LangChain

The 3 questions every agent builder should be able to answer:

✅ Where the agent fails
✅ How to reproduce it
✅ How to make it stop

Watch @jakebroekhuizen’s session: youtu.be/oVKGKdIAgtg

New in Managed Deep Agents 0.9: Reactions API for @SlackHQ Channels.

When it comes to building effective user agent experiences, loading states are underrated.

Now, you can build loading states and receipts using either heuristics, decision models, or custom logic.

Experience the best of Interrupt.

Access our archive and watch every session on-demand: interrupt.langchain.com/recordings

We simplified agent authentication, memory, and channels, and brought in web search as a pre-built tool for Managed Deep Agents.

Watch @VictorMoreira16’s full Interrupt NYC session for an inside look: youtu.be/XcsspzECTKA

LangSmith Signals from the last month:

✅ Claude Sonnet 5: #9 to #2 in model adoption. 51% more orgs using it

✅ gpt 5.6 luna: #3 to #1 in call footprints. 65% more calls

✅ Two open-weights models are now in the adoption top 10, but not for call volume

✅ Smaller, faster models dominate call footprints

✅ 60k queries handled
✅ 500+ customer accounts
✅ 85%+ of sessions resolved without a support ticket
✅ 250+ cases auto-detected + escalated to the right team

@snyksec Assist. Built on LangChain + LangGraph. Observability in LangSmith.

Full story: langchain.com/blog/how-snyk-…

.@factory_ai is sponsoring Interrupt London!

Stop by their booth during the event and go hands-on with the autonomy stack for enterprise teams.

For most global teams, flexibility matters as agent workloads grow, architectures evolve, and infrastructure requirements become more complex.

Join @AWScloud, @NVIDIA, and LangChain to learn how teams can approach the infrastructure layer behind production agent systems.

Save your spot: aws-experience.com/apj/smb/e/0700…

Sam on where decision models fit in a harness and how to use Jev with LangChain

langchain.com/blog/building-…

x.com/jaminball/stat…

the @OpenAI decisions API is now in @LangChain!

we shipped:

1. OpenAIDecisions: ask yes/no, choice, and score questions
2. model routing middleware
3. auto mode middleware

docs: docs.langchain.com/oss/python/int…

Next up on First Pass: a conversation with
@samecrowder from @LangChain
on decision models.

Jev from @typesafeai took the world by storm. Then OpenAI and Databricks released producs (Decisions API and ai_decide function) So what are Decision Models? We dig in!

Here’s an app we built called Restock, an office supply agent that works in @SlackHQ.

A quick demo ⏯️

LangChain developers can now easily build agents that can pay for things with @link (which works across any checkout online or programmatic payments over @mpp).

See their in-depth guide and demo! =>

we built Restock, an agent to automate ordering office supplies -pens, groceries, and more. it's open source, so you can fork it, modify it, and deploy it yourself with `mda deploy`!

payments are handled via @mpp. Restock is a great example of a complex use case which handles user authentication, secure secrets storage, and human-in-the-loop payments approval.

@stripe's Link + Managed Deep Agents. code 👇

now @link from @stripe makes it really easy to build agents that can make payments, with human approval on every purchase

agents like muse and instinct popularized payments for personal agents, MDA makes this easy to do for enterprise

You can now build an agent that:
🔎 Finds real products
🛒 Prepares purchases
💳 Pays
…with a person approving every order 👨‍💻

Ask in @SlackHQ, review the order, approve in @stripe's Link agent wallet.

Built on MPP + Managed Deep Agents.

langchain.com/blog/agents-th…

At #SFTechWeek? Join LangChain, @tavilyai, and @nebius for an afternoon bringing together enterprise leaders, founders, and engineers building with the agentic layer.

Info + RSVP: luma.com/tavily-gbt7

At Interrupt, The Agent Conference by LangChain, @OVOEnergy will be sharing how they built a flywheel to improve customer support agents.

Catch OVO's talk + more: interrupt.langchain.com/london

i'm most excited about the idea of "binding tools to skills"

this is basically progressive disclosure^2 -- when a skill is activated w/ relevant instructions, it comes w/ corresponding tools

great feature if you want to assemble context just in time for a given task

LangChain has ranked #12 on @paraform’s Talent Density Index.

As a growing team of builders making an outsized impact in our industry, we are proud to receive this recognition.

Want to join us? We’re hiring! langchain.com/careers