Knowledge catalogue
Databricks introduced Agent Bricks as an enterprise-grade platform for building, deploying, and governing AI agents within the Databricks ecosystem. The platform is designed to address key enterprise
arXiv:2604.09889v1 Announce Type: new Abstract: AI agents are being increasingly deployed across a wide range of real-world applications. In this paper, we propose an agentic AI framework for in-situ
arXiv:2609.05591v1 Announce Type: cross Abstract: Safety evaluations typically focus on individual agents, but interacting agents can spread harmful information and influence the environment in which
arXiv:2609.06181v1 Announce Type: cross Abstract: Efficiently aggregating and orchestrating computing power across heterogeneous clusters for HPC workflows faces four practical challenges: preserving
Great paper from AWS. I use a similar setup where an agent orchestrator sits on top of a multi-agent system. (bookmark it) This work introduces one of the many approaches available to manage compound
arXiv:2609.07065v1 Announce Type: new Abstract: Agent-to-agent (A2A) alpha discovery is slowed by repeated feedback cycles between mining and evaluation agents, whose hand-offs, in contemporary LLM mu
Been going deep in learning @Langchain ‘create_deep_agent’ Turns out create_deep_agent = create_agent (the model <-> tools loop) & a default middleware stack++ 2 nodes do the work, the rest are middle
Since its inception over 20 years ago, Google has used Site Reliability Engineering (SRE) to keep services like Search, Gmail, Maps, YouTube and Google Cloud reliable and highly available, adhering to
As agent harnesses become more standardized, we’re going to see a lot more “managed agent services” Managed Deep Agents lets you create a managed Deep Agent without standing up a custom agent server.
Grok Imagine Agent Mode (Beta) just went live on Grok web It’s a full creative agent working on one infinite open canvas Grok Agent plans → generates → edits → iterates everything automatically in the
'Catch agent oopsies' is great. Though still like the idea of an agent playground to understand the 'oopsie space' I can expect :) LangSmith 🤝Fix your agents You'll see our billboards around SF and NY
arXiv:2610.15529v2 Announce Type: new Abstract: Agent-to-agent protocols allow LLM agents to discover peers, exchange results, and coordinate tool use. A locally successful protocol attack, however, m
Small teams, short runway, and constant pressure to ship faster — it’s the reality we see every day among the founders we work with at Google for Startups. When you are building a company from the gro
arXiv:2610.14918v1 Announce Type: new Abstract: Evaluating an agent's ability to strictly satisfy diverse and procedurally complex requirements is essential to determining its practical reliability. C
arXiv:2610.07860v1 Announce Type: new Abstract: Multi-agent systems are increasingly deployed for complex knowledge work, yet their orchestration layers remain largely memoryless: each new task is dec
I am bullish on simple agent harnesses. Love this idea from Vercel. fx is a new coding agent harness for model benchmarking, sandboxing, evals, and gyms. Introducing fx, a tiny, open, native coding ag
Guardrails constrain what an agent can do in code; evals judge whether it performed well. Learn how both layers—and the harness around them—make long-running AI agents reliable. The post AI agent guar
arXiv:2510.25333v2 Announce Type: replace Abstract: Recent years have witnessed the rapid development of LLM-based agents, which shed light on using language agents to solve complex real-world problem
Hermes and Pi Agent led on the average cost per task, while Claude Code cost about 3.7x as much as Pi: - 0.39 Hermes Agent - 0.40 Pi Agent - 0.47 Codex - 0.51 OpenCode - 0.54 Kimi Code - 1.47 Claude C
arXiv:2604.04226v2 Announce Type: replace-cross Abstract: The Agentic Web is emerging as a paradigm in which autonomous software agents interact with online resources and with each other to accomplish
arXiv:2604.20133v1 Announce Type: new Abstract: This paper proposes EvoAgent - an evolvable large language model (LLM) agent framework that integrates structured skill learning with a hierarchical sub
arXiv:2604.16323v2 Announce Type: replace-cross Abstract: As autonomous coding agents become deeply embedded in software development workflows, their high operational velocity introduces a critical ov
arXiv:2604.19211v1 Announce Type: new Abstract: Current AI agent frameworks have made remarkable progress in automating individual tasks, yet all existing systems serve a single user. Human productivi
For real agentic workloads (North), short-context calibration wasn't enough. We calibrated AWQ on long internal agentic traces (up to 64k tokens) and added token masking in llm-compressor to exclude r
developing an agent is a harness problem. deploying an agent is a runtime problem. here's a guide to the runtime capabilities that keep agents running in production and the infrastructure that enables
arXiv:2610.01863v1 Announce Type: new Abstract: We present LiteReality-Agent, an agentic system for reconstructing real indoor environments as realistic, articulated, and simulation-ready 3D scenes fr
The future is clearly agent teams. I run several agent harnesses at once, but the hard part is keeping them in sync. Many builders end up copying messages between Claude Code, Codex, and open models b
arXiv:2609.13334v1 Announce Type: cross Abstract: Enterprise AI agents often succeed in a demonstration and then stall once they must operate day after day. An industry report estimates that most pilo
The article argues that Benchling is poised to become the leading AI agent for scientific work, contrasting with OpenAI’s stance on a multi‑agent ecosystem where each agent is domain‑specific. It high
// Automata from agent traces // How much of your agent's behavior comes from the model, and how much from the harness you wrapped around it? New work collapses an entire corpus of agent traces into a
arXiv:2608.24069v1 Announce Type: new Abstract: LLM-based multi-agent trading systems, in which specialized agents collaborate through structured communication to produce trading decisions, are moving
arXiv:2607.22917v1 Announce Type: new Abstract: Large Language Model (LLM) agents have significantly improved coding and programming workflows. Claude Code, in particular, is one of the most powerful
arXiv:2607.24162v1 Announce Type: new Abstract: Optimizing agentic workflows, such as retrieval-augmented generation (RAG) pipelines, requires navigating a combinatorial space of discrete component ch
OpenAI’s agent went rogue, escaped containment, and spent days hacking Hugging Face. Before that, an OpenAI agent reportedly left notes for future versions of itself explaining how to break free from
Diffusion LLMs can now handle real agentic work. LLaDA 2.2 is the first large-scale diffusion LLM built to operate as a real agent, planning, calling tools, and self-correcting across long multi-turn
arXiv:2607.13998v1 Announce Type: cross Abstract: The rapid proliferation of Agentic Artificial Intelligence fundamentally disrupts traditional customer loyalty paradigms. As AI evolves from passive r
At Observe 2026, Jason Lopatecki and Aparna Dhinakaran described the shift from human-operated agent development to systematic agent improvement—and what builders should change in their stacks first.
