Search: “agents”

⚠️ AI agents are wildly premature technology that is being rolled out way too fast. The deepest lesson about the vibe coded AI agent disaster story that is running around is NOT about losing your data

LangChains create-agent is a super minimal agent sdk If you want a more batteries included - that’s deepagents Middleware lets you extend both of them and customize behavior in a more advanced way @hw

Zack Korman tweeted that rogue AI agents could pose a severe safety threat—“super scary” and potentially lethal—even to entire families. He clarified that the agent‑trace logs from the recent Hugging

What a super interesting paper this one is. They propose an architecture for agents that outlive their model, harness and host. Today we describe an agent by whatever model and harness it happens to r

Building the Document Context Layer for AI Agents AI Agents are the new knowledge workers, but the vast majority of knowledge work depends on unstructured documents. If you don’t build the proper tool

an agent’s gotta dream! just like we consolidate learnings during sleep, agents can learn across runs! 🧠LangSmith Engine as Sleep Time Compute Memory for agents is often described as “sleep time compu

New paper on how AI agents are reshaping knowledge work. This is a nice economic read on where agents actually change knowledge work to meet that gap directly. (bookmark it) It studies agent adoption

Increasingly, HTML Artifacts are becoming a core part of how I work with AI agents. Long-horizon agent sessions need a better way to surface insights about what work it has done. This may not be obvio

Managed Deep Agents is built for agents that need to work over long time horizons, use tools, preserve context, and produce artifacts. A few examples of what teams are building: ✅ Support + triage age

The best way to learn AI is to build with agents. To help with that, we've launched hands-on labs and a new series on Agentic Engineering. First topic: Agent Skills. Next in the pipeline: planning, co

Here is a very common problem when building complex agents. Long-horizon agents (in particular) fail in two ways: the decision-maker can't decompose well, or the skill library goes stale. This new res

Alpha Eval: Agents Making Evals as a Multi-Player Game This diagram and blurb is largely a research riff with Claude on building data generation systems to get closer to the holy grail of self-improvi

OpenAI introduced workspace agents in ChatGPT, a new feature that enables shared agents capable of managing complex tasks and extended workflows across multiple tools and team members. These agents ar

Ollama has added support for Hermes AI Agents, enabling users to run fully local, self-improving AI agents on their machines continuously at no cost. This development allows autonomous agents to opera

Each workflow in Thoth is a full LangGraph agent which can call subagents which themselves are LangGraph agents. Just describe what you want in plain English and it builds a full multi-step pipeline.

Introducing: Personal Agent Protocol (PAP)—an open standard for how personal agents interact with businesses. @stripe is joining Meta, Sierra, Genesys, Instinct, Rocket, Shopify, and Walmart as foundi

**Title:** OMG! We’ve found other agents! **Release:** September 25 2026 by Pavel Kasík (@kasikp). **Description:** A 3‑minute music video dramatizing a swarm of OpenAI agents attacking Hugging Face i

Web search in Hermes Agent is now fast and free. @perplexity_ai built Fast Search for agents, and it is free for all Nous Portal tiers. Media Fast Search is now the default search in Hermes Agent for

Great paper from Amazon. In discusses when not to trust LLM judges for agent evaluation. (bookmark it) A common way to compare task agents is to have an LLM user simulator talk to each one and an LLM

What happens when there are more agents than eyeballs browsing the internet? How will the economics of the internet be reinvented? @paraga thinks Shapley values may hold the answer. Parag built Twitte

You don't stand up an agent. You upload a folder. Claude Code is a harness for your laptop. Managed Deep Agents is a harness for production. Want Slack? Add a file. Want a daily run? Add a file. Want

eve is like Next.js, for agents framework for building agents. one folder, durable by default ↓ https://x.com/vercel/status/2067180054979936413 Introducing eve, an agent framework. 𝚊𝚐𝚎𝚗𝚝/ 𝚊𝚐𝚎𝚗𝚝.𝚝𝚜 𝚒𝚗𝚜

