Harrison Chase

Open source coding harness!

RT Sure (e/acc) Re @LangChain really outdid themselves with dcode. It’s currently one of my favourite harnesses for coding. 🙌🏽

we did a bunch of work to standardize how coding agents trace to langsmith

RT LangChain Cursor, Copilot, Pi, and OpenCode tracing: Now in LangSmith. Full session observability, no extra instrumentation. ✅Identify, group, and query any coding-agent trace with the same stable keys, regardless of which agent produced it ✅See the full run tree: turns, model calls, tools, and subagents ✅Token usage and cost per session, out of the box Blog by @harisaiharish https://www.langchain.com/blog/your-coding-agents-are-a-black-box-heres-how-to-crack-them-open

RT Brace Who’s actually using OKF? What’re your reasons behind it/thoughts? We’re going to adopt it in OpenWiki for a couple reasons: - it’s a simple spec. Supporting it doesn’t mean changing much (basically just yaml front matter in each .md file) - the front matter spec should make it easier to build & use deterministic search & filtering tools against the docs (keyword, full text, etc) - when we eventually build a UI for OpenWiki, it’ll likely help with exposing content to humans (better sectioning, discovery, preview details, etc) Anyone else started using it yet? Super curious to hear more

RT Alex Olsen We need to talk more about model <> harness <> task fit This 🧵 is your excuse to learn why this is so important

> For me, agentic performance on spreadsheet tasks is the whole of Shortcut existence. So I'm going to beat competitors by obsessing over the harness. custom harness is the only way you will beat the labs agentic experience heres how to build one: https://www.langchain.com/blog/how-to-build-a-custom-agent-harness

RT Brace OpenWiki 0.1.2 is now out, with a ton of changes! Notable updates: - 🧑‍💻 QOL: `openwiki --init` and `--update` run Code Brain by default (most popular use case!) - 🔙 Specific prompting to document backlog tasks within wiki files - 🥳 8 new contributors, with this release including 11 total unique contributors!! Try it out today, and put up a PR if you have a new feature, fix or improvement! https://github.com/langchain-ai/openwiki

if you want to learn more about why coding harnesses are not going to be the optimal harness for science: https://www.youtube.com/watch?v=RjpTrffSMjE

RT Nicholas Larus-Stone Re @LatchBio has been on a tear recently. It should be obvious to everyone why coding harnesses are not going to be the optimal harness for science, but it was nice to see someone put numbers to it

RT Himanshu | AI Engineer Started contributing to LangChain's OpenWiki. Today I got a comment from @hwchase17 "Thanks for contributing!" Small moment, big motivation. Time to keep shipping and contributing more to open source. 🚀 #opensource #LangChain #AI #buildinpublic

RT Josh Rosen Don’t let them tell you it’s all about the models. It’s just as much about the infra.

LangSmith does this for you - in the cloud: LangSmith sandboxes & LangSmith deployments - any model: LangChain integrates with 100s - harness: deep agents - tracing: langsmith observability - recursive improvement: langsmith engine

📕LLM Wiki Webinar with @BraceSproul @devstein64 @jeffreyhuber is now on YouTube! Two of my favorite insights from this webinar: "Wiki as a cache" - @devstein64: basically, the purpose of a wiki is to keep things that are commonly looked up or accessed more top of mind/readily available. What goes in the wiki should be updated and organized with that in mind "Wiki is a set of hyperlinked pages" - @jeffreyhuber. The evolution of memory (in my view) has gone from: 1. single string 2. file 3. set of files in a directory (wiki) as you think about scaling up - as files grow, the file structure matters less, and you need links between pages. The internet is a set of hyperlinked pages - so that definitely scales! Watch it here: https://www.youtube.com/watch?v=Lsut4TCfygw

RT Brace OpenWiki now supports ChatGPT login!! Use your subscription instead of API credits when running OpenWiki Thank you @Topzsixx for the contribution to add support! Try it out today 👇

RT Ankush Gola I use OpenSWE multiple times a day directly from slack. Makes it super easy to go from conversation -> code

RT Thomas Reaves 1/ I watched LangChain’s webinar on LLM wikis and agent memory and wrote up a working paper from my own small agent-fleet experiments: Soft-Cache: A Human-Supervisable Coherence Protocol for Persistent Agent Fleets https://github.com/treaves-GSD/soft-cache-agent-indexing

great overview of general purpose brain!

