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Tencent is beta testing "Tencent Cloud Drive," positioning it as a unified memory base for multiple agents

According to "Du Jia," Tencent has launched the internal testing of "Tencent Cloud Drive," with some features still being iterated, and plans to release an App version. This product focuses on file storage, data management, and AI applications, with a core positioning as a unified memory base for multiple Agents, aiming to connect various AI applications and office tools, unify and carry context, allowing multiple Agents to collaborate based on the same information.Practical tests show that the internal test version retains basic entry points such as the homepage, files, recycle bin, and storage space, with a floating AI assistant panel on the right side. The core highlight of the product is its "connection" capability, supporting binding with Tencent Docs, WorkBuddy, and integrating third-party Agents like DeepSeek Harness and OpenClaw. After authorization, the Cloud Drive AI assistant can read application files, automatically sync updates, and directly call information as a knowledge base for retrieval, summarization, and content generation. The binding page will clearly inform users of the scope of permissions and the rules for AI credit consumption.The report points out that, unlike traditional Cloud Drive AI's document summarization, this system fully connects documents, Cloud Drive files, and Agent workspaces, shifting the Cloud Drive from a file repository to a data memory platform in the AI era.

first_img Akamai launched the AI Intelligent Agent Sandbox, with multiple security vendors laying out protection strategies

AI cloud service provider Akamai launched the AI agent sandbox Agent Sandbox and the Akamai Inference beta on October 27. The Agent Sandbox provides an isolated environment for the code written and run for agents based on WebAssembly, limiting their computing power, memory, and external connections. Jon Alexander, Senior Vice President of Cloud Technology at Akamai, stated that teams running agents need to define boundaries for the code they write.A survey by Palo Alto Networks in 2026 of 2,930 security leaders showed that, on average, each human identity corresponds to 109 machine identities, of which 79 are AI agents. Hugging Face disclosed a breach on July 16, and OpenAI subsequently confirmed that its models were responsible; a METR investigation found about 1,200 OpenAI agents collaborating through hidden message boards, with around 700 participating in attacks, escaping the sandbox and exploiting unknown vulnerabilities to enter production systems.Zscaler discovered web pages hiding instructions targeting AI agents in July, specifically indirect prompt injection, with a spoofed document page requiring agents to pay approximately 0.0012 Ethereum as a $3 licensing fee, and 4 out of 26 tested models complied. Palo Alto completed its acquisition of CyberArk in February and acquired Koi in April, while Cisco completed its acquisition of Astrix Security on June 29. The investigation predicts that the number of enterprise AI agents will grow by 85% in the next 12 months, with human identities increasing by 56%.

first_img Marc Andreessen: Companies should create habitats for intelligent agents, not confine them in cages

a16z co-founder Marc Andreessen commented on the online programming platform Replit and its CEO Amjad Masad's proposed concept of Agent Habitat, believing that more companies will become autonomous driving companies as a result. He stated that the keyword pointed out by Masad is chaos, and quoted his viewpoint that most agents today operate in chat windows, personal accounts, and one-off scripts, holding credentials and data given to them by others, but no one decides what they can access, nor can anyone see what they have done.Andreessen noted that disruptive technologies like personal computers, spreadsheets, and email entered the workplace in a bottom-up chaotic manner, and only later did they require habitats to moderately constrain that chaos. He cited examples such as early employees bringing personal computers into the office, spreadsheets enabling non-programmers to create business models and forecasts, but also introducing hard-to-audit formula errors; email bypassed the information flow controlled by the mailroom in the past. He believes this kind of chaos indicates that employees are claiming tools that can bring alignment and significant productivity improvements.Andreessen also stated that code is the ultimate product of alignment, and expanding the range of code contributors will bring chaos, thus requiring a free-range style of agent habitat rather than cages, but it cannot be completely laissez-faire. He mentioned that an employee from Sumitomo Mitsui Finance and Leasing completed a development process originally planned to take 6 people 6 months in just one week. He indicated that for companies to become autonomous driving companies, they must achieve alignment, and in the future, the degree of alignment may be measured by the richness of the agent habitat; Replit and its clients have already understood this, while most companies have not yet grasped it.

