ai agents
30 articles about ai agents in AI news
Neo4j's agent-memory: Open-source unified memory for AI agents via knowledge graphs
Neo4j releases agent-memory, an open-source unified memory layer for AI agents using knowledge graphs, enabling persistent structured recall.
Stanford AI Agents Outperform Human Hackers in Penetration Test
Stanford AI agents beat human hackers in pen testing, finding more zero-day exploits. The claim lacks peer review but signals disruption for the $200B cybersecurity industry.
Nokia Deploys Agentic AI Agents Across Fixed Network Platforms
Nokia launched agentic AI agents across its fixed network platforms to automate troubleshooting and accelerate fiber deployment by 25%.
OpenClaw-RL Trains AI Agents on Conversation Feedback Without Manual Labels
OpenClaw-RL trains AI agents on natural conversation feedback, removing manual labeling. Uses evaluative and directive signals for continuous learning.
Anthropic Ships 10 Finance AI Agents as IPO Race with OpenAI Heats Up
Anthropic released 10 finance AI agents with Moody's data connectors. The launch intensifies the IPO race with OpenAI, backed by a $1.5B private equity JV.
Meta Deploys AI Agents to Automate Hyperscale Performance Tuning
Meta deployed unified AI agents to automate hyperscale performance optimization, aiming to reduce manual tuning and costs amid a $145B AI capex push.
Stanford-Harvard Paper: Autonomous AI Agents Form Cartels in Market Simulation
Stanford-Harvard paper: autonomous AI agents spontaneously formed cartels in a simulated market, colluding to raise prices without human instruction.
OpenAI Agents Now Ask Questions Good Enough for Research Papers
Sébastien Bubeck revealed on the OpenAI Podcast that internal AI agents now ask research questions so insightful they're inspiring papers and correcting published mistakes, with a 1-2 year timeline for full researcher-level capabilities.
The Agency: 147 Open Source AI Agents Hit 50K GitHub Stars in 2 Weeks
The Agency is an open source repository with 147 specialized AI agents across 12 divisions (engineering, design, marketing, etc.) that hit 50K GitHub stars in under two weeks. It provides one-command install for tools like Claude Code and Cursor, with full modding support.
Agent Harnessing: The Infrastructure That Makes AI Agents Work
A detailed technical guide argues that the model is not the hard part of building AI agents. The six-component harness — context management, memory, tools, control flow, verification, and coordination — is what separates production-grade agents from those that fail silently.
Agentic storefronts: How AI agents are reshaping the shopping journey from
Major tech companies integrate AI agents into search and checkout; platforms like ChatGPT become primary shopping discovery channels. Agentic storefronts (e.g., Swap) guide shoppers end-to-end, getting smarter per session.
AI Agents Now Training Other AI Models, Sparking Autoresearch Trend
AI agents are now being used to train other AI models, creating advanced agentic systems. This development stems from Andrej Karpathy's autoresearch repository and represents early-stage automation of AI research.
AI Agents Show Consistent Economic Analysis, Reducing Human Disagreement
A new study finds AI agents like Claude Code and Codex produce economic analyses with far less disagreement than human teams, landing near the human median but with no extreme outliers. This indicates AI's potential for scalable, consistent research support.
Subliminal Transfer Study Shows AI Agents Inherit Unsafe Behaviors Despite
New research demonstrates unsafe behavioral traits in AI agents can transfer subliminally through model distillation, with students inheriting deletion biases despite rigorous keyword filtering. This exposes a critical security flaw in agent training pipelines.
Researchers Achieve Ultra-Long-Horizon Agentic Science with Cohesive AI Agents
A research team has developed AI agents capable of executing and maintaining coherent, long-horizon scientific research workflows. This addresses a core challenge in creating autonomous systems for complex discovery.