RT Brace Another big langchain week

🚀langchain launches this week: all about open source models and memory! First: open source models. We partnered with @NVIDIAAI to launch a NemoClaw DeepAgents blueprint. This pairs Deep Agents (our open source, model agnostic harness) with Nemotron 3 ultra (powerful OSS model) and OpenShell (enterprise ready run time). Blog: https://www.langchain.com/blog/langchain-and-nvidia-launch-the-nemoclaw-deep-agents-blueprint Second: memory. LLM wikis continue to intrigue us. @BraceSproul @colifran_ released a new version of OpenWiki focused on "personal brains" - creating wikis from gmail, internet, etc: https://github.com/langchain-ai/openwiki open models and memory pair well together as well. They both contribute towards companies and enterprises owning their whole stack - from the model level all the way up to the context level

RT Brace OpenSWE is one of our most widely used agents throughout the company. Since July 1st it's been tagged over 700 times in Slack! This doesn't even count the reviewer agent, tagging it in GitHub, or tagging it from Linear tickets It's 100% open source too

RT Colin Francis great viz by @BraceSproul to put this in perspective. the really important part of this is that OpenWiki is additive!

Sierra isn't the first to build this - Ramp, Stripe, CoinBase also have If you want an open source version - check out OpenSWE: https://github.com/langchain-ai/open-swe We use it internally (mostly for coding). Model agnostic, fully OSS but integrates seamlessly with LangSmith for o11y

RT Brace OpenWiki general purpose memory is meant to be complementary to codex/claude code memory: it's proactive & ambient, meaning it'll automatically go out into your world (via connections like gmail, x, notion, etc), discover what you're working on or interested in, and remember it for future reference this paired with reactive memory (codex/claude memory) leads to an incredibly powerful agent that knows everything about you to have truly comprehensive memory, you can't stick with one or the other since both types are useful and important

love this framing of memory as "proactive"

RT Colin Francis agent memory has always been reactive. OpenWiki makes it proactive. connect to sources, tell it what you care about, and your agent hits the ground running . what we're building is really exciting! try it out and get involved, it's open source! 👇 https://github.com/langchain-ai/openwiki

RT Evangelos Kostopoulos Thank you @hwchase17 @BraceSproul @devstein64 @jeffreyhuber for the LLM Wikis session today, I absolutely loved it! Really grateful you keep these sessions open and honest about what actually works in the industry. The idea I'm taking home is eventual correctness, where the wiki self-corrects over time until it converges on the truth. That's exactly what I'm chasing with my agents too. Thanks @LangChain for hosting, can't wait for the next one!

RT LangChain "Whoever Jerry is, he was excellent." That's a customer talking about an agent. @PodiumHQ's Walker Ward sat down with our COO @j_schottenstein to share how LangGraph + LangSmith helped his team take their agents from prototype to production.

RT Colin Francis OpenWiki Brains v0.1.0 is out 🎉 personally really excited about personal brains! these maintain context about you and what you're working on, interested in, etc. webinar for all things wiki happening now: https://events.langchain.com/webinar/llm-wiki/

big update to openwiki - it now supports two modes: - code brain: create a wiki for a code base - personal brain: create a wiki for more general purpose tasks (email, web, etc) webinar at 11am PST (5 minutes!) where we will be talking about wikis! https://events.langchain.com/webinar/llm-wiki/

RT Brace http://x.com/i/article/2075248391349768192

this is going to be a fun one! clay is one of the most ai-forward thinking companies i know of lots to learn here if you're in NYC

langsmith for coding agents

Setup evals with… terraform??

RT Adam Łucek You've heard of Infrastructure as Code- but agent evals can now ride your existing Terraform setup! I've been using the new LangSmith Terraform provider to auto-provision online evals + monitoring alerts for my agents, and think you should too. Here's how 🧵

RT Nick Hollon spent a ton of time working on this!! so happy to see the results come out. very impressive model from @NVIDIAAI that we fit our harness to so we could get better performance!

RT @cvmilo00: tbf this is one of the best repos on github, specially if you are REALLY into AI

Bigger update coming tmrw, but a bunch of small fixes today!

i want to build a more opinionated/detailed coding experience (for prompt optimization, eval set creation, some more things) what is the best way to package it all up?

Guess what we added someone else to this webinar: @jeffreyhuber, ceo and cofounder of chroma What does a vector database think about the concept of “wikis”? Come find out! It’s turning into a party

Congrats to prime intellect! Love partnering with them on LangChain labs work

Great opportunity!