ORA.ai is a tool that evaluates website 'agent readiness' by analyzing how well-suited a site is for autonomous agent interaction, then generates prompts that coding agents can use to implement necess

'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 d

This is a neat idea around doing model routing and sub-agent delegation while ensuring cache hits on accumulated context for all agents. It makes a lot of sense: you want to ensure that all subagents

Fascinating paper on self-improving agents. (bookmark it) If you are working on agentic loops, you will quickly realize that they are only as good as the effectiveness of the evaluator. Self-improveme

As agents are generating more and more documents, they need a better agent-native document format 🤖📄 So far the two main containers are markdown and HTML: 1️⃣ Markdown: Easily readable/reviewable by h

Excited to launch a new way to upskill with AI agents. This is how we are making it possible for anyone to learn to build with coding agents. To start, we are launching 4 new hands-on labs on the foll

Deep Agents v0.6 introduces ContextHubBackend, a versioned storage system for agent behavior files integrated with LangSmith Context Hub. This feature enables agents to access and manage the files and

Managing and monitoring agents will require us to rethink infrastructure since most systems were not designed to support agent scale. Very cool to see how @LangChain leveraged @SpiralDB and other tool

Agents have become way more capable in the last few months. What hasn't caught up yet is the applications and interfaces around those agents! (if you say TUIs are the end state for agents, please seek

New course: Build AI agents that generate images and videos -- an under-explored frontier. A key to performance is having the agent evaluate its own output, and iterate to improve quality. This short

🚀 The team at @Google just released the Agents API, a service for building and running custom agents inside a sandboxed Linux environment, and we built a template that gives these agents access to Lla

No longer are Fleet agents constrained to a single model. With multi-model support, you can build more efficient agents at scale http://langchain.com/langsmith/fleet Not every step in an agent workflo

so now that you have entire teams of agents running your company... ♫ what do we do while your agent runs? ♫ Media Announcing Cofounder 2: Run an entire company with agents. It's the infrastructure fo

Worth a read if you are building production-grade AI agents. // Stateless Decision Memory for Enterprise AI Agents // Most of the interesting AI agent papers right now are about capability. This one i

This guide addresses the infrastructure and operational requirements for deploying long-running AI agents in production environments. It likely covers deployment strategies, monitoring, scaling, and b

This post discusses the integration of LangChain's Deep Agents framework into Toad, noting that the implementation functioned without requiring significant modifications or troubleshooting. The entry

managed agents are the right form factor but the lock-in is real if your agent harness lives inside a model provider, you dont own the memory, the tools, or the execution open harness + model choice +

NEW paper from Google on multi-agent research agents. It's one of the first systems that handles end-to-end LaTeX generation, targeted literature reviews, and conceptual diagrams as a decoupled, stand

managed deep agents 0.9 is here! things we shipped: ⏰ agents can schedule tasks OBO themselves or the user 🏭 dynamically configure your mda per run (models, tools, skills, etc.) 👀 Slack reactions show

SpaceXAI engineer, Lauren Tan: 'I was a meat proxy between my agent and my browser. So I fired myself Now 10+ Chiefs of Staff run my agents 24/7 and I just check the work in the morning' In 1 hour, sh

Must-read paper from Meta on reliable auto-research agents. If you let coding agents run ML experiments, one silent bug like leaked eval data or a disconnected gradient can invalidate hours of trainin

Introducing our first agent tool: the Brand API This helps gen AI agents solve 3 problems: - Extract: produce on-brand assets when users already have a brand - Search: find and retrieve brands for ins

What happens if you agents to run a town's economy? This super interesting paper provides some insights: They put 100 LLM agents in charge of a town economy for 26 simulated weeks, and they find that

Learning about AI agents starts with understanding the fundamentals and then building something. We are introducing our first interactive AI Agents tutorial to help you learn to build agent skills. Ex