Knowledge catalogue
arXiv:2605.25815v1 Announce Type: new Abstract: Agent-to-Agent (A2A) networks enable autonomous AI agents to collaborate by sharing reusable problem-solving instructions. However, how these decentrali
arXiv:2605.25233v1 Announce Type: new Abstract: AI agents are increasingly used to solve complex, multi-step tasks, but existing multi-agent frameworks remain brittle as workflows grow in scale and de
Many of the world’s fastest-growing AI startups are choosing to build their future — and the world’s — on Google Cloud because of our complete and open AI stack. We embed AI into every layer of our ar
arXiv:2604.21154v1 Announce Type: new Abstract: At-home physiotherapy compliance remains critically low due to a lack of personalized supervision and dynamic feedback. Existing digital health solution
To act at the speed of business, AI agents must operate in fast and trusted reasoning loops. They need to “think” by reasoning across both your historical context and your live operational reality. On
arXiv:2604.17406v2 Announce Type: replace Abstract: The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science. While the scientific method is
AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem
// Artifacts as Memory Beyond the Agent Boundary // An agent doesn't always need a bigger memory buffer. Sometimes the environment itself remembers on the agent's behalf. New research formalizes this
arXiv:2604.09744v1 Announce Type: cross Abstract: The AI agent ecosystem has converged on two protocols: the Model Context Protocol (MCP) for tool invocation and Agent-to-Agent (A2A) for single-princi
The challenge with agent harnesses is not only building them but distribution. If we want agent products to scale like saas, the interfaces and ecosystem still need a fundamental breakthrough. im exci
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
Someone used Pi to build an Excel agent… then published all the traces from it to HuggingFace🤯 Just point your agent at this changelog and tell it to publish its traces to HuggingFace! http://huggingf
As enterprises shift their AI usage from experimental chatbots to autonomous agents, teams are hitting a critical bottleneck: accessing and reasoning over data scattered across multiple clouds, SaaS p
arXiv:2610.14115v1 Announce Type: new Abstract: Large language models have significantly lowered the barrier to writing code. Naturally, this has also led to the development of data science agents tha
Brilliant paper on agentic continual learning from Meta and MIT. (bookmark it) Agent memory harnesses usually only write forward. A lesson goes into the bank and is never checked against whether it he
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
Must-read paper on the effectiveness of multi-agent systems and persistent memory. We have recently seen many viral examples of multi-agent systems scaled via persistent memory. This work takes a clos
Coding-agent platforms, sandbox products, and code-execution services all need the same thing: isolated machines that start up fast, retain their state between bursts of work, and don’t consume comput
3 helpful agent use cases that function like an EA and only require calendar access: 1. Email filter: junk signups go to your agent's email address. It reads everything, and you only get recaps of the
arXiv:2610.00583v1 Announce Type: new Abstract: People are increasingly delegating tasks to AI agents, and those agents are increasingly encountering other people's agents over shared resources such a
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
Graph engineering is the design work: breaking a task into nodes, connecting them with edges, and deciding where code, models, or people control the next step. The Agent Development Kit (ADK)'s Workfl
For decades, the observability industry has answered one basic question: Is it running? Agentic artificial intelligence breaks that model. An agent can return a clean response, meet its latency target
arXiv:2609.26927v1 Announce Type: new Abstract: The objective of this article is to provide design principles and a software architecture for enabling interaction between humans and multiple agents in
Sarah Perez / TechCrunch: Google is testing a new version of its AI agent CC, pivoting the tool from an individual productivity assistant into a collaborative household management agent — Google is te
Multi-agent systems fail in ways traditional monitoring misses. This post presents a dual-layer approach to monitoring production agents: Amazon Bedrock AgentCore Evaluations for continuous quality sc
arXiv:2609.09565v1 Announce Type: new Abstract: Agentic graph learning (AGL) has recently achieved promising results on graph reasoning tasks, where an agent powered by a large language model (LLM) se
arXiv:2609.00267v1 Announce Type: cross Abstract: Autonomous LLM agents increasingly act on a user's behalf: they hold credentials, call tools and services, and spawn sub-agents that act further on th
New research from Meta. Agent harnesses are still mostly authored by hand. This makes it hard to tune robust agent harnesses for long-horizon tasks. In this new work, agents learn harness policies off
I think of it like this: If you are building a simple agent with custom tools in your app -> langchain create agent If you are simply doing some LLM analysis or synthetic data creation -> langchain in
Businesses want to quickly and safely deploy AI agents to drive revenue, mitigate risk, and optimize capital, all without disrupting mission-critical ERP systems. And to power AI agents, you need more
arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural und
arXiv:2602.10429v2 Announce Type: replace-cross Abstract: AIvilization v0 is a publicly deployed large-scale artificial society that couples a resource-constrained sandbox with a unified LLM-agent arc
@huggingface @polats Plus, a shoutout to Hanhee Lee, Javier Huang, and Joe Lee for winning Best Agent with their security camera agent Eyas, built for Lee's family's convenience store. Real problems,
If you've built a chatbot, you know this conversation: User: 'Book a table for two tomorrow at 7pm.' Agent: 'Okay, for what day?' User: 'Tomorrow.' Agent: 'What time?' A date picker would have ended t
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
arXiv:2510.16853v3 Announce Type: replace-cross Abstract: Autonomous AI agents capable of complex planning and action mark a shift beyond today's generative tools. As these systems enter political and
arXiv:2512.24827v3 Announce Type: replace Abstract: Temporally extended actions improve the ability to explore and plan in single-agent settings. In multi-agent settings, the exponential growth of the
The Agent Readiness score can help site owners understand how well their websites support AI agents. Here we explore new standards, share Radar data, and detail how we made Cloudflare’s docs the most
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
arXiv:2606.19911v2 Announce Type: replace Abstract: Decentralized deployment of LLM agents with diverse capabilities motivates infrastructure for knowledge sharing across heterogeneous agent populatio
arXiv:2610.06274v1 Announce Type: new Abstract: Many agent runtimes give the agent a tool for editing its own configuration. Some of that configuration grants abilities, such as enabling a tool. Other
Ivan Mehta / TechCrunch: Q&A with Brian Chesky on Airbnb's plans for agent-to-agent interactions, why chatbots fail at travel e-commerce, the need for an AI-native OS, and more — Airbnb rolled out its
arXiv:2609.39297v1 Announce Type: new Abstract: Autonomous agents powered by large language models (LLMs) are rapidly evolving into an open agentic ecosystem. To support trustworthy collaboration, ind
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
For organizations deploying AI agents at scale, there’s often a critical divide between structured and unstructured data. While large language models (LLMs) excel at parsing text documents, emails, an
As a market leader in enterprise agentic automation and business orchestration, UiPath is helping to pioneer an industry shift toward agentic AI. With it, the company is deploying autonomous agents to
arXiv:2607.26935v1 Announce Type: new Abstract: Bot detectors deployed at scale treat traffic as binary: human or bot. This assumption breaks when AI agents browse the web through browser automation,
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
Editor’s note: Today we hear from IDC on the results of its 2026 AI in Networking Special Report Survey exploring the enterprises' concerns about networking infrastructure to support the rise of agent
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
arXiv:2604.20070v1 Announce Type: cross Abstract: Advances in AI agent capabilities have outpaced users' ability to meaningfully oversee their execution. AI agents can perform sophisticated, multi-ste
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
Modal's blog post covers how to build and deploy AI agent applications by combining Modal's serverless cloud infrastructure with OpenAI's Agent SDK, enabling scalable execution of agentic workflows. T
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