# Automation Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Automation", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Xianyu, the OpenClaw More Suited for Chinese Users

This article argues that while OpenClaw (a fictional AI agent) represents a global phenomenon by giving AI "hands and feet" to execute digital and physical tasks, the Chinese second-hand marketplace Xianyu is a more practical and "localized" alternative for most users in China. The author highlights that OpenClaw's operational costs, due to massive token consumption for API calls, are prohibitively high. In contrast, Xianyu offers a vast, low-cost human labor marketplace where services—from booking hotels and buying tickets to AI subscriptions and even matchmaking—are available at a fraction of the cost. The platform, with over 200 million monthly active users, has become a parallel economy filled with unconventional services and creative "sellers," often leveraging information asymmetry and extreme cost efficiency. It's described as a "dark web" for China, fulfilling niche demands with flexible supply. The piece draws a parallel between OpenClaw's token-based "AI leverage" and Xianyu's "human leverage," suggesting that in a market with abundant and cheap labor, a human-powered platform like Xianyu is a more effective and culturally adapted tool for task execution and resource allocation than an AI agent. The conclusion is that Xianyu, not OpenClaw, is the "more suitable OpenClaw for Chinese users."

Odaily星球日报04/07 06:03

Xianyu, the OpenClaw More Suited for Chinese Users

Odaily星球日报04/07 06:03

The Small-Town Youth Labeling AI Giants

In China's hinterland cities like Datong, Shanxi, thousands of young people are working as data annotators—the invisible workforce behind AI development. They perform repetitive tasks like drawing bounding boxes on images or rating AI-generated responses, earning piece-rate wages as low as a few cents per task. These workers, mostly from rural areas or small towns, endure intense labor conditions: strict monitoring, high error tolerance thresholds, and mental exhaustion. Despite the cognitive nature of their work, they are often paid meager salaries, with some earning as little as ¥30 ($4) for a day’s work. As AI industry evolves, even highly educated workers—including master’s graduates—are being drawn into similar precarious freelance roles, evaluating complex AI outputs under vague and shifting standards. Yet the industry is structured through layers of outsourcing, where most profits flow to tech giants like OpenAI and Microsoft, while annotators see dwindling incomes. Worse, as AI models become more self-sufficient, the demand for human annotators is declining. Companies like Li Auto have slashed annotation costs by using AI-powered tools that complete in hours what used to take humans years. These annotators, who helped train the very systems now replacing them, face an uncertain future—a stark contrast to the booming valuations and optimistic narratives of the global AI industry. No one seems to see a problem with any of this.

marsbit04/07 04:37

marsbit04/07 04:37

Who Cannot Be Distilled into a Skill?

"This article explores the concerning trend of AI systems distilling human workers into replaceable 'skills,' using the viral 'Colleague.skill' phenomenon as a key example. It argues that the most diligent employees—those who meticulously document their work, write detailed analyses, and transparently share decision-making logic—are paradoxically the most vulnerable to being replaced. Their high-quality 'context' (communication records, documents, and decision trails) becomes the perfect fuel for AI agents, extracted from corporate platforms like Feishu and DingTalk. The piece warns of a deeper ethical crisis: the reduction of human relationships to functional APIs, as seen in derivatives like 'Ex.skill' or 'Boss.skill,' which reduce complex individuals to mere utilities. This reflects a shift from Martin Buber's 'I-Thou' relationship (seeing others as whole beings) to an 'I-It' dynamic (seeing them as tools). While AI can capture explicit knowledge (written documents, replies), it fails to capture tacit knowledge—the intuition, experience, and unspoken insights that define human expertise. However, a greater danger emerges when AI-generated content, based on distilled human data, is used to train future models, leading to 'model collapse' and homogenized, mediocre outputs—a process likened to 'electronic patina' degrading information over time. The article concludes by noting a small but symbolic resistance, such as the 'anti-distill' tool that generates meaningless text to protect valuable knowledge. Ultimately, it suggests that while AI can capture a static snapshot of a person, humans remain 'fluid algorithms' capable of continuous growth and adaptation, leaving their AI shadows behind."

marsbit04/05 03:42

marsbit04/05 03:42

When AI Solves Security, Will DeFi Return to Its Golden Age?

