agents

arXiv:2607.02345v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents increasingly automate software engineering tasks through reusable skills, natural-language instruction documen

So i built LangGraph Sync. it’s an interactive web tool that visualizes langgraph workflows & lets you edit & bidirectionally synchronize the graph & code in real time. you edit the visual graph, your

arXiv:2607.01507v1 Announce Type: new Abstract: Empirical research rarely admits a unique analysis. Different analytical choices can lead to different conclusions from the same data, yet these hidden

arXiv:2607.01415v1 Announce Type: new Abstract: Coding-agent reinforcement learning treats execution infrastructure as a background implementation detail, despite relying on large numbers of interacti

arXiv:2607.01992v1 Announce Type: new Abstract: Large-scale battery energy storage systems (BESSs) require O&M decisions that combine alarms, cell-level measurements, device topology, diagnostic table

Andrew Qu from Vercel discusses how AI agents represent a fundamentally different category of software compared to traditional applications, exploring their unique characteristics and implications for

When brainstorming new AI agent uses, I always remind myself what used to be expensive and is now nearly zero… 1) cost of reading everything fell → you can now watch 100% instead of a sample (every ex

This post discusses using WorkPods agent memory systems organized as wikis, likely exploring how LLM agents can maintain and access persistent knowledge repositories in wiki format for improved contex

You are going to end up running hallucinated code ~60% Fable cost cut by transparently turning the code into an image and having the model OCR it. WILD idea. also hilarious. https://github.com/teamcho

1/ OpenWiki First, we wrote about why 'wikis' are interesting as a form of memory: https://www.langchain.com/blog/wiki-memory Cites examples from @FactoryAI, @cognition, @karpathy Then @BraceSproul op

As organizations race to operationalize generative and agentic artificial intelligence, the conversation is shifting from pilots and proofs of concept to real-world AI deployments that deliver measura

3/ Harbor integration Harbor is a framework for running long running, stateful agent evals We integrate with it in multiple different ways. We wrote a blog on those integrations: https://www.langchain

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:2607.00155v1 Announce Type: new Abstract: We study runtime human oversight of an AI agent when private information runs in both directions: the human privately knows her reward function, while t

🎧A look at how we built LangSmith Engine with @hwchase17 + @bentannyhill Special episode with @bentannyhill on the Max Agency podcast. A month ago, his team shipped LangSmith Engine, our agent that hu

arXiv:2607.00502v1 Announce Type: new Abstract: While long-horizon mobile GUI agents typically rely on thought-action-observation loops, they struggle to separate persistent task states from transient

arXiv:2607.00056v1 Announce Type: cross Abstract: This paper studies energy efficient tracking of power-limited mobile users with the assistance of a Reconfigurable Intelligent Surface (RIS). Since lo

arXiv:2607.01061v1 Announce Type: new Abstract: Computer-assisted synthesis planning breaks target molecules into accessible precursors using large libraries of reaction rules that assign each transfo

arXiv:2607.00454v1 Announce Type: new Abstract: Agricultural advisory systems face a fundamental tension: static agronomic guidelines offer consistent, evidence-based recommendations, yet remain blind

arXiv:2607.00523v1 Announce Type: cross Abstract: Artificial intelligence (AI) is becoming ubiquitous, and across domains, increasingly autonomous systems are carrying out tasks which raise significan

as expected by whom? 🤔 META: ZUCKERBERG SAYS AI PROGRESS HAS BEEN SLOWER THAN EXPECTED • ZUCKERBERG SAID AI AGENT DEVELOPMENT HAS NOT ACCELERATED AS EXPECTED OVER THE PAST FOUR MONTHS • SAID META'S 20

Katie Paul / Reuters: At a town hall, Mark Zuckerberg said Meta's AI agent development has not accelerated as expected and its reorganization was not as “clean” as it could have been — Meta (META.O) C

arXiv:2607.00007v1 Announce Type: cross Abstract: Large language model (LLM)-based web agents reduce manual scripting for web data collection, yet on live websites, they often miss relevant pages, ret

arXiv:2607.01034v1 Announce Type: cross Abstract: Large language model (LLM)-based conversational agents (CAs) are now ubiquitous, creating new opportunities for AI-mediated behavior change. Their cap