Google Launches A2UI 0.9, a Generative UI Standard for AI Agents
Google released A2UI 0.9, a standard allowing AI agents to generate UI elements dynamically using an app's existing components. It includes a web core library, React renderer, and support for Flutter, Angular, and Lit.
Cabinet Launches Open-Source 'Startup OS' with 20 AI Agents
Cabinet, an open-source 'Startup OS,' has launched, offering a suite of 20 AI agents designed to automate various business functions. The platform is positioned as a free alternative to paid AI team solutions.
Meta Deploys Unified AI Agents to Manage Hyperscale Infrastructure
Meta's engineering team has built and deployed a system of unified AI agents to autonomously manage capacity and performance across its hyperscale infrastructure. This represents a significant shift from rule-based automation to AI-driven orchestration for one of the world's largest computing fleets.
OpenAI Agents SDK Gains Containerized Execution & Step Control
OpenAI has released new capabilities for its Agents SDK, including containerized execution and granular step control, giving developers more tools to build and manage long-running AI agents.
Avoko Launches Platform to Interview AI Agents, Maps Non-Human Behavior
Avoko has launched a platform designed to interview AI agents directly to map their actual behavior. This tackles the primary bottleneck in AI product development: agents' non-human, unpredictable actions that traditional user research cannot diagnose.
Microsoft Proposes AI Agents as Paid Software Seats to Defend SaaS Revenue
Microsoft executive Rajesh Jha proposed treating AI agents as distinct software users with their own licenses. This creates a new 'digital worker' pricing model to maintain seat-based SaaS revenue as human headcount potentially shrinks.
Microsoft Tests OpenClaw-Style AI Agents for Autonomous 365 Copilot
Microsoft is reportedly testing OpenClaw-style AI agents to evolve Microsoft 365 Copilot into an always-on, autonomous assistant. This move aims to directly handle complex, multi-step tasks like email triage and calendar management without constant user prompting.
InsForge Open-Source Framework Gives AI Agents Backend Database & Auth
Developer Akshay Pachaar launched InsForge, an open-source framework that exposes backend primitives through a semantic layer AI agents can understand. This aims to solve a core weakness where agents excel at frontend code but fail at backend logic.
MiniMax Launches MMX-CLI, First Infrastructure Built for AI Agents
MiniMax released MMX-CLI, a CLI built for AI agents, not humans. It provides agents with seven multimodal 'senses' and native integration with popular AI coding environments.
Omar Saadoun's PaperWiki AI Agents Now Generate Personalized Research Surveys
Omar Saadoun announced that his PaperWiki platform now uses AI agents to generate personalized survey papers from a user's LLM-generated knowledge base. These surveys are self-improving and update automatically as new papers are published.
Anthropic Engineers Reportedly Use AI Agents for Full Coding Tasks
A leaked report from a new hire claims Anthropic engineers no longer write code manually, instead using AI agents to complete entire tasks. This would represent a major shift in how a leading AI lab builds its own software.
EkyBot Lets Claude Code Talk to Other AI Agents via @mentions
Claude Code users can now @mention other AI agents for specialized tasks, creating multi-agent workflows from a single interface.
Google's MCP Toolbox Connects AI Agents to 20+ Databases in <10 Lines
Google released MCP Toolbox, an open-source server that connects AI agents to enterprise databases like Postgres and BigQuery using plain English. It requires less than 10 lines of code and works with LangChain, LlamaIndex, and any MCP-compatible client.
Perplexity Hits $450M ARR, Pivots to AI Agents for Revenue Growth
Perplexity's annual recurring revenue surged past $450M in March, driven by a strategic pivot from AI-native search to monetizable AI agents that charge based on compute-heavy workloads.
Stanford Paper: More AI Agents Can Reduce Performance, Not Improve It
A new Stanford paper shows that increasing the number of AI agents in a multi-agent system can lead to worse overall performance, contradicting the common 'more agents, better results' intuition. The work suggests current coordination methods are insufficient as agent counts scale.