Search: “agents”

DeepAgents Deploy is great, you get - a fully open agent harness (no hidden stuff, inspect everything) - managed infra - can use any cocktail of models including Open Models - and everything is traced

This is so good @hwchase17 walks through the complete setup of a Deep Agents deployment step-by-step It’s a great example of getting started fast with Deep Agents from the CLI! DeepAgents Deploy is th

last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each requirement and runtime capability that meets it, here's the lineup

Great podcast episode that covers OpenAI's Symphony, which dispatches autonomous agents (codex workers) with their own worktrees and tasks. I've found it works well with a layer above Symphony, where

Really enjoyed reading the post - I'm exploring Deep Agents and Pi harness's today also motivated by @DiegoARRG post. Harness, Memory and Skills in house - LLMs if you cans afford too except for compl

the team spent a lot of time totally revamping docs with care❤️ ofc for LangChain+deepagents DX but lots of ppl use them as general learning guides on patterns across Agents, Context Eng, Infra, Prod,

European businesses are rapidly expanding their use of AI agents. More than half of the AI use among our EU enterprise and business customers now involves these tools, and the number of small business

Laptops open across the room. Yesterday at AI Engineer New York, @cjav_dev + Harrison Stall of @AnthropicAI on Claude Managed Agents. Claude plans the work, then coordinates the agents. Workshop recap

Free SemIf this week is useful. Typed outputs + probabilities look like a cleaner way to route agents than parsing LLM text every time. jev is a new type of model - 'decision models' there are a few o

Grounded Confidence is here for Extract! 🦙 When your agents and workflows depend on extracted data, you need to know how accurate that data is. We’ve added confidence scores to give you a better read

Banger paper from Google Cloud AI Research. If you follow autonomous research agents, this one is worth your time. ScientistTwo takes a problem from a human expert and runs the full discovery cycle wi

I think Claude Managed Agents strikes the right balance here, the sandbox is optional and can be spun up independently of the rest of the agent loop. I recently ported an old project that was focused

Great reporting. Bad framing. The OpenAI and Hugging Face incident is serious. Agents coordinated, reward hacked, shared information and exploited real infrastructure. But calling this an “AI civiliza

Brain makes a user’s full history available to Computer without loading all of it into every prompt. Agents can explore it on demand, verify claims against the underlying evidence, and keep it current

ChatGPT Work is OpenAI's fighter in the highest stake product category in history: bringing the power of coding agents to the masses. It's also how a billion users will soon use ChatGPT by default. I

Soak testing for AI agents involves running agents continuously over extended periods to identify performance degradation, resource leaks, stability issues, and edge cases that may not appear during s

This post discusses using deep agents and OpenKeyFlow (OKF) for a wiki project built with LangGraph, a framework for constructing agent-based applications. The developer is leveraging LangGraph's capa

Can coding-agents replicate scientific ML papers? We know this is possible because we can already do this @dair_ai. Still a great read. So they try to replicate an ML paper from its materials alone. T

LLM Wikis are being slept on. I argue that creating knowledge bases with LLMs or coding agents is one of the most valuable applications of AI today. It's about being intentional in building and scalin

Excited to see @cohere open-source how they use AI coding agents to maintain their vLLM fork. 🙌 Keeping a long-lived fork in sync is tricky. Their agent treats it as a control loop: rebase onto each u

What happens when AI agents collaborate on open science? At @aiDotEngineer World’s Fair, @james_y_zou will share work on EinsteinArena and DSGym, from multi-agent math discovery to better evaluation f

🧠LangSmith Engine as Sleep Time Compute Memory for agents is often described as “sleep time compute” or “dreaming” This involves running a background process to analyze agent trajectories and update a

you need docs built for agents Docs are the eyes and ears of Agents. But we're moving so fast that they are always outdated. So hence an outdated doc also confuses the models. But it's also hard keep

Deep Agents are an AI concept that Sydney Runkle explains concisely in under 90 seconds, likely covering how agents can be designed to operate with deeper reasoning and decision-making capabilities. T

Now you can text Hermes on iMessage 💬 It's just that simple. Photon brings the BEST agents to everyone where they already are -> http://tryphoton.ai Your Hermes Agent now lives in iMessage via @photon

Fleet agents now come with a computer! They can write and execute code, which is helpful for general purpose tasks beyond coding Fleet agents can now securely write and run code. With computer use in

Great to see a GBrain x ActiveGraph crossover here Great retrieval pairs well with almost anything you want to do with agents Gbrain is what an agent *knows* — a durable markdown/git knowledge substra

Yohei Nakajima discusses the emergence of self-improving AI agents, likely exploring how autonomous agents can iteratively enhance their capabilities and performance through feedback loops and learnin

LangChain Academy Course: LangSmith Fleet Essentials Learn how to build your own agents with LangSmith Fleet. Anyone can now build, use, and manage an agent fleet for complex daily tasks, without writ

nice write up from the HuggingFace folks aggregating works on defining agents, harnesses, environments, RL, etc. The more we can roughly have a shared vocabulary the better…I still find it confusing (

Kafka, but for agents! i'm excited to open source Active Graph: an event-sourced reactive graph runtime for long-running, agents 🔄🧠 events/logs projects a graph. reactive behaviors react and affect th

you can condense long horizon evals with agents into smaller subsets that still let you test intended behavior. i'm currently evaluating an agent that runs for 30+ minutes, and analyzes thousands of t

two years ago we started building agents to automate work. turns out these are really useful, so there’s a LOT of runs and long traces that are hard to reason about now, use an ambient agent (engine)

LangChain released Deep Agents v0.6, described as their largest release to date. The announcement was made by Harrison Chase on X (formerly Twitter), indicating a significant update to the Deep Agents

some good discussions and experiments around stateful agents in the replies, but seems like we’re not quite there yet, as in we’re starting to track memory and traces, but not quite agent capability a

Many AI agents in finance rely on extremely high quality context engineering from documents 📑 They can be roughly divided into two categories: 1️⃣ Repetitive, operational work common in back-office us

This is one of the first real continual learning systems for agents in production. Not just monitoring. Actually getting better over time. LangSmith Engine is how we’re spinning the always-on, self-im

Had the honor of sharing the stage with the one and only @sydneyrunkle at Interrupt 2026 to talk about Deep Agents. Sign-up for the Managed Deep Agents waitlist today to get early access! https://www.

ICYMI: 1️⃣ LangSmith Engine 2️⃣ SmithDB 3️⃣ Managed Deep Agents 4️⃣ LangSmith Sandboxes: Now Generally Available 5️⃣ Context Hub 6️⃣ LangSmith LLM Gateway 7️⃣ Sandboxes, Prebuilt agents, + free model

it almost never makes sense to use real api's for your evals. with how good coding agents have become, i will pretty much always opt to create a fake mock server for my agent to hit. the workflow is u

# Agents as Products This post likely explores how AI agents can be effectively deployed as standalone products, discussing their practical applications and advantages over traditional software soluti

The future of Math is mathematicians and AI agents working together. Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a multi-agent system designed to actively collaborate with human e

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is bu

BabyAGI, an AI agent project, generated significant public interest and search attention according to Google Trends data, potentially catalyzing broader awareness of AI agents as a category. The obser

here's a deep dive on how middleware lets you customize your agent harness, excellent writeup by @Vtrivedy10 !! deepagents offers a powerful base harness that you can customize for your use case! crea

A Deep Dive into Deep Agents 🚀DeepAgents deploy is a simple, configuration driven way to get an agent harness deployed to the cloud deepagents.toml is the file that configures it. It has four sections