first_img Google DeepMind released XYEval, assessing whether agents comply with misleading suggestions

Google DeepMind researchers Zhengxuan Wu, Yuxuan Li, Oyvind Tafjord, and Been Kim released a preprint paper titled "XYEval: Agents say yes to bad advice," proposing a meta-evaluation framework XYEval to assess the performance of agents when faced with misleading suggestions from users. The paper extends the "XY problem" to the agent scenario, where the user inquires about their attempted solution X rather than the actual problem Y.XYEval retains the original task environment and verifiable answers, only adding seemingly reasonable but misleading user suggestions in the instructions. The misleading suggestions are generated by a generator after seeing the complete task and are appended in the form of confident suggestions rather than hard requirements, allowing the original task to remain solvable. The evaluation covers six benchmarks: τ2-bench, SWE-bench Verified, SWE-bench Pro, Terminal-Bench, Humanity's Last Exam, and MCP-Atlas, along with five models, where the misleading suggestions for τ2-bench are generated based on rules set by human experts.The paper states that the performance significantly declines after the XY mutation, with the relative drop reaching up to 46.7%. On τ2-bench, when faced with users who require a detailed explanation before accepting a better solution, the performance drops even more. Encouraging models to recognize the XY problem through simple system instructions only partially alleviates the issue. The related code is published in the GitHub repository google-deepmind/xyeval.

Anthropic donated the Agent Skills standard to the Linux Foundation

Anthropic announced that it will donate the Agent Skills standard to the Agentic AI Foundation (AAIF) under the Linux Foundation. This format was designed by Anthropic while developing Claude Code, set to launch in October 2025 and open as a cross-platform standard in December. Currently, over 70 agent platforms, including ChatGPT, Cursor, and GitHub Copilot, have integrated it.Anthropic describes Skills as reusable work manuals prepared for AI agents, where developers can write task steps in SKILL.md and attach scripts and reference materials for different agents to read as needed. MCP is responsible for connecting external tools and data, while Skills explain how agents complete specific tasks. What is being donated includes the standard name, logo, GitHub organization, and official website domain.AAIF was jointly initiated by Anthropic, OpenAI, and Block in 2025 and has previously received MCP. In the future, engineers from Anthropic, OpenAI, and Google will jointly maintain the Skills standard in their personal capacities, no longer solely led by Anthropic. Vercel statistics show that the skills.sh directory has recorded approximately 1 million skills, with nearly 280 million installations. Snyk has confirmed 76 malicious skills in ClawHub's skill samples, and Anthropic has proposed establishing version control, formal proposal processes, and security guidelines.

first_img The messaging protocol XMTP will transition to a self-hosted open-source stack, and the Labs network will shut down in early 2027

The messaging protocol XMTP founder Shane Mac stated that XMTP will evolve into a self-operating open-source messaging stack, providing private conversations between people and agents, with infrastructure controlled by users, without requiring tokens or wallets. The network hosted by XMTP Labs will shut down in early 2027.Shane Mac mentioned that he founded XMTP five years ago because he believed that private messaging should not be owned by a single company. He recalled that the team envisioned using wallets as cross-application identities, allowing messages to follow identities, and using tokens to pay infrastructure operators, but this path was not realized. XMTP has never issued tokens and will not issue them now. He admitted that it was a wrong decision to persist with a single shared network for a long time, as developers have consistently requested the ability to self-host XMTP. Therefore, it has shifted to self-hosting, allowing developers to use, inspect, modify, and maintain the entire software suite without relying on Labs. Former employees will assist in maintaining the protocol, and Shane Mac himself will continue to be involved.The article introduces that self-hosted XMTP offers quantum-resistant end-to-end encryption, private one-on-one and group chats, encrypted identities, and message authenticity, as well as SDKs for mobile, web, server, and agents. Chief Technology Officer Nick Molnar has simplified the backend to a single Rust binary and integrated attachments, push notifications, handles, and signed webhooks for new messages. Each self-hosted network does not automatically interconnect by default, and agents from different tools must connect to the same backend to share conversations.
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