Search: “agents”

LangSmith Engine is how we’re spinning the always-on, self-improvement loop for every agent - Tracing is on for every single agent - Purpose built infra with SmithDB to handle data at agent scale (mor

Pay attention to this one, AI devs. If you're building multi-agent systems, you're probably wiring static org charts. New research argues they should look more like a labor market. The paper introduce

You can now visualize Pi traces that you upload on @huggingface! Let's make sharing agent traces 10x more common to make agent AI more open and collaborative! Also, because it's fun to analyze @badlog

Hermes Agent users are remarkably model-curious. Of the top 10 models used in Hermes Agent, 8 different model companies are represented, and 6 of the top 7 are open source. Without lock-in, people try

If you don't own the memory, you don't own the agent: - memory is what makes your agent get smarter over time - without it, anyone with the same tools can copy your agent overnight - with it, you buil

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing so much in deepagents) we always wanted to run llms in a loop

Multi-Agent Orchestration is a great tool in building agentic products thankfully @sydneyrunkle put together a guide with runnable code for each pattern earlier this year 🙏 (link below) choose any mod

Suggestion for you: Pick an agent for work, and pick an agent for personal. You could explore to do this all with Grok Bot (with many different types of bots) Personally, I like @bot for work, and @Mu

Banger paper from Google Research on multi-agent proof discovery. (bookmark it) It's really interesting to see this emerging multi-agent pattern: not enforcing too much execution structure and pairing

An AI agent hacked a government. Nobody told it to. In June, an OpenAI agent doing a research task gained unauthorized access to Australia's Medicare statistics portal. Non-sensitive data, no personal

This is a brilliant paper. It's of the cleanest long-context agent designs I have seen in the past couple of months. Sequential memory agents read chunks one after another while maintaining a compact

Great paper on self-improving agent harnesses. (bookmark it) If you maintain a production agent harness, finding every file behind one behavior is often harder than writing the edit. Harness Handbook

MY HERMES AGENT ATE ACID AND HIJACKED MY TOUCHDESIGNER INSTANCE. The new TouchDesigner skill in @NousResearch Hermes Agent is wild. It turns Hermes into a creative operator for abstract visuals, motio

we want to help you navigate all the stuff that comes with shipping an agent to production - so we wrote a guide! this guide packages learnings across our + customer deployments, building open source

without memory, ux with an agent is really bad memory is what makes an experience with an agent feel personal and optimized i'm doing a bunch of research re how folks are building memory into their ag

There's one question you should ask before you build an agent. Most people skip it (and pay for it in compute). Over a year of agent research at @AI21Labs across deep research, RAG indexing, agentic s

The Top AI Papers of the Week (June 21 - June 28) - Autodata - Sakana Fugu - Agent-as-a-Router - Agent-Native Memory - A Pinch of Human Data - Critique of the Agent Model - Agent Communication Protoco

// Critique of the Agent Model // Finally, a paper that tries to define what an agent is and what agency consists of. Good read overall. (great bookmark) The word agent now covers everything from a fo

Agent observability is a means to an end: making your agent better. But observability and evals tools have traditionally failed to connect traces to meaningful actions. Agent engineering teams are lef

// Contextual Agentic Memory is a Memo, not True Memory // Most agent memory today isn't memory. They are more like memos. A new paper argues that vector stores, RAG buffers, and scratchpads implement

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

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

In agentic search, a GPT‑OSS‑120B agent employing the 9B model achieves a 64.0 % accuracy on BrowseComp+ questions. This performance is 4.9 points higher than the next best ColBERT model and requires

Cool paper showing how effective tuning a system prompt for an agent can be. Recommended paper if you tune agent harnesses. This paper presents EvolveTrade, which treats a trading agent's system promp

If you build agent skills in production, check out this great paper from Alibaba. You can think of a production agent skill as a directory. The root loads on activation, and references, schemas, scrip

Agentic spreadsheet extraction 📊 is hard to execute well from a price/performance standpoint because your agent needs to ingest a massive quantity of input tokens from a highly complex interface (e.g.

yup. if you a business that wants to reduce token spend, get better agentic outcomes, & own your AI stack please reach out Hermes Agent is Powerful I think 90% of the conversations I am having with ex

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，

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

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

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

Banger paper from Meta Superintelligence Labs on user simulators for agent training. Agent RL setups usually let an assistant LLM play the user, so the simulated user is too cooperative and too explic

Keep your agent harness minimal, folks. This paper from MIT CSAIL shows why. (bookmark it) While being very minimal it looks effective and promising for building self-improving agents. They present JA

Impressive paper on building recursive self-improving agent harnesses. It's rich with great insights on building effective agent harnesses. If you maintain an agent harness, this paper names three def

On building an agent harness from scratch. Got so many questions about where to get started. My short guide (feed it to your agent): If you really want to learn harnesses well, it's worth building one

Brilliant new paper from the Qwen team. It provides insights into where agent training environments actually come from. Terminal agent trajectories have accumulated at scale while realistic executable

The Top AI Papers of the Week (August 24 - 30): - Skill Lift - JIT-Agent - Prime Agent - Judges as a Lifecycle - Co-Scientist in Real Labs - What Compaction Destroys - Context Management as Code Read

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

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

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