AI Briefing#langsmith
The latest AI and developer news about #langsmith, with the original source and a short summary.
The latest AI and developer news about #langsmith, with the original source and a short summary.
LangSmith Managed Deep Agents automates API key rotation and user-specific identity authentication through the Connections feature.
LangChain has launched Managed Deep Agents and LLM Gateway in public beta.
The LangChain team shares technical lessons learned from rebuilding their chatbot to improve internal support efficiency.
Marking its third anniversary, LangChain announced a ₩125 billion investment round and the expansion of its agent engineering platform, LangSmith.
LangChain marked its second anniversary by introducing the evolution of its tool ecosystem for agentic application development.
Podium used LangSmith to optimize AI agent performance and reduce engineering intervention by 90%.
This article presents diagnostic and optimization strategies to reduce AI agent latency.
LangChain raised $125 million to build an agent engineering platform and launched LangChain 1.0.
This article presents methods for managing the dynamic cost structures of agentic AI in financial services and demonstrating business value.
LangChain has released LangSmith Engine, which analyzes agent traces to identify repetitive errors.
Built an agent combining LangChain Deep Agents and the Parallel API to automate enterprise due diligence workflows.
Used LangChain's Deep Agents and the You.com API to analyze GDP data for the EU's 27 member states and generate a sourced briefing.
Harmonic rebuilt Scout using Deep Agents and LangSmith, increasing user retention by 4x.
Candidly built an agent harness using LangSmith to track and respond to user states in real time during conversations.
LangSmith LLM Gateway provides runtime control for centrally managing the cost, speed, and data protection of agent model calls.
Built an agent combining the Perplexity Agent API and LangGraph to generate VC investment memo drafts in 90 seconds.
A guide has been released to support the fine-tuning and evaluation processes of open-source and OpenAI models using LangSmith.
LangSmith has introduced enterprise-grade RBAC and a new API key system to strengthen access management.
LangSmith has launched beta versions of Pytest and Vitest/Jest integration features to enhance the convenience of LLM evaluations.
LangSmith has introduced workspace features to strengthen team-based resource isolation and permission management.
LangChain released Polly and a CLI to support complex deep agent debugging via LangSmith.
The key to improving LLM agent performance lies in context engineering, which dynamically provides the correct information and tools.
LangSmith Engine has improved agent issue detection performance by more than 2x and fix performance by 25%.
Toyota North America is leveraging Deep Agents and LangSmith to maximize AI development efficiency and pursue eight-figure cost savings.