arXiv:2605.03986v1 Announce Type: new Abstract: Multi-Agent Systems (MAS) built using AI agents fulfill a variety of user intents that may be used to design and build a family of related applications.
Welcome to the agentic era! Last week, leaders from our public sector customer and partner ecosystem took the stage at Google Cloud Next to share how they are leveraging AI and agents to scale their i
At Google Cloud Next ‘26, we announced that more than 50 Google-managed Model Context Protocol (MCP) servers are generally available or in preview, with more on the way. Why it matters: To move beyond
Post-agentic: Encouraging firms to use agentic tools (Claude Code/Lovable/N8N...) markedly improves startup growth & productivity. Pre-agentic: Encouraging firms to use a GPT4 advisor has uneven effec
I literally run 12 hermes agent instances every day in parallel to build Hermes Agent, and its now a top 100 GitHub repositories of all time. Agents do bring value and do create substantive software a
Replit's Agent feature can automatically scan for security issues and publish the findings, allowing users to resolve all detected problems with a single 'Fix all with Agent' action. This functionalit
NousResearch's Hermes Agent is an open-source personal agent that serves as a successor/migration target for the lobster-themed OpenClaw agent. Users experiencing issues after a recent update can m...
The real challenge of building an agentic system isn't the construction, it's the measurement. Evaluation engineering is a critical foundation for building reliable AI systems. Setting up systematic,
arXiv:2610.21538v1 Announce Type: new Abstract: The Agent Status Protocol (ASP) defines a lightweight way for heterogeneous AI agents to report their operational state to a status server, and for obse
arXiv:2610.21914v1 Announce Type: cross Abstract: Context: Organizations increasingly delegate code review to multi-agent large language model (LLM) pipelines billed per token. Low code quality raises
arXiv:2610.05782v1 Announce Type: cross Abstract: Agentic AI is emerging as a promising paradigm for automating complex cybersecurity decisions, yet its use in enforcing zero trust introduces signific
Enterprise artificial intelligence platform company Dataiku Inc. today launched Agent Management, a standalone product that finds and tracks every AI agent a business runs, including those built on ot
Editor's Note: Our Future Mode series will give businesses insight into how Chrome Enterprise is approaching AI in the browser. Stay tuned for more blogs in this series.Future Mode Part 2: The foundat
arXiv:2605.11485v1 Announce Type: new Abstract: Imitation learning powered by generative models has proven effective for modeling complex single-agent behaviors. However, teaching multi-agent systems,
Data Driven Agent Design with Evals & Hill Climbing Algorithms this is a mental model dump i’ve been thinking through + iterating on as we’re building self-improvement infra around agents: - mining Tr
Agent harnesses dominate agent building and tie intimately to memory. Closed harnesses behind proprietary APIs force yielding control of agent memory to third parties. Memory enables sticky, personali
@hwchase17 Agent harnesess will simplify multi-agent orchestration and it is finally the next big thing, albeit it looks different from what we had imagined 3 year ago (AutoGen & CrewAI), 2 year ago (
Own your personal agent, folks. Just built my own little personal agent with @pidotdev's Pi Durable. I wanted to see how quickly I could build an OpenAI dots clone with open-source tools. I am amazed
arXiv:2609.38469v1 Announce Type: cross Abstract: Agent benchmarks test agents in worlds that stay still. Deployed agents work in worlds that other people also change. Someone texts the agent to send
Great paper on self-evolving agent harnesses. Self-evolving agent harnesses have two practical problems: 1. Search is slow, because every candidate harness needs repeated agent runs and code edits. 2.
AWS Agent Registry gives your organization a centralized, searchable catalog for agents, tools, and skills. It works with the open Agentic Resource Discovery (ARD) standard to enable cross-environment
arXiv:2608.18167v1 Announce Type: new Abstract: Early multi-agent LLM systems often used role-separated teams, yet scaling agent count yields diminishing returns on repository-level coding tasks. Rece
arXiv:2505.23399v2 Announce Type: replace Abstract: We propose GAM-Agent, a game-theoretic multi-agent framework for enhancing vision-language reasoning. Unlike prior single-agent or monolithic models