RT Niko Come help us scale @harvey’s model training team. If you’re interested in bringing frontier agent research into the Harvey product and working with: - @baseten to scale up RL to 80M+ token virtual datarooms - @PrimeIntellect to create structured agent training environments from unstructured legal data - @FireworksAI_HQ to navigate the quality <> cost Pareto frontier with inference-time routing and advisor models - @LangChain & LangChain Labs to build efficient verifiers and close the observability <> training feedback loop - @appliedcompute to post-train open weight models and high-volume agents for end-to-end legal tasks - @EngramLab to create an entire synthetic law firm and firm knowledge memory systems for better / more efficient open-world search - @trajectorylabs & @NVIDIAAI to shape the frontier of continual learning and sovereign AI for high-stakes domains - @mercor_ai & @SnorkelAI to build out Legal Agent Bench and other benchmarks across legal and other verticals and other projects like this, then this is the role for you. Apply here: https://www.harvey.ai/company/careers/d78083d9-a203-4ae4-b4b9-454d65df3702

RT Gabe Pereyra We are hiring for @Harvey’s model training team. This team will help Harvey expand from the application layer into the model layer and from legal into high end knowledge work more broadly. We are hiring AI researchers of all seniority, particularly those with experience post-training frontier or open source models. Our program is centered around large-scale model training, synthetic data generation, long horizon reinforcement learning, and rigorous evaluation in real world deployments. We are scaling-pilled and believe that nothing beats the combination of larger models and better training data. We’ve been able to generate incredibly realistic legal environments and validated that this allows us to post-train open source models to achieve frontier performance with agents. We plan to scale up these data generation and training efforts significantly across legal to start, and eventually other verticals. As a researcher, you will have access to thousands of GPUs and unique training data from our product and customer relationships. Your research will inform Harvey’s product strategy and power AI used for some of the most economically and societally impactful work in the world.

Love partnering with baseten to make sure everyone can use open weight models in deep agents

Really excited to partner with @nvidia on the NemoClaw Deep Agents Blueprint Deep Agents is a fully open source agent harness that we are tuning to make perform incredibly well with open models

RT Alex Olsen I cannot put into words how stoked I am on this It's not an understatement to say that this blueprint could represent the future of enterprise inference

gpt-5.6 sol isnt the only thinking launching thursday we're also releasing a big update to OpenWiki (auto create wikis of code bases... and more?) we're also going live with a webinar to talk all things wiki: https://events.langchain.com/webinar/llm-wiki/ (openwiki: https://github.com/langchain-ai/openwiki)

agents for ad spend

RT Anuj Patel The most important part of an AI agent isn't the LLM. It's what surrounds it. 👇 The first image made it click for me. While exploring LangChain Deep Agents, I ran the same prompt. Same model. Almost the same answer The harness decides how the agent thinks and acts That's why two agents using the same LLM can behave very differently My takeaway: As models become similar, better harnesses will matter more

RT Mykhailo Chalyi Re @hwchase17 ATIF proposes to have steps as a field in JSON document. This means that more or less longer sessions especially with some binnary content would result in unprocessable huge JSON file. Sounds like no starter. My best guess community should adopt PI session format, or codex.

is anyone standardizing on ATIF as a format for agent traces? or a different format? or is it still wild wild west, roll your own

deepagents is our newest open source project - an open source, model agnostic agent harness this is maybe the most important academy course we've launched

llm wikis are a glimpse of the future of what agent memory looks like this blog i wrote resonated with a lot of folks will be discussing this (as well as some updates ive made to my beliefs since this!) this thursday with @BraceSproul @devstein64 https://events.langchain.com/webinar/llm-wiki/

How a local-first personal AI agent uses orchestration, memory, tools, LangGraph, background workflows, and child agents

RT 𓁟 SYD 🛸 I wrote an article on the core Agent architecture for Row-Bot. How it uses a @LangChain LangGraph agent at its core for the main agent, background workflows and child agents. Each is a full LangGraph ReAct agent Here is the full article @hwchase17 : https://x.com/SydSachar/status/2074499930236821550

Good blog from viv on how improving agents (via rl, harness Eng, anything) boils down to a data mining problem over traces

RT Viv http://x.com/i/article/2073138207986966528

RT Coframe We drove 410% conversion lift on @Replit's enterprise funnel, 2x-ing the number of demo requests. All in a matter of months. "Coframe makes you feel like you have a team of 100 people. There's nothing on the market like it." ⧉ x ⠕

RT Taylor Dolezal Come join us on Thursday! It'll be a great session you'll want to add to your MEMORY.md 😄

devin has a hot take that wikis are NOT the right abstraction should be a fun webinar!!

RT Devin Stein does your agent need a wiki? should humans and agent use the same wiki? should you have one wiki or many wikis? if you're wiki-curious, join @BraceSproul @hwchase17 and I on Thursday! you don't want to miss it @dosu_ai 🤝 @LangChain

RT Brace We're going to be discussing LLM memory & wiki's this week with @hwchase17 and @devstein64! Don't miss it

RT Brace big things happened over the weekend!

