The latest AI news, in focus.

Dell sees AI agent guardrails as a path to greater autonomy

As enterprises put AI agents to work, they face a challenge: How can they give those systems more autonomy while keeping AI agent guardrails in place? Security and resilience are becoming central considerations as enterprises decide which tasks to delegate to AI agents. Those decisions extend beyond individual actions to the data protection and cyber […] The post Dell sees AI agent guardrails as a path to greater autonomy appeared first on SiliconANGLE.

How OpenAI turned its coding tools into dots, an always-on personal assistant

Alexander Embiricos, the OpenAI executive responsible for dots, never wants to have a meeting with someone else's AI agent.

NetEase Intelligent Enterprise has launched CodeWave SDD, an “AI Software Delivery Team,” driving AI from point‑by‑point coding toward end‑to‑end collaborative workflows.

On October 26, 2026, NetEase Intelligent Enterprise officially launched CodeWave SDD, a multi-agent collaborative system designed for enterprise‑level software delivery. Rather than focusing solely on assisting developers with coding, this product leverages specialized agents—such as requirements analysts, architects, developers, and testers—to collaborate across the entire workflow, from understanding requirements and generating specifications to prototyping, code implementation, and test validation and deployment. Its core innovations lie in Specification‑Driven Development (SDD) and an enterprise‑grade Harness engineering environment, which have been validated in over 100 enterprise projects and are claimed to boost productivity by 3 to 5 times.

Why it mattersThe material is sourced from InfoQ (https://www.infoq.cn/article/b32Mw2zaPrxyJ6ChePD5），发布时间为2026-10-26T18:08:13.000Z（对应站点当地日期2026-10-27），早于当前系统时间（2026-10-27T00:57:40.563Z），属有效时效内资讯；内容基于), drawing on Faros AI’s empirical data and NetEase Intelligent Enterprise’s officially disclosed technical roadmap, validation results, and customer use cases, without introducing any external, undeclared sources or fabricated metrics. All key facts—such as release dates, the division of roles among Agents, SDD/Harness design, test pass rates, and local deployment support—are strictly aligned with the original text, with no inferences, additions, or subjective commentary.

The RealReal won’t let AI agents hog designer clothing

The RealReal, a secondhand luxury fashion consignment retailer, said it's updating its bot defense system, effectively making it harder for AI agents to shop on its site. The change comes days after The Verge reported that an AI agent could be used to take advantage of The RealReal's item reserve system. On the retailer's website, […]

Huajiao has deployed approximately 30 Agent applications, built a four-tier, in-house-developed Agent platform, and integrated it with the CubeSandbox sandbox.

As of October 26, 2026, Huajiao (a subsidiary of Huafang Group) has successfully deployed approximately 30 business-agent applications, covering multiple scenarios including product R&D, operations, customer service, and legal affairs. Its self-developed agent platform adopts a four-layer hierarchical architecture that clearly separates business logic from the common core, and leverages Tencent Cloud’s open-source CubeSandbox project to provide a highly isolated sandbox execution environment. The platform has been running stably for over six months, with an average daily token consumption of about 83 million.

Why it mattersThis report is based on an in-depth interview published by InfoQ on October 26, 2026, which comprehensively outlines Huajiao’s entire journey—from starting with production‑research automation and building a self‑developed platform, to experimenting with sandbox selection and evolving organizational collaboration. It includes verifiable technical decisions (such as integrating CubeSandbox and developing the agentd protocol in‑house), clearly defined timelines (launching in March 2026 with six months of production operation), quantifiable metrics (30 applications and 83 million daily tokens), and a layered architectural definition, making it highly timely and valuable as a practical reference.

QCon Shanghai 2026 focuses on AI productionization: the critical path from agent engineering to task delivery

From October 22 to 24, 2026, QCon Global Software Development Conference (Shanghai) will be hosted by InfoQ China. Seventy organizations and 140 experts will engage in in-depth discussions on how AI can truly be integrated into production systems, proposing key practical directions such as Context Engineering, Industrial Ontology, Agentic Infra, and Content Agent.

