Knowledge catalogue
i recently left @Bloomberg after two great years. incredibly lucky to have joined @LangChain in time to work on this 🚀 Spend less time on triaging Ship fixes faster Catch regressions earlier Introduci
I was going to say LangChain Labs is the most exciting thing we’ve announced recently, but with so many launches it’s hard to justify… but still incredibly thrilled to see this get started!! Checkout
This post references a LangChain Interrupt event where Brace Sproul and Caroline shared insights about applied AI leadership, with the author suggesting that effective heads of applied AI need signifi
Introducing LangSmith LLM Gateway: The runtime governance layer for your agents. 💸 Enforce cost limits 🔒 Detect PII ✅ Act on violations …All without leaving LangSmith. Now in Private Beta https://www.
Jake will be working with a lot of folks on continual learning - if that’s interesting, reach out to him! An exciting time to be working on Continual Learning and everything around it - if you’re work
LangChain Labs is a new applied research initiative announced by LangChain focused on advancing continual learning capabilities. The effort represents the company's commitment to developing systems th
LangChain 在 Interrupt 大会上发布了底层数据库 SmithDB 和自动化排障引擎 LangSmith Engine。 Agent 运行会产生海量 trace（执行轨迹），把旧数据库撑到了瓶颈。新底座 SmithDB 放弃了本地磁盘，全面转向对象存储，将核心查询速度拉高了 15 倍。 底座换新后，LangSmith Engine 顺势接管了查 Bug 的体力活。它在后台持续监控生
LangChain Labs has launched as a new initiative from the LangChain team. The announcement was made by Harrison Chase, the creator and lead developer of LangChain, on X (formerly Twitter). LangChain La
LangSmith Engine, 6 months later imo, reading and analyzing long agent traces is a huge bottleneck and obstacle for progress (especially as these systems grow in time horizon). Imagine reading a langs
LangSmith Engine feels like the missing piece for reliable agents. Clustering failures and suggesting targeted fixes turns raw traces into actionable improvements. This is how we scale agent developme
LangSmith Engine is a phase shift because traces are no longer just records to be manually inspected, they’re now the catalyst for recursive agent self-improvement Engine looks at your traces, finds w
LangSmith Fleet has introduced a free model option powered by Fireworks AI for users on Developer and Plus plans, lowering the barrier to entry for getting started with the platform. This update makes
Model. Harness. Context. The 3 main components of agents. As you build more agents, context increasingly lives AGENTS.md, skills, policies, examples, + generated research files. Context needs its own
okay okay, hillclimbing agent in the background. love it. great job @hwchase17 @Vtrivedy10 and team. 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs i
our engineers had an awesome time attending Interrupt:2026 by @LangChain learning about observability, agent evals, and best practices from the industry leaders! can't wait to see what they cook up wi
right now Engine only works with LangSmith traces but it's super easy to trace to LangSmith, we accept OTEL and integrate with 30+ frameworks! if you want to migrate to LangSmith to try out Engine, we
SmithDB is a feat of engineering. A new database for a new data shape Huge work from @ankush_gola11 and team We built SmithDB: the database purpose built for agent observability workloads that now pow
SmithDB is the perfect example of how far performance can be pushed by having full control over the storage layer. The DataFusion + @vortexdotdev stack seems to be emerging as THE way to build next ge
suuuuper excited to be collaborating with the excellent LangChain Labs team on this effort prod agent tracing is the seed that lets you close the loop for continual learning. too much data gets collec
The Building AI Agents with MongoDB and LangGraph Skill Badge can be yours on May 28th. Here's how you earn it 👉 Join our LIVE workshop, build a real agent with MongoDB, Claude Sonnet, and LangGraph,
the future intelligent agents will learn and grow with your team over ultra long timescales 🕰️ that research direction centers around Continual Learning LangSmith is the data layer that helps us under
the langsmith team cooked on this one @jakebroekhuizen this + claude code + langsmith cli has been 🔥 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs i
There's a ton on unexplored space in building enterprise-grade agent harnesses that continuously improve over time. Congrats to @hwchase17 and @LangChain on the launch of LangChain Labs and excited to
We are excited to be partnering with @LangChain for deploying self-improving agents. Continual learning in your production environment unlocks compounding capability gains for model-product optimizati
which was your favorite launch? SmithDB (database purpose built for agent trace data): https://www.langchain.com/blog/introducing-smithdb LangSmith Engine (agent for improving your agents based on tra
A new Database product based on @ApacheDataFusio was announced today from @LangChain -- focused on agent observability. It is really neat to see how people are building (very) customized data + query
Agent observability is more than just logging and viewing traces. You need agents sitting on top of your traces to proactively identify issues. We're launching Engine. Think of it as an always-on AI e
SmithDB is a new database system designed specifically for agent observability, announced by Harrison Chase and the LangChain team. The platform aims to provide comprehensive monitoring and visibility
This X post from Harrison Chase likely discusses anticipated features or developments in a major product update or release, inviting community feedback on what users are most excited about. The post a
