raM9X0ni
Similar Articles
@LangChain: Everything you need to know about Managed Deep Agents:
LangChain announces Managed Deep Agents in private beta, a hosted API-first runtime for building, running, and operating deep agents in production, leveraging the open-source Deep Agents harness and integrating with LangSmith for durable execution, streaming, and human-in-the-loop workflows.
@LangChain: Managed Deep Agents keeps the project shape you already know: ↳ AGENTS.md, skills/, subagents/, + tools.json Context Hu…
LangChain introduces Managed Deep Agents, maintaining a familiar project layout with AGENTS.md, skills/, subagents/, and tools.json, along with Context Hub for persistent context management across sessions.
@LangChain_OSS: LangChain Community Spotlight: Deep Agents + ACP Coding Agent Jacob Lee built a custom AI coding agent with Deep Agents…
Jacob Lee created an open-source AI coding agent using Deep Agents and ACP that supplants Claude Code, offering multi-model support, LangSmith observability, and human-in-the-loop safeguards.
@LangChain: What do the agents of the future look like? A highlight from @hwchase17's Day 2 keynote.
LangChain announces on-demand interrupt capability for agents, highlighted in Harrison Chase's Day 2 keynote.
@LangChain: This macroeconomic research agent powered by Deep Agents, LangSmith, and the @youdotcom Finance Research API: Analyzes …
LangChain showcases a macroeconomic research agent built with Deep Agents, LangSmith, and the You.com Finance Research API that analyzes GDP data, detects anomalies, and investigates structural and cyclical drivers at the sector level, producing structured, cited briefings.