Search: “agents”

This WikiSkill paper from Google is a must-read. At a high level, it shows the effectiveness of persistent agents, knowledge bases, and skills. @karpathy popularized LLM Wikis. But this paper provides

Artificial intelligence agents are moving from experimentation to production, and with this shift, the stakes are rising. A coding agent at PocketOS recently deleted an entire production database. An

Made a stand-alone Hermes Agent plugin for BackSearch - a wayback machine-like SaaS for agents - adds two tools, and requires their API key. Let me know if you like it https://github.com/NousResearch/

arXiv:2411.08881v3 Announce Type: replace-cross Abstract: AI-based systems, including Large Language Models (LLMs), impact millions by supporting diverse tasks but face issues like misinformation, bia

Grok Bot is the best AI agent right now and a full walkthrough just dropped covering setup, use cases and plugins. An army of agents working around the clock 24/7. Set it up correctly and the leverage

arXiv:2608.14613v1 Announce Type: new Abstract: Modern LLM-agent frameworks increasingly interoperate through standards such as Anthropic's Model Context Protocol (MCP) for agent-to-tool access and Go

arXiv:2608.12977v1 Announce Type: cross Abstract: The expanding operational capabilities of large language model (LLM) agents introduce sophisticated security threats. Runtime defenses have emerged as

A background comment about pizza exposed a failure that Uber’s offline evaluations had missed. The incident helped reveal what production AI agent evaluation actually requires: automatic tracing, livi

arXiv:2602.17902v2 Announce Type: replace Abstract: Large language models (LLMs) can plan scientific workflows and generate code, but these capabilities do not specify how scientific state is validate

arXiv:2608.06949v1 Announce Type: new Abstract: Prior benchmarking work has shown that a single large language model (LLM), forced to make life-or-death resource-allocation decisions, exhibits measura

arXiv:2608.06020v1 Announce Type: new Abstract: Economic World Models (EWMs) are generative economic models that simulate how economies evolve from within by modeling heterogeneous agents, their belie

Enterprise AI agents lose effectiveness when they must access data outside of protected, governed systems. The article argues that truly reliable agents need to be *data‑native*—run directly inside th

Your Claude Code can now make phone calls. Introducing phone carrier for agents. Your agent can now book restaurants, chase leads, and talk to anything with a phone number. Just one prompt. 15 seconds

Ramp for Agents. Replit Agent can now incorporate your company, apply for Ramp, and get your business ready to spend, pay bills, and manage money. Every company used to start with paperwork. The next

4/ programatic subagents in deepagents Deep Agents is our open source, model agnostic agent harness: https://github.com/langchain-ai/deepagents We added the ability to programatically call subagents.

arXiv:2512.04988v2 Announce Type: replace-cross Abstract: Emerging agentic marketplaces provide the economic infrastructure for matching and coordinating the large amounts of AI agents used in agentic

Agentic retrieval is changing the way retrieval-augmented applications are built, especially in domains like legal and fintech, where agents need to autonomously navigate large, evolving knowledge bas

get started with deep agents code, our open source coding agent with first class open model support You can start building with GLM 5.2 in minutes: 1️⃣ Download dcode 2️⃣ Select your model (GLM 5.2) 3

Great paper on managing agent skills. Skill libraries keep growing, and picking the right skills has become a bottleneck for coding agents. The defaults are to expose the agent to the whole skill coll

arXiv:2606.31179v1 Announce Type: new Abstract: As AI agents become increasingly capable of complex, long-horizon reasoning, rigorous and holistic evaluation is essential for measuring progress toward

you can now build RLMs with Deep Agents! the more context agents accumulate, the worse they perform, a phenomenon called context rot. RLMs, proposed by @a1zhang from MIT, help: instead of working mode

.@harborframework can now integrate directly with Deep Agents, LangSmith Sandboxes, and LangSmith Observability. You need to run agents in a real, reproducible, isolated environment, many times in par

we launched code interpreters for deep agents last month. Basic idea is to let agents plan, delegate, and organize context using code instead of chained tool calls Code interpreters don't need a sandb

