New in LangSmith Engine: red teaming and automated testing
LangSmith Engine v2 adds automated red teaming to catch agent issues before production, plus automated agent testing.
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Thursday, Sep 24, 2026
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LangChain dominated agent-tooling news, shipping LangSmith Engine v2's red teaming and automated testing, a session-level trajectory view, custom app building, and a 0.8 release of Managed Deep Agents — four features in one day — while Databricks shipped a CLI for running coding agents at production scale.
Security had a rough day too: a macOS zero-day let unprivileged code hijack Meta's Muse assistant via a single debug setting, and Apple moved photo provenance to the camera sensor itself. DeepSeek's revenue run rate more than doubled ahead of a planned IPO, and Google and Alibaba both pushed frontier-model updates.
LangChain rolled out LangSmith Engine v2 in a single day — red teaming, session trajectories, and custom apps — while Databricks shipped a CLI for running coding agents at production scale.
LangSmith Engine v2 adds automated red teaming to catch agent issues before production, plus automated agent testing.
The 0.8 release adds user-owned credentials, user-level memory, HTTP channels, and Slack file transfer for agents running in production.
A new conversational trajectory view makes trace data easier to navigate, speeding up debugging for long-running agent sessions.
Teams can now build and publish custom interfaces on top of LangSmith agent data without separate hosting, auth, or permissions work.
A new CLI lets teams deploy and manage coding agents at scale on Databricks' Unity Gateway.
A macOS zero-day in Meta's Muse client and Apple's new sensor-level photo signing show how much trust now sits in agent clients and AI-generated media.
GitHub's Security Lab open-sourced a fuzzing taskflow built on its Taskflow Agent framework to automate vulnerability discovery.
Researcher Patrick Wardle found an unpatched macOS zero-day where a single debug setting let unprivileged software abuse Muse's extensive assistant permissions.
Databricks details how it layered agents onto its existing automated security-review process to close gaps manual checks missed.
Apple's new iPhone 18 Pro camera mode signs photos at the sensor and develops them in Private Cloud Compute, shifting provenance trust away from C2PA.
Google and Alibaba both pushed major model updates, while DeepSeek published details on the sandboxed training harness behind its latest agent models.
Gemini 3.8 Live with Live Avatar is now generally available in Gemini Enterprise, following last week's Live and Live Extended Thinking launches.
Gemini 3.8 Flash TTS lets developers clone a voice or design one from a text description, then direct delivery line by line.
Alibaba unveiled new Qwen models, custom AI chips, and an agentic cloud platform as part of a full-stack AI push.
A new DeepSeek paper describes DSec, the sandboxed training environment used to train every agent model from V3.2 through V4.1.
DeepSeek's revenue growth ahead of a planned IPO and Meta's hardware push at Connect show where AI capital is flowing outside the model layer.
DeepSeek's annualized revenue run rate has more than doubled to roughly $1 billion, driven by rising popularity and a price increase, ahead of a planned IPO.
Meta's Connect 2026 keynote centered on Muse smart glasses alongside new voice, video, and Charm features.
As AI makes scientific thinking cheap but experimentation still expensive, research organizations are restructuring around that asymmetry.
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