RT LangChain Last minute webinar this Thursday Will cover all things related to "LLM Wikis"

🚨Emergency webinar: LLM Wikis and how to give your agent memory LLM Wikis are so hot right now - OpenWiki by @BraceSproul up to nearly 7k GitHub stars in less than a week I'll be chatting with Brace and @devstein64 about Wikis this Thursday: https://events.langchain.com/webinar/llm-wiki/

RT Caspar Broekhuizen Soon most agents for work will run in the cloud and communication with them will happen almost exclusively in your existing work channels (Slack, Teams, ...) This hasn't become the norm yet because local-first platforms are much easier to engineer. Running on the user's machine avoids the harder product surface: hosted VMs, identity, sharing, permissions, long-running state But these mechanics are necessary for agents to become shared team software so will become table stakes

RT LangChain Product Manager @BenTannyhill on why LangSmith Engine routes trace investigation through screener + verifier sub agents instead of letting the main agent read everything.

RT Julia Schottenstein new favorite episode of Max Agency with @bentannyhill and @hwchase17 ! They sit down to talk about how we built Engine, our agent for agent engineering, at @LangChain. So much to love about this episode - spans everything from the who builds agents, how we did it, and tools we used to get it done. if you can't tell, I've never been more excited about a product at LangChain! listen here 👇 https://www.youtube.com/watch?si=wp2AKnhbVnFSCzb8&v=YqjR4vQwbTc&feature=youtu.be https://podcasts.apple.com/nz/podcast/the-best-ai-agents-are-secretly-teams-ben-tannyhill/id1891551672?i=1000775182821

RT Varun yadav Re @hwchase17 Yes using deep agents and okf both for my wiki. https://github.com/varunyn/wiki-langGraph

anyone looked into or using Open Knowledge Format (https://github.com/GoogleCloudPlatform/knowledge-catalog/blob/main/okf/SPEC.md) for their wikis?

(deepagents existed ~10 months before EVE, but...) yes - the agent industry has shifted from: ~agent frameworks~ (langchain, ai sdk, llama index) to ~agent harnesses~ (deepagents, claude agent SDK, EVE)

RT Min Choi This is actually useful. LangChain just released OpenWiki. It's an open-source agent that creates a wiki for your codebase, connects it to your coding agent, and keeps it updated as your repo changes. Your AI coding agent gets long-term repo context without stuffing everything into CLAUDE.md. Here's how to setup. Save this.

RT Brace OpenWiki is at 1.7k stars in just 3 days! Right now it's just for codebases, but we're working to expand it to everything for memory. What do you want to see in a general purpose memory wiki agent? https://github.com/langchain-ai/openwiki

OpenWiki up to 1.7k GitHub stars in two days Most common ask it to make it more general purpose (not just coding) What sources do people want to see? Notion? GMail? Slack? GDrive? Internet search? Other?

RT it’kanyirijames WorkPods agent memory as wikis. @langchain #openwiki @cognition #deepwiki @karpathy #llmwiki @Factory #autowiki @hwchase17 @BraceSproul

RT kammeows So i built LangGraph Sync. it’s an interactive web tool that visualizes langgraph workflows & lets you edit & bidirectionally synchronize the graph & code in real time. you edit the visual graph, your python source code updates. you edit the python code, the visual graph updates.

wikis!

RT Brace OpenWiki is designed to run in the background, without you needing to think about it It'll generate docs, update your AGENTS.md so your agent automatically knows how to read the docs, and update itself automatically. All of this allows you to set it up once, then forget about it! To let it update itself automatically, we've included a GitHub workflow you can copy into your repo which will run OpenWiki nightly to update its docs! Check it out today and start using OpenWiki locally: https://github.com/langchain-ai/openwiki/blob/main/examples/openwiki-update.yml

RT LangChain Your coding agent bill doubled and nobody can tell you why. Here's the actual reason: Claude Code, Cursor, and Copilot all log activity in different formats. The second your team uses more than one (they will), your visibility goes to zero. We built LangSmith to fix this. It traces Claude Code, Codex, Cursor, Copilot, Pi, and OpenCode into one consistent format. ✅ Same trace tree ✅ Same metadata ✅ Same query syntax …regardless of which tool actually ran the session. Everything you need to know: https://www.langchain.com/blog/fix-your-coding-agent-bill

RT Colin Francis huge week of really exciting launches at langchain!

