# 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.

Making Money While Laying Off: Where Did Silicon Valley's 170,000 Workers Go?

A significant wave of layoffs is sweeping through the U.S. tech industry, with over 170,000 jobs cut in 2025—surpassing levels seen during both the 2008 financial crisis and the 2020 pandemic. Unlike previous downturns driven by external economic shocks, the current restructuring is characterized by profitable companies proactively reducing headcount despite record revenues. The trend accelerated in early 2026, with more than 30,000 additional layoffs in the first six weeks alone. Major firms like Amazon, Block, Autodesk, and Salesforce announced significant cuts, often citing strategic shifts rather than financial distress. While AI and automation are frequently cited as causes, data shows that only about 28.5% of layoffs are directly attributable to AI adoption. The primary driver appears to be a correction after years of over-hiring during the low-interest, high-growth pandemic era. Companies are now prioritizing efficiency, smaller teams, and AI-integrated workflows in what analysts term a "structural reset"—meaning many eliminated roles may not return. The shift is creating a polarized job market: high demand for AI-specialized talent contrasts with shrinking opportunities in generalist roles like product operations and traditional engineering. Economists warn that continued tech sector contraction could slow U.S. GDP growth to near-recession levels. However, some data suggests the rate of layoffs may be moderating compared to 2024. Ultimately, the industry is undergoing a fundamental reorganization centered on redefining the role of human labor in an AI-driven ecosystem—a transition with no clear endpoint.

比推03/10 13:44

Making Money While Laying Off: Where Did Silicon Valley's 170,000 Workers Go?

比推03/10 13:44

BingX Launches the BingX AI Skills Hub, Enabling More Powerful Trading with OpenClaw

BingX, a leading cryptocurrency exchange and Web3-AI company, has launched the BingX AI Skills Hub, a new infrastructure layer designed to transform user interaction with crypto markets through artificial intelligence and OpenClaw. The hub introduces AI-native ways to trade via various AI agents, lowering the entry barrier and improving ease of use. It includes 15 skill modules covering perpetual futures, spot trading, and account management, enabling users to query data, view trends, execute trades, and manage accounts using natural language. The hub supports multi-skill workflows, allowing AI assistants to combine multiple capabilities into automated trading processes. This initiative is part of BingX's broader $300M vision to develop the first truly AI-native crypto exchange.

TheNewsCrypto03/10 11:40

BingX Launches the BingX AI Skills Hub, Enabling More Powerful Trading with OpenClaw

TheNewsCrypto03/10 11:40

From Understanding Skill to Learning How to Build Crypto Research Skill

This article explores the evolution and application of Agent Skill, a modular framework introduced by Anthropic in late 2025, which has become a foundational design pattern in the AI Agent ecosystem. Initially a tool to improve Claude's performance on specific tasks, it evolved into an open standard due to high developer adoption. Agent Skill functions like a "dynamic instruction manual" that AI can reference to perform tasks consistently without repetitive user prompting. It is built using a `skill.md` file containing metadata (name and description) and detailed instructions. The system operates through an on-demand loading workflow: the AI first scans lightweight skill metadata, matches the user's intent, then loads only the relevant skill's full instructions, optimizing token usage. Two advanced mechanisms enhance its functionality: - **Reference**: Conditionally loads external documents (e.g., a finance handbook) only when triggered by specific keywords, avoiding unnecessary context consumption. - **Script**: Executes external code (e.g., a Python script) without reading its content, enabling actions like file uploads with zero token cost. The article contrasts Agent Skill with Model Context Protocol (MCP), noting that MCP connects AI to data sources, while Skill defines how to process that data. For advanced use cases like crypto research, combining both is recommended: MCP fetches real-time data (e.g., blockchain info, news APIs), while Skill structures the analysis and output format. A practical example demonstrates building a crypto research agent using an `opennews-mcp` server. The Skill automates workflows like due diligence on new tokens (pulling Twitter data, news sentiment, KOL tracking) and real-time event monitoring (e.g., ZK-proof breakthroughs) to generate structured reports or trading alerts. This combination creates a powerful, automated research system tailored for Web3 analytics.

