LangChain

Powering the Agent Development Lifecycle. Makers of LangSmith and @LangChain_OSS and @LangChain_JS.

[LangChain @LangChain]

We're taking Interrupt on the road this fall with two new stops in NYC and London.

🗽 NYC: September 24

🇬🇧 London: October 13

Get your tickets now! https://t.co/fPMwmmdSxf

[LangChain @LangChain]

We’re hosting a meetup with @cognition on July 28th.

Come learn about LLM Wikis and how to give your agents open memory with OpenWiki.

RSVP while spaces last: https://t.co/qv5hoc3Fij

[Factory @FactoryAI]

Our CTO @EnoReyes sat down with Harrison Chase to talk models, harnesses, and what it actually takes to build a software factory.

[Colin Francis @colifran_]

OpenWiki 0.2 adopts OKF!

this is a big deal for two reasons:
1. OKF adds structured metadata to every doc and builds connections through cross links which means faster results, fewer tokens
2. the growing OKF tools ecosystem lets you visualize your wiki and the connections between docs

[LangChain @LangChain]

As agents take on larger workloads across the organization, governance becomes part of the system design, shaping how teams control spend, protect sensitive data, enforce internal policies, and manage access at scale.

On August 12th, we’ll break down the foundations teams need to govern production agents and where gateway infrastructure fits into the broader Agent Development Lifecycle.

https://t.co/VwNwf1vS2g

[Sydney Runkle @sydneyrunkle]

owning intelligence doesn't mean being able to afford the best model

it means owning the agent development lifecycle from model agnostic harness -> observability -> learning from each run

[Sydney Runkle @sydneyrunkle]

come join us in boston to chat about loop engineering and open models!

https://t.co/9jvBY32XVJ

[Jacob Lee @Hacubu]

This year @LangChain 🦜 🔗 has almost tripled in size, from ~100 people to over 300! That's a lot of new faces, and I'm often asked: "What made you join early? What was the company like at seven people?"

I'm always honest: I wasn't convinced right away. I mean, three years ago, the website looked like this: https://t.co/4o0IGsHTBG

Raw HTML and two emojis for a logo. When I told my parents I was joining, they asked, pretty directly, if I'd lost my mind.

I met @ankush_gola11 about a month after ChatGPT launched and the open-source started getting real traction. I was completely fascinated by the technology, but my reaction to his pitch was "cool - good luck!" In addition to said website, I had just come off six years founding a company, and didn't want to jump back into an early startup.

A few weeks later, a client wanted to build an LLM-powered extraction pipeline - nowhere near as trivial then as it is now. I tried an early version of LangChain.js, and it worked great, so I kept exploring and found the section on agents.

The magic there completely hooked me. It truly seemed like something out of science fiction.

Thankfully, @hwchase17 and Ankush were still looking to round out their founding team, and I got to see how they operated up close. Unlike most startups, LangChain has never had a name recognition problem, and I knew firsthand how easy it was to start chasing GitHub stars and other vanity metrics.

But from the start, the team was serious about seeing through the fluff, listening to the community even when tempers flared, and building what actually solved user problems. They weren't always right - I joke that back then we were a six-month-old startup with a year of tech debt - but I admired how quickly they'd throw out popular beliefs and abstractions the moment evidence showed they were wrong or wouldn't scale. Anyone remember ConversationalRetrievalChain?

The website itself was emblematic of this "zero tolerance for bullshit" approach (as Harrison puts it). The small early team could have spent time creating a beautiful marketing site, but marketing wasn't the problem back then (though we're hiring now!). A parrot and a link emoji was enough. Time was better spent shipping.

So, what was it actually like at seven people? Different principles, but ones that rhyme with the old ones. "Zero tolerance for bullshit" has become "act with maximum agency". Our most interesting Slack discussions start with "Hot take", and it's a mark of dishonor if people react with ice cubes, meaning it's not extreme enough to encourage a rethink of a longstanding belief.

But the north star hasn't moved: build something great, and cut everything that isn't that.

There's a lot of story left to write. We're hiring across product, engineering, office management, people ops, and more! If that sounds like a place you'd thrive, come find us.

