# Workplace İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Workplace" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

Those Who Use AI to 'Quickly Finish the Job' Are Ruining the Workplace

Some people are using AI tools to quickly produce superficially complete work, like reports, proposals, or performance reviews, just to "check a box." This results in "Workslop" – workplace AI output that looks polished but lacks factual verification, professional judgment, and real value. The core problem is the shifting of work costs: while the generator saves time, the receiver must spend hours verifying information, correcting errors, and deciphering vague conclusions. This undermines team efficiency and trust. Examples include a manager using AI for vague, unactionable employee feedback, an analyst generating weekly reports with misleading AI-interpreted data, and a team producing extensive project documents with no one able to justify the underlying assumptions. The issue isn't AI itself, but how it's used. It amplifies existing work habits. Responsible users treat AI as an assistant for drafting and organizing, then add firsthand verification and judgment. Those merely looking to "hand in" work delegate responsibility to the AI and their colleagues. Ultimately, the value of work should be judged not by its speed or polish, but by whether it provides new facts, clear judgments, and an accountable owner. AI cannot understand context, make critical decisions, or bear the consequences – those remain irreplaceably human responsibilities.

marsbit07/29 08:11

Those Who Use AI to 'Quickly Finish the Job' Are Ruining the Workplace

marsbit07/29 08:11

From Return to Resignation: Chen Hang's 437 Days at DingTalk

The 437-Day Return and Departure of Chen Hang at DingTalk This article chronicles the 437-day period from March 31, 2025, to June 11, 2026, when Chen Hang (also known as "No Move") returned as CEO of DingTalk, the enterprise communication platform he originally founded, only to later step down. Chen Hang, the creator of DingTalk in 2015, was brought back by Alibaba in 2025 after the company acquired his subsequent startup, HHO. His return was driven by Alibaba's renewed focus on AI and DingTalk's strategic role as its key to-B AI application. However, his aggressive management style, marked by strict work policies like mandatory clock-ins and extended hours, quickly caused internal friction and was criticized as being at odds with Alibaba's culture. Despite the internal turmoil, Chen Hang drove significant product launches. In August 2025, he unveiled "AI DingTalk 1.0," featuring new products like the AI-native entry point "DingTalk ONE." By March 2026, he announced "Wukong," touted as the world's first enterprise-grade AI-native work platform, representing a fundamental rebuild of DingTalk's architecture. The turning point came in early June 2026. A detailed internal post criticizing DingTalk's work culture went viral, followed by a public critique from a former executive. This prompted an unprecedented public rebuke from the Alibaba Partners Committee, which stated such management was not aligned with company values. One day later, on June 11, Alibaba announced Chen Hang's departure. He was succeeded by Chen Yusen, a 32-year-old technical expert known for founding cybersecurity firm Changting Technology. While Chen Hang's tenure laid the technical foundation for DingTalk's AI transformation with "Wukong," his leadership style ultimately led to his replacement as the company seeks a new direction under younger leadership.

marsbit06/11 10:23

From Return to Resignation: Chen Hang's 437 Days at DingTalk

marsbit06/11 10:23

Is AI Creating a New Class of 'Information Poor'?

AI is generating a new kind of "information poverty." The core issue isn't that AI denies answers to the poor; it's that it provides abundant, cheap, and plausible-sounding answers to everyone. This availability shifts the true scarcity from obtaining answers to possessing the **judgment to evaluate them** and the access to turn them into real-world opportunities. New information poverty thus describes those who have AI tools and outputs, but lack the complementary skills, authorization, and contextual experience to critically assess and act on them. Research reveals a multi-layered divide: access to AI is stratified by income and platform design (e.g., premium vs. free, embedded tools). In workplaces, usage heavily favors higher-paid, more experienced, or formally trained employees, with AI often automating entry-level tasks that were traditional stepping stones. Crucially, the heaviest users are often mid-career professionals whose existing expertise allows them to effectively judge and leverage AI outputs, while novices risk over-relying on them without building judgment. While controlled experiments show AI can significantly boost low-skilled workers' performance, real-world adoption and benefit are constrained by unequal social and organizational structures. Historically, general-purpose technologies first reward those with existing complementary capital. AI, by affecting judgment-based work, may accelerate and deepen this initial inequality gap, even if it narrows over decades. The danger lies in the illusion of competence it creates, potentially stunting the very critical thinking needed in an era where judgment is paramount.

marsbit06/08 11:38

Is AI Creating a New Class of 'Information Poor'?

marsbit06/08 11:38

Interview with 7 Ordinary Professionals: After AI Arrived, How Are You Doing?