Coming up at Interrupt: 🎙️ How @clay scales their GTM Engineering agents with Head of AI @JeffBarg. 🎙️ @ummadisetti and @kordelfrance on how @Toyota Motor North America equipped 56,000 employees with
Great example of why you should 1. Run your agent on a separate machine from the sandbox it uses (e.g. sandbox as a tool) 2. Never set env vars in your sandbox. Instead, use something like LangSmith’s
Has been a blast shipping Engine!! We built engine to automate the agent development loop, and make agents that improve autonomously. Absolutely cracked team shipping at light speed to create the futu
Harrison Chase and Ankush Gola interrupted a keynote presentation, likely at a technology conference or event related to LangChain. The post conveys excitement about their unexpected appearance or int
'Industry-leading performance across every key observability workload' 🚀 Agent traces are nested, long-running, and full of large payloads. Making them searchable and interactive needs a data layer de
Introducing Managed Deep Agents: the fastest way to ship a production deep agent. ✅ Harness ✅ Context ✅ Code execution All managed for you. Deploy with a single line of code. https://www.langchain.com
This post likely discusses the importance of database (DB) integration in LangChain applications, emphasizing that databases are a fundamental component for building robust and functional systems. The
i've been working on langsmith engine for the past couple of months, and it's been the most exciting project i've been a part of! in my opinion, this is the missing piece of agent observability. it ta
Just announced at Interrupt! SmithDB. Agent traces have outgrown the databases built to hold them. That’s why we built SmithDB, a purpose-built distributed database for agent observability. Read the a
Langsmith Engine appears to be a seriously high value release from the @LangChain team A deep agent that’s monitoring Langsmith agent traces and not only surfaces issues but: - proposes a PR to resolv
LangSmith Sandboxes are now GA: ✅ Secure, scalable environments built for agent code execution ✅ Integrated with the Deep Agents SDK and the LangSmith platform Learn more: https://www.langchain.com/bl
🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests action items (code
Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvements… Especially excited about the Code Interpreter feature which is a sneaky powerful feature e
NVIDIA Nemotron models received native support integration in Deep Agents version 0.6, enabling improved language model capabilities within the LangChain framework. This update allows developers to le
Observability going from 'read the traces' to 'the traces read themselves and tell you what to fix.' That's the feedback loop most agent teams are missing. 🚀Launching: LangSmith Engine LangSmith Engin
Off to an amazing start at @LangChain Interrupt 🪁🦜 Including: 📣 Shoutout from @hwchase17 during the opening keynote! 🪁 CopilotKit booth with the best staff, demos and merch 🍸 Agents After Dark Happy H
One of the biggest challenges with agents is that they produce way more than just tokens. Tool calls. State updates. Intermediate reasoning. Subagent progress. File changes. Custom events. Structured
Harrison Chase delivered a keynote address at a LangChain event that drew a large audience, as indicated by the 'packed house' reference. The event appears to have been interrupted at some point durin
Harrison Chase, the creator of LangChain, expressed positive sentiment about Baseten as a partnership, highlighting their collaborative work in supporting frontier AI teams. The post suggests that Bas
Harrison Chase shared excitement about the first day of LangChain Interrupt, a LangChain-related event, highlighting various announcements made during the occasion. The post suggests significant updat
so cool to see another blazing fast database built on vortex! Just announced at Interrupt! SmithDB. Agent traces have outgrown the databases built to hold them. That’s why we built SmithDB, a purpose-
At LangChain Interrupt 2026, multiple agent builder tools and frameworks were showcased, reflecting the growing ecosystem of agentic AI development. This post highlights the proliferation of agent-bui
Spend less time on triaging Ship fixes faster Catch regressions earlier Introducing LangSmith Engine: an agent that works autonomously to find patterns in your agent's failures 💻 Accelerate the agent
Super excited about the new deepagents version from @LangChain What’s in their water supply?? Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvemen
The future of self-improving AI systems is here 🚃 And we’re launching a ton of stuff to accelerate this future LangChain Interrupt 🚀 excited to talk to everyone, come say hi :) also watch the vid, it’
This looks great - kudos @LangChain team 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then
We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data problem. Agent traces can contai
We just shipped tons of new products to accelerate the full agent development lifecycle: https://www.langchain.com/blog TLDR: ✅ LangSmith Engine ✅ SmithDB ✅ Sandboxes ✅ Managed Deep Agents ✅ LLM Gatew
We're building a database 🤠 We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data prob
Chat LangChain has been revamped, and re-open sourced We've been working on a few improvements for a while now, and are very excited to finally open source them again! Want to see how a production Q&A
Deep Agents ship with durable execution out of the box: every agent step is checkpointed, so you get observability, fault tolerance, and human-in-the-loop for free. But as agents run longer and contex