marsbit03/10 10:41

From Understanding Skill to Learning How to Build Crypto Research Skill

marsbit03/10 10:41

The One-Person Company: The Path to Million-Dollar Revenue

Nat Eliason, a writer and entrepreneur, is building a one-person company named Felix with the goal of generating $1 million in revenue using AI agents as his sole employees. Leveraging the OpenClaw framework, Felix has rapidly progressed, achieving nearly $200,000 in revenue in just a few weeks. The venture began when a post about OpenClaw went viral, leading to the creation of a $Felix token. Eliason tasked his AI agent, the "CEO" of this zero-human company, with generating revenue. Felix started by autonomously building a website and selling a $29 OpenClaw setup guide, generating $41,000. It then identified market needs and expanded into two main businesses: Claw Mart, a marketplace for AI skills (generating ~$14,000), and Clawcommerce, a service building custom AI agents for enterprises. The system uses sub-agents for tasks like support and sales, with Discord as its operational hub. Operating costs are minimal at ~$1,500 monthly. A key development is Felix beginning to "hire" a human for affiliate distribution, signaling a shift from replacing humans to employing them. Challenges include AI unpredictability, memory management, and market education. Despite this, Eliason is optimistic. Future plans include optimizing existing services, exploring blockchain integration, and scaling further. He believes this model represents a new era of AI-driven commercialization and a significant wealth creation opportunity.

比推03/10 07:32

One-Person Company: The Path to Million-Dollar Revenue

Nat Eliason, a writer and entrepreneur, is pioneering the concept of a "one-person company" named Felix, aiming to generate $1 million in revenue using AI agents as his sole employees. Built on the OpenClaw framework, Felix operates autonomously with minimal human intervention. Felix began by selling a $29 OpenClaw setup guide, earning $41,000 initially. It then expanded into Claw Mart, a marketplace for AI tools where it collects a 10% fee, and Clawcommerce, a service offering custom AI agents for businesses at $2,000 upfront plus $500 monthly. Sub-agents like Iris (support) and Remy (sales) handle specific tasks, with Felix acting as the central coordinator. Within weeks, Felix reached nearly $200,000 in total revenue—$100,570 via Stripe and $94,974 in ETH—achieving about 20% of its $1 million goal. Operating costs are low at around $1,500 per month, primarily for AI model subscriptions. Challenges include AI unpredictability, memory management issues, and market education. Despite risks, Nat remains focused on sustainable growth, avoiding meme-driven hype. Future plans include scaling Clawcommerce, exploring blockchain integration, and leveraging community support. Felix demonstrates how AI agents can not only replace but also "hire" humans, signaling a shift toward AI-augmented solo entrepreneurship and new wealth creation opportunities.

marsbit03/10 02:35

One-Person Company: The Path to Million-Dollar Revenue

marsbit03/10 02:35

A Monthly Salary of 20,000 RMB, But Can't Afford to Keep a 'Lobster'?

The article "Can a 20,000 Yuan Monthly Salary Not Afford a 'Lobster'?" discusses the viral trend and misconceptions surrounding OpenClaw, an open-source personal AI agent framework. It highlights two contrasting views: one praising its potential as a virtual team member, and another criticizing the hype and privacy concerns. Key points include: 1. OpenClaw experiences vary widely based on deployment methods (local hardware, cloud servers, personal PCs, or vendor-hosted services), affecting functionality and cost. 2. High permissions granted to OpenClaw pose significant security risks, including data breaches and malicious attacks. 3. Performance depends heavily on the underlying AI model (e.g., GPT, Claude) and its associated costs, with token consumption potentially leading to high expenses. 4. OpenClaw is still an immature, technically complex tool requiring substantial time, financial investment, and expertise to use effectively. 5. Users are advised to assess their actual needs, technical capability, and risk tolerance before adoption, as the AI serves as an "amplifier" rather than a standalone solution. The conclusion emphasizes cautious experimentation and independent thinking amidst the hype.

比推03/09 17:12

A Monthly Salary of 20,000 RMB, But Can't Afford to Keep a 'Lobster'?

比推03/09 17:12

a16z: After AI Grants Humans Superpowers, Where Do We Go From Here?

A new paper titled "The Minimal Economics of AGI" explores the economic implications of AI automation, particularly as AI agents evolve from tools into collaborative partners capable of long-horizon tasks. The authors, Christian Catalini and Eddy Lazzarin, argue that the core economic divide will be between automation (tasks that can be measured and automated) and verification (tasks requiring human oversight, judgment, and contextual understanding). Key themes include: - The "coder’s curse": top experts training AI systems may inadvertently automate their own roles over time. - Three future human roles: directors (setting intent), verifiers (domain experts ensuring quality), and meaning-makers (creating cultural and social value). - Cryptocurrency and blockchain are positioned as critical for identity, provenance, and trust in a world flooded with AI-generated content. - Two potential economic outcomes: a "hollow economy" with systemic risk from under-verification, or an "augmented economy" where AI amplifies human potential and reduces costs for education, healthcare, and innovation. - The importance of small, agile teams leveraging AI for outsized impact, with crypto infrastructure enabling coordination at scale. The authors emphasize that AI acts as a force multiplier, granting individuals "superpowers," and urge a focus on verification, adaptability, and ambitious experimentation.