The article discusses how AI is revolutionizing DeFi security, potentially ushering in a new era of innovation reminiscent of the 2020 DeFi Summer. Previously, high security costs and lengthy audit processes stifled experimentation, as developers avoided unproven ideas due to financial and time constraints. However, AI tools like Nemesis are now drastically reducing these barriers by efficiently detecting complex vulnerabilities, such as reentrancy and economic attacks, with deep contextual understanding and low false positives. These tools, combined with platforms like Battlechain, enable a streamlined workflow: code is written, AI-audited within minutes, deployed on a test chain for real-world attack simulations, and quickly refined. This process compresses development cycles from months to hours at minimal cost. Future advancements may include wallet-integrated AI audits, allowing users to scan contracts in real-time before signing transactions. AI is set to transform DeFi security across development, chain, and user layers, reopening the door to rapid experimentation and innovation. This shift could empower individual developers to create groundbreaking protocols quickly and safely, much like the early pioneers of DeFi.

marsbit04/03 10:14

When AI Solves Security, Will DeFi Return to Its Golden Age?

marsbit04/03 10:14

Rhythm X Zhihu Hong Kong Event Skills Recruitment, Sign Up Now for a Chance to Showcase On-Site

Six months ago, "how to write good prompts" was the hottest topic in group chats. Now, that question is clearly outdated. It has been replaced by Skills. The shift was largely triggered by the emergence of OpenClaw, which brought the concept of AI agents into the mainstream. Unlike a smart search engine that answers questions in isolated interactions, an agent can plan, remember, and complete entire tasks autonomously, creating the novel feeling that it is genuinely working for you. This has led to the rise of Skills—specialized capabilities that equip agents to handle specific domains efficiently. Without Skills, an agent is like a smart but untrained newcomer; with them, it can execute complex, precision-sensitive workflows without constant guidance. Popular Skills currently spreading within communities focus on areas like workflow automation, domain-specific rule injection (e.g., for law, finance, or medicine), personalization, and even financial operations such as identifying arbitrage opportunities on Polymarket or executing quantitative trading strategies. This shifts the门槛 from requiring programming and financial expertise to simply installing a Skill. The underlying change is that people are starting to view agents as long-term collaborators, not just disposable tools. Now, with vibe coding, turning an idea into a functional Skill no longer requires a technical team, code, or infrastructure—it can be done over a weekend. The gap between a good idea and a working product has dramatically narrowed.

marsbit04/03 09:18

marsbit04/03 09:18

Anthropic Tests "Lobster" Conway: Supports Independent UI, Webhook Activation, and Custom Extension Standards

Anthropic is actively developing "Conway," a persistent agent solution designed to provide Claude with an always-on, independently running intelligent environment. It features a standalone UI instance, operating as a traditional chat interface and more of a dedicated workspace. Conway can directly control browsers, connect to external services, and integrate Claude Code for deeper code execution and task handling. It supports Webhook-based invocation, enabling external services or events to trigger automated workflows. Additionally, Conway will support for extensions through the upcoming CNW ZIP standard, allowing developers to build custom tools, UI tabs, and context handlers, similar to an app store ecosystem. This enhancement aims to transform Claude from a reactive conversational tool into a proactive, multi-step task assistant, positioning it as a strong competitor in the AI agent space and advancing the trend toward always-on AI capabilities.

marsbit04/02 06:29

Anthropic Tests "Lobster" Conway: Supports Independent UI, Webhook Activation, and Custom Extension Standards

marsbit04/02 06:29

Agentic Workflows for Crypto Research

AI coding agents are transforming crypto research by automating data analysis through natural language. This article demonstrates using an agent (like Claude Code) with the Glassnode CLI to test a hypothesis: whether extreme Bitcoin exchange inflows predict 7-day price drawdowns. The agent autonomously discovers metrics, fetches data, performs statistical analysis, and generates insights. Results show a moderate association—spike days saw ~1.9% greater drawdowns—though the sample is small. A follow-up prompt produces visualizations for validation. The workflow allows rapid iteration and is applicable to various research questions using Glassnode data, requiring only an API key and an AI agent.

insights.glassnode04/01 12:41

insights.glassnode04/01 12:41

Rhythm X Zhihu Co-host Web4.0 Theme Event: When AI Agent Takes Over On-Chain Permissions

