Search: “agents”

Next up: Hermes Agents on Tuesday in Lisbon 🇵🇹 as we work to make our office the go-to space for AI builders in Portugal, then we have another major one this week. we will this time be joined by the t

agents that are made to support specific teams end up helping a ton! great read on how we use deepagents every day to maintain our docs. Our docs are both a reference for our libraries but also a grea

Google Duplex, introduced in 2018, represented an early attempt at customer experience automation through AI-powered phone conversations, while Google Agents (expected circa 2026) represents a more ma

I've commented that 'this is the year of subagents', but that is largely an optimization problem. the inverse problem - having agents that compose and boss agents that manage/query them - is a capabil

🚀 deepagents 0.5 release 👉 Async subagents - kick off background tasks on any Agent Protocol backed server while you continue to interact with the main agent. Start multiple background tasks in parall

the most important abstraction in AI agents isnt the model — its the harness it orchestrates tools, memory, prompts. this is where all the alpha is deepagents is our take: built-in tools, memory, smar

@IeloEmanuele is on a roll! you can now use claude code's advisor strategy with @LangChain agents because langchain/deepagents are provider agnostic, you can use different providers for your advisor a

Claude Agent SDK tracing in LangSmith just got an upgrade. Now you can trace: → Subagents → Child runs inside MCP tools → Cost tracking + more Update to the latest Python SDK to try it out. Docs: http

we just added a langchain-task-steering middleware to our community registry, s/o @EHallvaxhiu for the contribution! keep your agents on track w/ ordered task pipelines. this is great for structured d

Curriculum Learning for harnesses - should we teach agents how we teach kids? start small and easy and progressively get harder for my research friends here's an under-explored area we're thinking abo

Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making complex reasoning difficult📄 So we teamed up with @lancedb

Really nice paper on harness-aware distillation for small language model agents. (bookmark it) It's a super interesting distillation framework for small language model agents that are deployed with a

Check out jes: An open source real-time guardrails for AI agents, powered by decision models like Jev from @typesafeai Built to guard every step in the agent trajectory: prompts, tool calls, tool resu

Cool to see classification models resurge in the era of agents. The effects of Jev are insane. Also very cool to see our emotion dataset built at @dair_ai used to test this new model, Julia-1. I spent

coding agents are moving fast from prototype to production. the infrastructure question is what's left. join @parthsareen from @ollama and @zainhas Hasan from Together AI at @AIconference for a breako

Nice paper discussing context trimming for agents. This is a hot topic at the moment, so it might be worth your time. Context trimming for agents is usually judged by how many tokens it removes. This

My conversation with @jerryjliu0. He's building @llama_index: document infrastructure for AI agents, the layer underneath everything models need to work. Did you know he's the guy whose tool half the

Interesting new approach to recursive self-improvement in agents. Systems that add a meta-level hold that level fixed. Systems that edit themselves have to leave part of their own editing machinery un

This is a sign of the future: 1) Explainability of AI actions is already tenuous 2) It gets more tenuous at extreme scale of multiple agents working over long periods because they produce so many thin

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 tagg

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 🎓 New course launch from LangChain Academy: I

Code-writing AI agents can solve complex problems more effectively than agents using other approaches, but deploying them requires executing potentially untrusted generated code within sandboxed or is

This post likely discusses how to evaluate AI agents built with LangChain using Harbor, a tool for testing and monitoring. It covers practical approaches for assessing agent performance, reliability,

i've been using cursor mobile on the go for the last weeks, and having access to all cloud agents from everywhere is really nice go on a walk, get an idea, dictate it in the app come back from walk to

💪deep agents harness The AI SDK Harness API now supports @OpenCode and @LangChain Deep Agents through a single unified interface. Use 𝙷𝚊𝚛𝚗𝚎𝚜𝚜𝙰𝚐𝚎𝚗𝚝 to run any supported runtime without changing your ap

excited to be speaking at @aiDotEngineer World Fair next week on Improving Agents, Continual Learning, and why we think a large part of it is...Data Mining! Trace Mining is how we understand agent beh

At @tryramp, engineers use Devin Desktop to bring their favorite agents into one place. With Devin Desktop they can dispatch, monitor, and jump between agents from a single surface with shared context

This post explores the concept of using ActiveGraph with event sourcing for AI agents operating under EU regulations, suggesting a potential architecture where detailed logging and event histories ser

Introducing Devin Desktop: the next generation of Windsurf Manage fleets of local and cloud agents from one surface Support for any ACP-compatible agent With a full IDE for when you need to jump into

Connecting agents directly to Snowflake, Slack, or BigQuery via MCP/CLIs is a multi-token disaster. They default to brute-force exploration, firing 20-30 tool calls just to rediscover context on every

🧑‍⚖️Evaluating Deep Agents with LangSmith on AWS Great deep dive blog with our friends at AWS on evaluating DeepAgents with LangSmith Covers datapoint and evaluator design for longer horizon agents ht

Learn more about the latest from @james_y_zou and our Frontier Agents Research team! To evaluate frontier AI agents, we need more complex tasks. But such tasks are also more prone to have design mista

make something agents want studying ActiveGraph by @yoheinakajima and apart from the concept the implementation itself is brilliant on the site it shares a prompt that will make my agent study docs, i

oh yeah first* automations - instead of dumb crons kicking of agents, devin has made them smart. try it - it is the first non annoying proactive agent impl ive seen https://x.com/russelljkaplan/status

/goal is really insane! It's how you can get the most out of coding agents today. For efficiency, I find it works best when you do planning before /goal. This ensures the agent has the right context a

Agents shouldn’t have direct visibility into env vars or credentials that can expose sensitive systems and data. Keeping secrets outside the agent’s context helps secure the env while still allowing a

Agents are too good at sounding right. And terrible at proving what actually happened, especially on complex, long-running tasks. So I built a fully traceable and forkable research agent with @yoheina

This post references a previous article discussing stateful agents broadly, which served as inspiration for Yohei Nakajima's project. The post likely documents how earlier discourse on agent architect

ICYMI: LangSmith Sandboxes are GA ✅ Agents get a real filesystem, shell, and package manager. Isolated from your infra. ✅ Works with Deep Agents, Open SWE, or your own code. ✅ Auth with the same API k

we've been building agents around the llm, starting with conversations, adding tools, giving rules, logging everything, and storing a form of it as retrievable state Active Graphs flips this. what if

LangSmith Engine feels like the missing CI/CD loop for AI agents , automatically detecting failures, clustering issues, proposing fixes, and generating evals from production traces. Agent engineering

This quote from our friends at @cogent_security says a lot: “At Cogent, our background agents can produce a huge volume of traces all at once. We need live observability into those systems, and SmithD

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

Introducing the Printing Press, a CLI-factory and a CLI-library. Built with @trevin. 🏭🖨📚 Most APIs suck for agents. Most MCPs suck for agents. Most official CLIs suck for agents. They waste tokens and

300 million agents. @clay runs all of them through LangSmith. This is what production-grade AI looks like at one of the fastest moving startups! .@Clay uses LangSmith to manage 300M agent runs a month

Want to run the same harness across multiple interfaces? Try ACP. Deep Agents ships with it out of the box. open-weight LLMs have come a long way on agent tasks! but the harness you wrap them in matte