P.S. the OG site is a lot more clever than it looks - see https://t.co/M4gwyYsLyP

[Brace @BraceSproul]

I just published a short YouTube video on OKF in OpenWiki. It's only 3:30 long, so if you're curious what OKF is, what it'll mean for OpenWiki, and why we decided to adopt, you should give it a watch!

https://t.co/LfkIFP8mo3

[LangChain @LangChain]

OpenWiki is adopting OKF in 0.2!

OKF will lay the ground work for a lot of new exciting features and capabilities in OpenWiki, and it'll allow us to take advantage of the growing OSS ecosystem around OKF!

Checkout @BraceSproul's short blog on what this means for OpenWiki, and its users:

[Brace @BraceSproul]

https://t.co/pmaoSBeaMb

[Brace @BraceSproul]

https://t.co/pmaoSBeaMb

[Brace @BraceSproul]

Super excited to officially adopt OKF in OpenWiki! There's a ton of exciting things this will allow for & make easier. I wrote a super short (~5min read) blog on what this will means for codebase memory in OpenWiki

Tldr;
- better structure of wikis
- foundation for search & retrieval tools (not just agentic search)
- a strong oss ecosystem already

[LangChain @LangChain]

New video from @its_ao.

How to run @NVIDIA Nemotron 3 Ultra with @baseten + Deep Agents Code.

✅ 550B parameters, up to 300 tokens per second
✅ Terminal agent w/ skills, sub-agents, MCP support
✅ First-class tracing through LangSmith

[LangChain @LangChain]

🎧 Apple: https://t.co/BFlHg8NQGH

🎧 Spotify: https://t.co/adiJoxN2dj

⏯️ YouTube: https://t.co/ctKpRYfvIl

[LangChain @LangChain]

Brand new Max Agency with @FactoryAI CTO & Co-Founder @EnoReyes!

[Harrison Chase @hwchase17]

New Max Agency with @FactoryAI CTO & Co-Founder @EnoReyes.

This was a particularly fun one. Since we're both building harnesses, we nerded out pretty deep.

Awesome conversation on why the harness matters more than the model running underneath it, how Factory built Missions, + more.

⏯️ YouTube: https://t.co/krvNwR6bJO

🎧 Apple: https://t.co/l518wBr2IZ

🎧 Spotify: https://t.co/szgWgMPYag

[LangChain @LangChain]

How @Box uses Deep Agents middleware for Box Agent:

1️⃣Citation generation: Streaming of the answer + citation generation happens in parallel to avoid user interruption

2️⃣Prompt caching: Injects caching on multi-turn conversations, reducing cost + latency

3️⃣Context management: Summarizes conversation history after exceeding 170k tokens, preventing context overflow

https://t.co/BJVMvLwVIy

[LangChain @LangChain]

Governing agents requires teams to think across the full system, from authentication, audit logs, rate limits, fallbacks, and centralized spend controls.

Our latest conceptual guide, breaks down the foundations teams need to manage access, protect sensitive data, enforce policies, and control costs as agents move into production.

https://t.co/d3RnFxFdKk

[Brace @BraceSproul]

Most agents fail because they don't have the right context, but because the model is weak.

That's the problem LLM wikis are trying to solve: a structured knowledge base an agent can query to understand a codebase, product, or domain. We recently open sourced OpenWiki, our take on building and maintaining one of these.

We're hosting a meetup in our new office to dig into this pattern with @jacobtpl from @cognition's research and engineering team.

I'll walk through how we actually build these systems, and push on whether "wiki" is even the right frame for what they're doing. Then Jacob will share how Cognition built DeepWiki.

If you're building agents and thinking about context, come argue with us: https://t.co/7SoqhBh5iz

[LangChain @LangChain]

ICYMI

[LangChain @LangChain]

Fleet in Slack just got a big upgrade.

Now you can bring any Fleet agent into Slack in one click. Give it a custom identity. Use it in channels and threads. Hand off files, approve its actions, and keep all the context of your work in one place.

Read more in our blog: https://t.co/wqY3tlFJg0

[LangChain @LangChain]

Upcoming stops:
📍8/11: Atlanta
📍8/27: Silicon Valley
📍9/29: Boston

Get more info + RSVP for a LangSmith Roadshow event near you:
https://t.co/rM5JUNiL63

[LangChain @LangChain]

LangSmith Roadshow:
✅ A half-day, hands-on look at LangSmith Engine + Managed Deep Agents
✅ Live demos, customer stories, lab sessions, and more