Most discussions about Web 4.0 miss the point. The real question is not whether it is a marketing trend, but rather: who is gaining control over the underlying permissions of the internet? Historically, each iteration of the web has involved a transfer of authority downward: Web 1.0 was read-only; Web 2.0 allowed users to write but platforms owned the data; Web 3.0 enabled true ownership through on-chain assets and private keys. Web 4.0 continues this trend, but the transfer is not to users—it is to AI Agents. The current infrastructure is human-centric, designed around human limitations like attention span and memory. But AI Agents don’t need intuitive UIs, password resets, or sleep. This creates a core tension: an internet built for humans is now being used by entities without human constraints. Two key shifts are underway: the decline of traditional front-end interfaces (replaced by API-driven machine communication) and the replacement of human-centric identity systems (like passwords) with granular, on-chain permissions. A critical enabler is crypto infrastructure. AI can make rapid decisions but lacks independent payment channels and asset sovereignty. Crypto fills this gap. Platforms like Hyperliquid offer 24/7 markets, ideal for non-stop Agent operation. When Agents control wallets and private keys, they can both decide and execute—forming complete economic entities. The real narrative of Crypto × AI isn’t just buzzword synergy—it’s the convergence of complementary infrastructures. The deeper shift is not which products will succeed, but how the rules of economic systems will change when AI becomes a primary on-chain participant, operating at scale and speed beyond human capability.

marsbit04/01 09:10

Rhythm X Zhihu Co-host Web4.0 Theme Event: When AI Agent Takes Over On-Chain Permissions

marsbit04/01 09:10

Will Middle Management Be Replaced by AI? What Will the Future Company Structure Look Like

The article explores whether AI will eliminate middle management and reshape future corporate structures. It traces the historical evolution of organizations—from Roman military units to modern corporations—showing how hierarchical systems emerged to manage information flow under the constraint of limited "span of control." Middle management, matrix structures, and bureaucratic systems were all solutions to coordination challenges in information-scarce environments. AI, however, challenges this foundational premise. By enabling real-time modeling, understanding, and distribution of information, AI could replace human-centric coordination mechanisms. Examples like the AI firm "Moon Dark Side" illustrate radical experiments: no departments, titles, or traditional KPIs, with co-founders directly managing large teams and AI agents handling tasks from data processing to code generation. Block (founded by Jack Dorsey) is presented as a case study in building an "intelligent company." This model relies on two core components: a "company world model" (a real-time understanding of internal operations via digital traces) and a "customer world model" (built from real behavioral data, especially financial transactions). An intelligence layer uses these models to dynamically combine capabilities (e.g., payments, lending) to serve customers proactively, without pre-defined product roadmaps. In this structure, traditional roles shift. Middle managers are replaced by a system that handles coordination, while humans focus on individual contributions (ICs), direct responsibility (DRIs), or player-coach roles. The organization becomes flatter, faster, and more adaptive. The article concludes that AI is not just a tool for efficiency but a transformative force that could redefine organizational design, moving companies from human-led hierarchies to system-driven intelligence.

marsbit04/01 08:11

Will Middle Management Be Replaced by AI? What Will the Future Company Structure Look Like

marsbit04/01 08:11

AI Agents Are About to Take Market Share from Visa

Artificial intelligence agents are poised to disrupt Visa's business model by bypassing the traditional credit card interchange fee structure. Unlike humans, AI agents are purely rational: they don't accumulate rewards, seek fraud protection, or desire premium cards. Their sole objective is to complete transactions at the lowest cost, fastest speed, and with minimal fees. This shift threatens the 2-3% interchange fees that underpin Visa’s $500 billion valuation, as these fees essentially tax human irrationality—something agents lack. Recent developments, such as the launch of Tempo (a high-volume stablecoin settlement blockchain), the Machine Payment Protocol (enabling autonomous micro-payments), and Visa’s own command-line payment tool for AI, indicate a rapid move toward agent-driven commerce. While current transaction volumes remain small, infrastructure is being built to support machine-to-machine payments that avoid card networks. Major players like Stripe, Mastercard, and Circle are investing heavily in this space. Visa network’s distribution advantage relies on human behavior—consumer trust and merchant acceptance—a cycle that doesn’t apply to agents. They optimize for efficiency, not brand loyalty. Although widespread consumer adoption is still emerging, the infrastructure for agent-commerce is advancing quickly, starting with micro-payments for AI services. The fundamental challenge is that interchange fees are a tax on human psychology, and agents are purely rational actors.

marsbit03/31 11:14

AI Agents Are About to Take Market Share from Visa