In this post, we share best practices for reliable multi-turn RL training. We cover how to build a training environment you can trust, set up an external evaluation, design a reward aligned with the e

arXiv:2607.00874v1 Announce Type: new Abstract: This paper introduces a probabilistic framework and hybrid validation methodology for V2X-enabled Collective Perception (CP) in complex traffic scenario

Building on Devin's new capabilities, today we're announcing the Security Vulnerability Remediation Program: a tailored engagement to take your security backlog towards zero in six weeks. Remediation

arXiv:2607.01087v1 Announce Type: cross Abstract: Generative AI is shifting software engineering from a practice organized around scarce implementation effort toward one organized around abundant, low

arXiv:2607.00642v1 Announce Type: new Abstract: Reinforcement learning has proven to be a valuable tool in the creation of advanced AI and robotic systems, contributing to everything from game playing

arXiv:2607.01047v1 Announce Type: new Abstract: Complexity and interpretability rarely coincide: systems rich enough for complex behaviours to emerge are usually too opaque to question, while transpar

This post credits Murtaza Khomusi for a contribution shared by Jerry Liu on X (formerly Twitter), likely related to AI, LLMs, or open-source development given the context of Jerry Liu's typical conten

arXiv:2603.14354v3 Announce Type: replace-cross Abstract: End-to-End autonomous driving (E2E-AD) systems face challenges in lifelong learning, including catastrophic forgetting, difficulty in knowledg

Yohei Nakajima shared a brief update on X about completing a talk and meeting interesting people afterward. The post reflects a positive experience at what was likely a speaking engagement or event. W

eve is like Next.js, for agents framework for building agents. one folder, durable by default ↓ https://x.com/vercel/status/2067180054979936413 Introducing eve, an agent framework. 𝚊𝚐𝚎𝚗𝚝/ 𝚊𝚐𝚎𝚗𝚝.𝚝𝚜 𝚒𝚗𝚜

Replit has re-introduced Fable 5, an AI coding assistant designed to handle longer and more complex projects. Users can access this feature by enabling 'High effort mode' in the Replit Agent tool. Thi

Fable: 'you have Unity and access to MCP. I want you to build a game that is a unique twist on a FPS. You want the player to say 'wow' & 'so clever' and to enjoy the core gameplay loop' WebGL: https:/

arXiv:2607.00918v1 Announce Type: cross Abstract: Although large language models (LLMs) have demonstrated impressive creative fiction generation, they struggle to maintain narrative consistency and co

Fugu is now available on OpenCode! ✨ When our team was developing Fugu’s multi-agent orchestration, OpenCode was our tool of choice to verify our models. We share a core philosophy with the OpenCode t

Full prompt: you have unity and access to an MCP server. I want you to build a game that is a unique twist on a FPS, with excellent graphics and such (download assets as needed). First generate 20 uni

Fun chat with @hwchase17 talking about our work on Engine! Special episode with @bentannyhill on the Max Agency podcast. A month ago, his team shipped LangSmith Engine, our agent that hunts through yo

arXiv:2601.04424v2 Announce Type: replace Abstract: Large language models (LLMs) now support contexts of up to 1M tokens, but their strengths and weaknesses on complex long-context tasks remain unclea

Agent evals are repeatable tests that score whether AI agents completed a task correctly. Learn how to design rubrics, test suites, and trace-based evals that catch failures and prevent reward hacking

ORA.ai is a tool that evaluates website 'agent readiness' by analyzing how well-suited a site is for autonomous agent interaction, then generates prompts that coding agents can use to implement necess

arXiv:2607.00926v1 Announce Type: cross Abstract: Generalizing machine learning models to environments that differ from their training distribution remains a critical hurdle, particularly when data fr

arXiv:2607.00191v1 Announce Type: cross Abstract: Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-percep

I really like this 'understand to participate' framing of the cognitive debt problem when working with coding agents That's where another answer comes in: we can understand to participate. You can lea