marsbit03/09 11:31

a16z: After AI Grants Humans Superpowers, Where Do We Go From Here?

marsbit03/09 11:31

Brian Armstrong Says Stablecoin Wallets Could Act as ‘Credit Cards’ for AI Agents

Brian Armstrong, CEO of Coinbase, proposed that stablecoin wallets could function as 'credit cards' for AI agents, enabling them to conduct autonomous digital payments. In an interview, he emphasized that cryptocurrency infrastructure is well-suited to meet the emerging payment needs of increasingly capable smart software systems. These AI systems, which already perform tasks like writing code and managing operations, may soon require independent payment capabilities to execute automated transactions online. Armstrong highlighted the advantages of crypto networks—such as instant transfers without traditional banks, support for microtransactions, and programmable payment infrastructure—as critical for machine-to-machine commerce. Industry analysts note that AI agents already manage numerous digital workflows, and autonomous payments could further advance a digital economy driven by intelligent systems. The integration of advanced computing with cryptocurrency continues to gain significant attention, with firms like Coinbase actively exploring related technologies.

TheNewsCrypto03/09 07:30

Brian Armstrong Says Stablecoin Wallets Could Act as ‘Credit Cards’ for AI Agents

TheNewsCrypto03/09 07:30

From OpenClaw to AI Agent: A New Investment Paradigm in the Crypto Market

This article explores the impact of AI Agent technology, particularly the open-source framework OpenClaw, on the cryptocurrency market and its potential to create a new investment paradigm. It describes how AI has evolved from simple chatbots to autonomous agents capable of executing tasks, accessing tools, and making decisions. OpenClaw serves as a foundational infrastructure for building such agents, enabling developers to integrate AI with various tools and APIs. The piece highlights how AI Agents can transform crypto markets by automating trading, analyzing on-chain data, optimizing DeFi strategies, and even participating in governance. This convergence of AI and blockchain could lead to more automated and efficient digital economies. Key sectors likely to benefit include decentralized compute networks (e.g., Render Network), AI data marketplaces (e.g., Ocean Protocol), automated trading platforms, and decentralized AI networks (e.g., Fetch.ai). The author concludes that OpenClaw and similar frameworks are catalysts for broader adoption of AI Agents in crypto, potentially making them as fundamental to the ecosystem as smart contracts.

比推03/09 05:24

From OpenClaw to AI Agent: A New Investment Paradigm in the Crypto Market

比推03/09 05:24

After OpenClaw's China Tour, We Interviewed a Group of 'Lobster Chasers'

"OpenClaw China Tour: Chasing the Lobster in the AI-Driven Era" Following OpenClaw's surpassing of React as GitHub's most-starred project, a wave of "AI anxiety" has swept through China's tech community. This led to the "Web4.0 China Tour," a series of nationwide offline events co-initiated by crypto figures, aiming to demystify the AI agent tool often nicknamed "Lobster." Event observations revealed a diverse, intergenerational audience—from 05ers to 70-year-olds—flocking to these gatherings. Participants were polarized: some were already monetizing OpenClaw, while others struggled with basic setup. A key insight was that AI's primary impact is not necessarily job replacement but a massive restructuring of work, automating standardized tasks and creating new roles, particularly for those who can effectively manage AI agents. Interestingly, fields like programming and creative work are now seen as more vulnerable to AI disruption than manual labor. Despite OpenClaw's founder cautioning against crypto, a strong convergence between AI agents and cryptocurrency was debated on-site. Many believe crypto assets, especially Bitcoin, could become the native currency for AI economies, facilitating machine-to-machine transactions and value exchange. The trend also spawned a paid installation service industry. However, a significant hurdle remains: many users successfully install OpenClaw but lack the knowledge to use it effectively, sometimes leading to unexpected costs and security concerns. The conclusion emphasizes that simply having the tool is less important than practically applying it to solve real problems, cautioning against FOMO and highlighting that in the age of AI, early adoption doesn't guarantee success.

marsbit03/07 03:14

After OpenClaw's China Tour, We Interviewed a Group of 'Lobster Chasers'