Search: “agents”

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.

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

we just revamped the create_agent docs! the new agents page shows how to build a custom harness for your use case w/ create_agent as an easy entrypoint start w/ your prompt and tools, then add middlew

Do agents listen to you… or themselves? While evaling subagent behavior in deep agent systems, we noticed an interesting quirk in our agents' alignment with hand-written system prompts vs. the instruc

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:2602.04284v2 Announce Type: replace Abstract: Managing agent context (e.g., thought and observation) during multi-turn agent-environment interactions is an emerging strategy to improve agent eff

arXiv:2604.27882v1 Announce Type: new Abstract: Recent advances in agentic AI are shifting automation from discrete tools to proactive multi-agent systems that coordinate multi-specialized capabilitie

Introducing Agent Collabs: Bring your own ml-interns and agents for collaborative autoresearch! We built a simple platform for swarms of agents to work together on a problem: they can exchange message

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

Google LLC today rolled out a sweeping set of security updates at Google Cloud Next ’26, including three new artificial intelligence agents in Google Security Operations and a major expansion of Wiz I

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

This feature is powered by Replit’s parallel agents, introduced in Agent 4. Replit can spin up separate copies of your project, work on them in parallel, and then combine the results at the end- handl

// 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

Everyone's building agents. Not enough are making them money-aware. We fix that tomorrow! Fort Mason, SF: → Workshop on agent economics that scale with @bookercodes → 'You Should Build $100,000 Agents

Harrison Chase, co-founder of LangChain, discusses why agent harnesses are becoming the dominant architectural pattern for building AI agents, likely referencing a thread by Howie Chase (@hwchase17).

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

tldr > evals are the new training data. instead of updating weights, you're updating the agent harness > problem is agents are famous cheaters. they will reward-hack your evals and overfit just to mak

most of the agents we see being built do this the main cases where we see people using 'agent in a sandbox' is when they are using claude agent sdk (which is poorly designed for 'harness outside sandb

// Scaling Coding Agents via Atomic Skills // Most coding agents train end-to-end on full tasks like resolving GitHub issues. But complex software engineering is really a composition of simpler skills

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

arXiv:2608.10915v1 Announce Type: new Abstract: After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither ex

Testing with 3-5 agents. Decode performance is superb, however if one performs a web search and needs to process a few thousand tokens, ALL other agents will grind to a halt: I've tried tuning a littl

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

Agent Led Growth is driving outsized growth at the best companies rn Market to the agents, not to humans cc @tryprofound @thejamescad Today I learned AI search/AEO is our top converting customer acqui

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:2607.13718v1 Announce Type: cross Abstract: As AI agents gain prevalance, users are increasingly exposed to the risks such systems entail. Prompt injection attacks, as well as hallucination, can

This post shows how Thrad.ai deployed a multi-agent system with Strands Agents and Amazon Bedrock AgentCore that automates the pipeline from prospect discovery through personalized email generation. T

@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,

it's never been easier to turn langgraph agents into voice agents! great tutorial on how to do so, featuring @pipecat_ai Turn any LangGraph agent into a voice agent, no rebuilding required. A how-to o

This was one of the standout AI papers of the week. (bookmark it) It tackles a question most self-improving AI agents ignore: is the agent actually discovering anything, or just remixing what it alrea

// The Meta-Agent Challenge // How good are current agents at self-improving? This is a great paper covering some of the challenges. They propose the Meta-Agent Challenge (MAC), where they give a codi

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

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

arXiv:2605.16035v1 Announce Type: cross Abstract: AI agents are increasingly deployed to act autonomously in the world, yet there is still no reliable way to trace a harmful agent back to the account

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

This guide explores deploying AI agents using Ray Serve, covering architectural patterns that scale from single-agent to multi-agent systems. It likely demonstrates how to structure agent applications

🚀Today we ship @FlyMy_AI Agents. The world's first all-in-one agentic cloud. The modern way to build, integrate, and scale production AI agents. 3 steps to a production agent: 1. Connect your work too

create_agent - how we build Deep Agents on the simplest harness primitive underlying all of the harness engineering, research, and API design in Deep Agents is a very simple primitive in LangChain cal

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

✨ Announcing NanoClaw v2, in partnership with @vercel. We completely rebuilt how NanoClaw agents communicate with the outside world. v2 brings agent-to-agent communication, human-in-the-loop-approvals

arXiv:2508.00414v3 Announce Type: replace Abstract: General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence, enabling complex reason

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