RT LangChain 🎧A look at how we built LangSmith Engine with @hwchase17 + @bentannyhill

RT Nick Hollon so proud to be working with a bunch of people who are absolutely crushing it! check out all these new things if you haven’t had a chance to yet. huge week for us here @LangChain!!

Special episode with @bentannyhill on the Max Agency podcast. A month ago, his team shipped LangSmith Engine, our agent that hunts through your agent's failures, prioritizes issues, and drafts the fix. We dive into the architecture decisions -- from how we used sandboxes to how we created subagents. And we also discuss an interesting challenge -- how we were able to build evals for an agent that never stops running. Check out the full conversation ⤵️ ⏯️ YouTube: https://youtu.be/YqjR4vQwbTc?si=wp2AKnhbVnFSCzb8 🎧 Apple: https://podcasts.apple.com/nz/podcast/the-best-ai-agents-are-secretly-teams-ben-tannyhill/id1891551672?i=1000775182821 🟢 Spotify: https://open.spotify.com/episode/5lT8hva20sVmJ0WiVCLAaO?si=81119f1d193e4f7d

Ton of interest in wikis We’re going to push hard on open wiki this weekend What do you want in your wiki? Different sources? Different structure?

RT Brace You shouldn’t need to think about your memory or agent docs! It should *just work* which was the thesis we went into this with

RT Caspar Broekhuizen Imagine if, as an engineer, your working memory of a codebase was wiped every time you started a new ticket Sounds ridiculous, but this is functionally what happens to agents whenever we start a new thread Maybe your company is ahead of the curve and has committed context like 𝙰𝙶𝙴𝙽𝚃𝚂.𝚖𝚍 and skills. But most problems are both complex and niche, so agents still waste a ton of tokens rebuilding the context they need to solve them Code is the current state of a system, but it is not enough to understand the whole thing. OpenWiki adds the missing context layer and maintains it automatically, so agents know how pieces fit together, which patterns your company values, and where to look before making changes. Really excited for this release

RT LangChain Interrupt 2026 is coming to New York City and London this fall. → Hear from engineers + teams shipping agents in production → Keynotes from @hwchase17 + industry leaders on what's next for agents → Hands-on workshops with LangChain product experts → First look at new LangChain products Tickets go on sale next week and seats are limited. Sign up to get notified when tickets drop: https://interrupt.langchain.com/

RT it’kanyirijames Introducing Computer in WorkPods. Computer lets your agents use a browser. Every task that lives on the web, behind a login, a form, a button, now runs inside the same session you're already watching. It makes WorkPods able to act anywhere, even where there's no API. Built end to end on @LangChain . @hwchase17 @LangChain @bromann @BraceSproul @Baconbrix @jakebroekhuizen

RT Sydney Runkle if you want agents to do work at scale (like security triage, trace analysis, document parsing), they need structured workflows enforced w/ code map reduce is a great example -- exactly the kind of pattern enabled by dynamic subagents in deep agents! https://x.com/sydneyrunkle/status/2071629451712983319

"agentic map reduce" is a nice name spawning subagents programatically allows you to do these advanced agent patterns, where you want some determinism to control how agents are created/run check out dynamic subagents in deepagents for a way to do this: https://docs.langchain.com/oss/python/deepagents/dynamic-subagents

RT LangChain OpenWiki is the easiest way to document your codebase, built specifically for agents to consume. OpenWiki can generate repo docs, automatically update them as your codebase evolves, and do Q&A over your docs and codebase! https://github.com/langchain-ai/openwiki

RT Brace Just published a YouTube video walking through OpenWiki. Setup and configuration, how it works, what it targets, and how to automatically keep your docs up to date. Check it out, and see the OSS GitHub repo with the OpenWiki code! https://youtu.be/nIVu3zfYprI https://github.com/langchain-ai/openwiki

harvey is ripping!! honor to work with them

wikis for memory are all the rage - we wrote about this yesterday today we're releasing an open source example for doing this code bases

RT Brace Excited to release OpenWiki! OpenWiki is the easiest way to generate and maintain documentation in your codebase, built specifically for agents to consume Get started with a single command: `openwiki --init`

RT Brace http://x.com/i/article/2072361450925096961

RT Nick Hollon this video goes into more detail on how our integrations with @harborframework actually work! if the blog yesterday caught your eye definitely watch this! thanks for all the help @kobe0938 @alexgshaw!!

RT LangChain You can now run recursive language model (RLM) workflows in Deep Agents. Everything you need to know in 6 minutes from @sydneyrunkle.

More and more developers turning to glm5.2 as a daily driver for coding Here’s how to use it with deepagents code