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Rippling이 Deep Agents와 LangSmith로 6개월 만에 프로덕션 AI를 구축한 방법
How Rippling built production AI in 6 months with Deep Agents and LangSmith
Rippling uses LangChain Deep Agents and LangSmith to run cross-domain AI across HR, IT, finance, payroll, and global operations.
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LangSmith Engine 소개
Introducing Langsmith Engine
LangSmith Engine watches your production traces, clusters failures into named issues, and proposes targeted fixes and eval coverage. Stop manually triaging agent failures.
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LangSmith 샌드박스가 정식 출시되었습니다
LangSmith Sandboxes are Generally Available
Run AI agents safely with LangSmith Sandboxes (GA): kernel-isolated microVMs with snapshots, parallel forks, service URLs, and auth proxies. Built for coding agents, CI agents, and…
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LangSmith 엔진 구축 방법: 에이전트 개선을 위한 우리의 에이전트
https://www.langchain.com/blog/how-we-built-langsmith-engine-our-agent-for-improving-agents
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쿠버네티스 기반 자체 호스팅 LangSmith를 위한 미션 컨트롤
Mission Control for Self-Hosted LangSmith on Kubernetes
How Mission Control helps teams operate self-hosted LangSmith on Kubernetes with in-cluster config, preflight checks, health views, releases, and diagnostics.
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프로덕션 에이전트 실패 수정: Interrupt 2026 회고 | LangChain 뉴스레터
Fixing agent failures in production: Interrupt 2026 recap | LangChain Newsletter
Recapping two days of Interrupt 2026 — LangSmith Engine, Sandboxes GA, LangChain Labs, and 23 talks from teams at LinkedIn, Rippling, Cisco, and more. Now on demand.
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Lyft가 LangGraph와 LangSmith로 구축한 자체 서빙 AI 에이전트 플랫폼
How Lyft Built a Self-Serve AI Agent Platform with LangGraph and LangSmith
Lyft used LangGraph and LangSmith to build a self-serve AI agent platform for customer support, cutting agent development from months to weeks.
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우리는 SmithDB를 개발했습니다: 에이전트 옵저버빌리티를 위한 데이터 레이어
We built SmithDB, the data layer for agent observability
Introducing SmithDB: LangSmith's purpose-built distributed database for agent observability, delivering up to 12x faster performance with full portability.
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관리형 Deep 에이전트: 프로덕션 Deep 에이전트를 가장 빠르게 배포하는 방법
Managed Deep Agents: the fastest way to ship a production deep agent
Run deep agents in production with durable execution, sandboxes, tool access, and LangSmith observability, without building the runtime yourself. Now in private beta
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LangSmith Context Hub 소개
Introducing LangSmith Context Hub
Introducing Context Hub in LangSmith: a central place to store, version, and collaborate on the files that shape how your AI agents behave.
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딥 에이전트, LangSmith, 병렬 처리를 사용한 회사 실사 에이전트 구축
https://www.langchain.com/blog/building-a-company-due-diligence-agent-with-deep-agents-langsmith-and-parallel
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메모리 검색 개선: New Computer가 LangSmith로 50% 높은 회상률을 달성한 방법
Improving Memory Retrieval: How New Computer achieved 50% higher recall with LangSmith
New Computer used LangSmith to improve their memory retrieval system, achieving 50% higher recall by tracking regressions in comparison view and adjusting conversation prompts acco…
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LangSmith를 이용한 회귀 테스트
Regression Testing with LangSmith
Evaluate and iterate on LLM applications with confidence using LangSmith's regression testing. Compare experiments, track performance, and identify changes.
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Azure 마켓플레이스에서 LangSmith이 거래 가능한 상품으로 출시 발표
Announcing LangSmith is now a transactable offering in the Azure Marketplace
LangSmith is now available in Azure Marketplace. Deploy the DevOps platform for LLM apps in your Azure VPC with full data control and MACC credit support.
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평가 주도 개발을 통한 LLM 신뢰성의 반복적 향상
Iterating Towards LLM Reliability with Evaluation Driven Development
Dosu uses evaluation driven development and LangSmith to build reliable LLM products at scale, monitor production performance, and iterate with confidence.