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.
The round, led by CapitalG, supports LangSmith, which over 7,000 organizations use to run and govern agents.
The agent generated 1,540 artifacts in 12 weeks, saving 337 hours of rep time by using business context rather than just prompt tuning.
A team of four engineers built the platform on Workday's infrastructure, which has since grown to roughly 30 members.
The method uses a three-step process of defining pass/fail criteria, building datasets from real runs, and comparing baseline scores to detect regressions in agent behavior.
The company outlines three principles for using human-in-the-loop workflows to define quality, evaluate context, and create golden datasets for continuous agent improvement.
LangChain manages the data plane infrastructure while keeping traces, evals, and agent deployments in the customer's own cloud account.
The Schedules SDK allows developers to define static or dynamic cron jobs, enabling agents to perform background tasks like memory consolidation and smart triage.
Numan uses LangGraph and LangSmith to test its AI health coach against regulatory safety lines, reducing frontier model migration time from weeks to a single day.
The October 2026 update introduces semantic trace search, red-teaming capabilities, and FastMCP support in LangChain v1.4.0.
The LangSmith team details strategies for agent evaluation, including using cheaper judges like Jev to cut costs from $28.17 to $0.34 per run.
The platform is deployed across 120,000 Orange employees and adopted by over 150 customers in France and Europe.
AI Search is available in public beta on LangSmith Cloud at no additional cost, enabling semantic queries across agent traces.
The LangGraph-powered agent has handled over 60,000 queries and resolves more than 85% of sessions without creating a support ticket.
LangSmith Engine v2 introduces red teaming and automated fix validation, while Managed Deep Agents v0.8 adds user-level memory and built-in web search.
Engine v2 proactively detects issues like hallucinations and validates fixes before deployment, with new features available in Private Beta for LangSmith Deployment users.
LangChain has released Managed Deep Agents v0.8, introducing user-level memory isolation, HTTP channels for integration, and built-in web search powered by Parallel.
Trajectories project nested traces into a linear, readable view of agent actions, enabling faster debugging and SME review.
The new `smithtune` CLI enables end-to-end supervised fine-tuning using agent trajectories, partnering with Fireworks and Baseten for training infrastructure.
LangSmith has launched Custom Apps, allowing Plus and Enterprise users to build and publish custom interfaces on agent data, with Plus plans including one app and chat-based creation.
By leveraging LangSmith to transform clinical expert judgments into reusable evaluation assets, teams have simultaneously secured release speed and safety for medical AI.
LangSmith has integrated TypeSafe AI's Jev model to support agent evaluations that are up to 450x cheaper and 200x faster than LLMs.
LangChain has released 'Deep Life Sci', an open-source agent template for life sciences researchers.
Included Health launched 'Dot', a medical navigation agent leveraging LangGraph and Deep Agents.
LangChain has released an AI agent that increased marketing pipeline contribution from 0 to 20%.