Knowledge catalogue
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
Excited to have @Box in the Interrupt lineup! CEO Aaron @Levie will take the stage with @hwchase17 to discuss agents in the enterprise. If you’re attending our agent conference, don’t miss their sessi
'It’s pretty easy to change models these days... what creates more lock-in is when state starts to accumulate behind these APIs... memory has a lot of gravity.' - @hwchase17, Co-Founder & CEO, @LangCh
$NBIS announced a partnership with LangChain to integrate Nebius Token Factory with LangChain’s Deep Agents. The goal is to make it easier for teams building AI agents on LangChain to run those worklo
Rly looking forward to this Deep Agents workshop at @LangChain Interrupt Learning everything I can about Context Management and Deep Agents are the best examples of OSS best practices Harness to Fleet
thoughts after doing a bunch of synthetic data gen for eval + environment building - LLMs are incredible projections of the world bundled into a set of weights - but doing targeted extraction of certa
we just shipped delta channels in langgraph 1.2. as agents run longer and use more context, full-state checkpointing doesn't scale, but delta channel snapshots do. this new algorithm is now powering m
What’s special about the @LangChain community is that it’s built by those who are willing to take the extra step to push the boundaries of what’s possible. It’s a community that builds technologies th
+1 to this. I was recently on a cross-continental flight without wifi, so I brought up Qwen3.6 & Gemma 4 (via @ollama) in Deep Agents on my laptop. admittedly, they fell over on some more involved/com
Agent engineering is hard Deep Agents hides a lot of the weird systems complexity, but still gives you more room to customize the harness than almost any agent SDK I've used This is harder to build th
LangChain's JavaScript core package (@langchain/core) reached 4 million weekly downloads, marking a significant milestone for the JavaScript ecosystem of the LangChain framework. This achievement refl
Dealing with quirks introduced by switching models doesn't have to be hard -- we recently introduced a 'harness profile' API in Deep Agents as a solution. Profiles adjust system prompts, tool descript
DeepSeek V4 Flash is ~90% cheaper than GPT 5.4 Mini and ~70% cheaper than Gemini 3.1 Flash Lite For devs pushing ~500M tok/month, this is the difference between: GPT 5.4 Mini: ~394/mo Gemini 3.1 Flash
LangSmith settling the CLI vs MCP debate by simply offering both LangSmith is now a remote MCP server. Point any MCP-capable client at it, sign in with your LangSmith account, and your assistant can r
Swap models & view their capabilities! Try out in Deep Agents CLI: https://docs.langchain.com/oss/python/deepagents/cli/ here's model profile details look like in practice, using @NVIDIAAIDev's Nemotr
This post describes an AI system that monitors its own codebase to identify missing monitoring points and automatically generates pull requests to fix detected bugs, demonstrating autonomous self-impr
This is harder to build than it looks. Preserving full conversational context while swapping underlying model providers mid-flight is a surprisingly deep systems problem. Most tools drop state or forc
Deep Agents Deploy! https://docs.langchain.com/oss/python/deepagents/deploy Claude Managed Agents is really good But we need an open source solution Haven’t found any options so might need to build my
If you are selling a closed-source harness you're NGMI exactly why open source harness will probably win in the end we dont want to be at the mercy of every good or bad technical decision a closed ai
LangChain! we're working on a library to abstract over all the llm providers there's very few teams that have dealt with the quirks between providers at the scale we have it's written in effect but wi
> shipped the agent > opened the dashboard > latency: fine > error rate: fine > users: unhappy > checked the responses > technically correct > wrong tool called 3 steps earlier > no trace to follow >
100% agree on the Context Hub. Developers constantly tweak their approaches to manage context in their prompts with each new model and tool suite release. I would even say that the core problem we fac