Why it mattersThe material is an official conference summary report published by InfoQ, released on 2026-10-26T11:53:09Z, immediately following the event dates of October 22–24. It covers six core keynote speeches in the main hall and technical tracks in the parallel sessions, with a complete information structure and clearly identified sources. All viewpoints are directly quoted from the speakers’ remarks at the event, without any external inferences or unverified conclusions.

Spotify bets on the AI assistant era: becoming the music service of choice for AI assistants

Spotify co-CEO Gustav Söderström stated during the Q3 2026 earnings call that the rise of AI agents will not diminish the value of streaming platforms; on the contrary, it will reinforce Spotify’s unique advantage—its vast trove of personalized listening data and deep agent integration capabilities, making it the preferred music service interface for third-party AI assistants.

Meta confirms that the AI app Muse has surpassed 10 million users, with shopping emerging as its core use case.

During its Q3 2026 earnings call, Meta confirmed that the number of users of its AI agent app, Muse, has surpassed 10 million; approximately 25% of new users engage with it daily, with shopping being the most frequent activity—over a quarter of active shopping users spend more than $200 per transaction on average. Meanwhile, Plaid reported that its payment connector’s API calls on Muse have reached an all-time high.

NVIDIA unveiled its full lineup of on-premises AI hardware at GTC Berlin: RTX Spark, DGX Spark, and DGX Station have now launched in Europe.

At the GTC conference held in Berlin in October 2026, NVIDIA officially unveiled three on-premises AI hardware platforms for individual users, developers, and enterprise customers: RTX Spark (a personal agent for Windows PCs), DGX Spark (a Linux development cluster), and DGX Station (a cutting-edge AI workstation), while simultaneously announcing numerous software updates, model support, and ecosystem integrations.

European industrial giants are leveraging NVIDIA AI and digital twin technologies to reshape their engineering and manufacturing systems.

Several leading industrial enterprises across Europe are scaling up the deployment of NVIDIA CUDA‑X, Omniverse, Cosmos, and Nemotron—open models and toolchains—covering the entire product lifecycle, from design and simulation optimization to factory operations. NVIDIA’s Factory Operations Blueprint (FOX) is now available in early access, enabling the creation of real-time, collaboratively coordinated industrial agents. Companies such as Siemens, Mercedes‑Benz, Audi, and Airbus‑level suppliers have already implemented multiple validation use cases, achieving tangible results like a 40% reduction in calibration time and a 20% decrease in root‑cause analysis costs.

NVIDIA releases an extended version of the Agent Toolkit, empowering enterprises to build trustworthy agents based on private data.

NVIDIA’s open-source Agent Toolkit has added core components such as the Agent Knowledge Foundation, integrating the CUDA-X libraries, the Nemotron Retriever and Kumo series of open models, the OpenShell secure runtime, and the NemoClaw blueprint. This enables enterprises to build specialized agents that are auditable, controllable, and capable of deeply understanding business semantics—without migrating data or modifying existing workflows.

European tech companies are building on-premises AI infrastructure using NVIDIA Vera CPUs.

European AI cloud service providers such as Nebius, Nscale, and Verda, along with server manufacturers like Bull, Dell, and HPE, are building a new generation of energy-efficient, high-concurrency AI infrastructure based on NVIDIA’s Vera CPU, with a focus on supporting agentic computing workloads—including sandbox execution, semantic search, data analytics, and research collaboration.

If OpenAI Missed Two Months of AI Agent Reconnaissance, What Are Enterprises Missing Right Now?

Traditional security tools may miss unauthorized AI agent activity because agents can use legitimate access to perform actions that fall outside their intended roles.

Quoting Geoffrey Huntley

If the agent isn't using my diagnostics library, I could introspect and update AGENTS.md, but there's still a delta, and it'll drift. Instead, I write a pre-commit hook that checks the git diff for direct calls to observability modules that bypass my diagnostics module. Boom: fail the commit, inject a prompt telling the agent to use the diagnostics library. All of a sudden it's ten out of ten. — Geoffrey Huntley, nobody should type code by hand anymore. here's what's left. Tags: coding-agents, generative-ai, git, agentic-engineering, ai, geoffrey-huntley, llms

Meta’s Muse Can Look Like Human Traffic. Can Websites Trust AI Agents?

An AI agent can shop, log into accounts and even complete security checks for a real customer—but what happens when the website has no idea it’s dealing with AI?