Deep Agents now supports dynamic subagents. Instead of invoking subagents with tool calls, the main agent writes orchestration code to coordinate work at scale. This enables workflows like processing

Building Agent Skills is great, but testing them clearly and across agents is difficult. The Pinecone DevRel team has released Cultivar, a CLI tool and agent skill designed to solve this problem. With

memory is the key to continual learning for agents!! memory helps your agent improve over time, check out this guide on how to automate memory development! i've been talking a lot about loops recently

Deep Agents v0.6 feature spotlight: a code interpreter. Agents can now call tools from inside a runtime, keep intermediate results out of model context, and only pass the relevant output back. Fewer r

If you are building agents, Max Agency with @hwchase17 is THE best behind the scenes of how the top agents are built at companies like @SierraPlatform @RampLabs @benchling @ListenLabs @_hex_tech @coge

people want to build agents, and they want it to be easy even more important, it should be easy for your agents to improve over time that's what the 4th loop ('hill climbing') enables. automating the

arXiv:2606.10917v1 Announce Type: new Abstract: Although Large Language Model (LLM) agents have demonstrated strong performance on complex tasks, their learning is often limited by inefficient interac

Nebius AI announced the Agents Blueprint, a framework integrating multiple tools including LangChain Deep Agents, Tavily AI, Pinecone for vector storage, and Guardrails for building AI agents. This bl

Agent Swarm & Instant Document Delivery Kimi will automatically coordinate 300 sub-agents to break down and execute your tasks. Delivers production-ready output in PPTX, Word, PDF, and Excel, straight

arXiv:2606.05304v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models are typically organized around roles, pipelines, and turn schedules, while the content that age

Sandboxes are already helping teams move from agents that answer questions to agents that can do work safely. At @mondaydotcom, that means giving Sidekick a secure environment to write and run code fo

This is the enterprise-agent security frame I like: treat agents like untrusted developers. They need the ability to call an API, not possession of the credential. Control plane outside runtime. Fail

arXiv:2606.03698v1 Announce Type: new Abstract: A central goal of large language model (LLM) research is to build agentic systems that can plan, act, and adapt through sustained interaction with dynam

This macroeconomic research agent powered by Deep Agents, LangSmith, and the @youdotcom Finance Research API: ✅ Analyzes GDP data ✅ Detects anomalies ✅ Investigates structural & cyclical drivers at th

arXiv:2602.02751v2 Announce Type: replace-cross Abstract: Small language models are increasingly viewed as a promising, cost-effective approach to agentic AI, with proponents claiming they are suffici

Start creating agents using everyday language with LangSmith Fleet. Learn how to build no-code agents for real work. Take our free LangChain Academy course today: https://academy.langchain.com/courses

Agent Lake = Agents + high-scale data processing Watch our full conversation with Geng Sng, Co-Founder & CTO of @cogent_security ⏯️ YouTube: https://www.youtube.com/watch?v=D6XWu54oG4g&feature=youtu.b

Fleet agents can now securely write and run code. With computer use in LangSmith Fleet, agents get isolated execution environments. Analyze data, transform files, generate & write code, and run shell

arXiv:2605.24823v1 Announce Type: new Abstract: Manufacturing has passed through four widely recognized paradigms - mechanization, electrification, programmable automation, and Smart Manufacturing - e

optimise for fun when it comes to building for and with agents setting up a hermes agent is fun because it feels like you’re hatching and raising an incredibly smart digital pet that can do and learn

We’re giving away $10,000,000 to founders building agent-first businesses. Autonomous, proactive agents will run tomorrow's companies. We're backing 500 founders building them. The Founding 500. http:

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Coding agent, end to end. Frontend prototypes, multi-file refactor

arXiv:2605.19149v1 Announce Type: new Abstract: Agents operating with computer and Web use inevitably encounter errors: inaccessible webpages, missing files, local and remote misconfigurations, etc. T