Search: “agents”

Hermes Agent tip of the day: You can backup and transfer your agent cleanly and simply. Want to move it to a new VPS that is bigger? Take it to your new Mac Mini? `hermes backup` - > creates a zip ins

Security Agent builds on Replit Agent’s always-on security, which scans for vulnerabilities and audits dependencies as you build, before anything goes live. Read details here: https://blog.replit.com/

Replit's Security Agent feature allows users to initiate security scans directly from their project's security panel by selecting the 'Run Scan with Agent' option. This tool enables developers to anal

Announcing Hermes Agent Community Meetup in Seoul, South Korea 🇰🇷 as the avid user of @NousResearch's hermes agent i want to build the community around the user group happening on may 9 (sat) in seoul

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

Memory makes your agent smarter over time. The agent harness is key to the memory layer. You can't bolt one onto the other after the fact. Every decision the harness makes - what goes in context, what

智谱直接把开源 Agent 拉到新高度了！ GLM-5.1 正式开源： ✅ 开源模型里 SWE-Bench Pro 拿下 #1（58.4），全球第 3 ✅ 真正长时程 Agent：自主运行 8 小时、几千次迭代 + 自审循环 ✅ 从零搭出一个带 50+ App 的完整 Linux 桌面（视频太炸了） ✅ Vector-DB-Bench 性能直接 6 倍提升 开源权重 + API 同步上线，明天就能

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

LangChain 今天连发两记，直接把 agent reliability 往前推了一步：一套统一评估栈，一个不用完整沙箱的代码执行方案。 先说评估。长运行、有状态的 agent 怎么测？Harbor + LangSmith 的组合给出一个 runner，能挂载 sandbox、接入 observability，终于不是靠单元测试糊弄了。 再看代码执行。Deep Agents 需要跑不受信代码，

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

Memory is what turns an ok general agent into YOUR excelling agent- but requires constant reflection and updating Engine does this 24/7 for you 🧠LangSmith Engine as Sleep Time Compute Memory for agent

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

Cognition AI's Chief Product Officer Walden Yan previously advised against building multi-agent systems, but the company has since changed its position based on evolving market conditions and technica

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.

I'm frequently using Claude Code and i love @openclaw. But i would say Hermes Agent from @NousResearch is the best open-source agent I’ve ever used, especially given that it comes from an independent

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

Agent memory systems often follow a three-step iterative process: executing the agent to generate traces, analyzing those traces through some evaluation mechanism, and then updating the agent based on

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

The `create_agent` function in LangChain provides a minimal, lightweight agent framework designed for easy customization through middleware, enabling developers to build task-specific agent harnesses

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

Excited to finally get our agent live for the world. A lot of what we’ve learned over time has been condensed and built into the agent so it can do the best work for you. Meet Runway Agent. Your new A

// Harnessing Agentic Evolution // Pay attention to this one if you run iterative agentic search loops. (bookmark it) AEvo splits the self-improvement loop into two jobs: > One proposes the next candi

Langsmith Engine appears to be a seriously high value release from the @LangChain team A deep agent that’s monitoring Langsmith agent traces and not only surfaces issues but: - proposes a PR to resolv

We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data problem. Agent traces can contai

Agent observability enables monitoring of agent behavior, but to effectively improve agents through feedback loops, developers must actively collect observability data and generate synthetic examples

First module in my Hermes Agent Masterclass is live! I wanted to create a super in-depth series about Hermes Agent, exploring every aspect of the agent. First video breaks down installation, setup, an

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

Don't try to build a self-improving AI agent without evals. You are just wasting time and compute. An agent can't improve from traces it can't evaluate. This is why it's exciting to see @FutureAGI_ go

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