This article interviews seven professionals from diverse fields like Web3, bulk chemical trading, digital agriculture, and traditional wholesale to examine the impact of AI on their work. Key themes emerge from the discussions. AI has become integral to their workflows, primarily for increasing efficiency in tasks such as coding, content creation, research, and data analysis. Individuals across roles, from developers to managers, report that AI tools like ChatGPT and Claude have significantly reduced workloads and accelerated learning, creating opportunities for "super individuals" or one-person teams. However, this efficiency comes with a double-edged sword. It intensifies competition, pushing professionals to constantly learn new tools and adapt, leading to widespread anxiety about job security and a heightened pressure to keep pace. Interviewees anticipate significant job reductions in roles like administrative support, finance, HR, customer service, and some creative fields. A recurring view is that AI acts as a "great equalizer," amplifying the capabilities of those who use it effectively while leaving others behind, potentially deepening polarization. Despite AI's capabilities, interviewees identify enduring human strengths. AI struggles with tasks requiring deep contextual understanding, complex judgment in areas like risk assessment and system stability (especially in finance/Web3), nuanced human communication, and handling exceptions in logistics and manufacturing. These areas remain firmly in the human domain. Consequently, many professionals are refocusing their career strategies. They plan to evolve from task executors into "complex system owners," "super coordinators" managing AI agents, or specialists in high-level areas like business context, risk control, product design, and personal branding. In summary, the article portrays AI not as an optional tool but as a transformative force reshaping job demands. While it automates routine work, it also creates new forms of pressure and competition. The future, as seen by these professionals, belongs to those who can strategically integrate AI to augment uniquely human skills like judgment, responsibility, and strategic oversight.

marsbit06/01 08:17

Interview with 7 Ordinary Professionals: After AI Arrived, How Are You Doing?

marsbit06/01 08:17

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

What Is the Web3 Workplace Really Like? A Sample Observation from a Leading Exchange

Based on interviews and data from leading crypto exchange Gate, this article explores the realities of working in Web3, countering common stereotypes of instability and high pressure. A key feature is remote work, embraced by over 66% of Web3 companies. While offering flexibility, it can create isolation and make vetting companies difficult, driving talent toward established firms like Gate, which has a 13-year history and global regulatory licenses. This provides a sense of security absent in newer projects. The workforce is highly educated (89% hold bachelor's degrees or higher) and global. Talent is attracted by growth potential, learning opportunities, and the ability to have a global impact. Compensation, while not always exceeding top tech firms, offers geographic arbitrage—earning a competitive salary while living in a lower-cost region. Performance-based incentives are central. At Gate, year-end bonuses range from 2-6 months' salary, with top performers receiving up to 20 months' pay. The culture emphasizes "high effort, high reward," not just long hours. Work intensity is high due to the 24/7 nature of crypto, but the flexibility of remote work and a results-oriented model prevent a pure "996" culture. The article concludes that while Web3 has its challenges, it offers unique opportunities for growth and flexibility. It advises against relying on polarized external narratives and encourages firsthand experience to understand the real Web3 workplace.

Odaily星球日报03/02 11:08

What Is the Web3 Workplace Really Like? A Sample Observation from a Leading Exchange

Odaily星球日报03/02 11:08

The Stronger AI Gets, The More Tired People Become: 'Anxiety' Becomes the Norm for Companies and Employees

Amidst promises of liberation, AI coding tools like Claude Code and Codex are instead fueling widespread workplace anxiety and a "productivity obsession." While over 40% of C-suite executives claim AI saves them at least 8 hours weekly, 67% of non-managerial staff report saving less than two hours—or none. Studies reveal that even as AI handles more tasks, working hours are increasing. This anxiety is top-down: executives like Intuit’s CTO code at 5 a.m. with AI, while CEOs monitor usage bills to gauge effort. Employees face量化管理, tracked on daily AI interactions, leading to burnout and "AI fatigue." The gap between leadership’s staff experience is stark, with executives enjoying hands-on prototyping while employees bear转型成本 and job insecurity. Researchers note "task expansion" – non-technical staff generate code, but engineers clean up, increasing workloads. The risk? A surge in "busyware": low-value projects that consume resources but add little. True efficiency may lie not in building more, but in questioning what shouldn’t be built at all.

marsbit03/02 02:04

The Stronger AI Gets, The More Tired People Become: 'Anxiety' Becomes the Norm for Companies and Employees

marsbit03/02 02:04

Anthropic Just Released an "AI Job Disruption Report": The Higher the Education, the More "Disrupted"

Anthropic's latest "Economic Index Report" reveals a counterintuitive finding: AI accelerates work most dramatically in complex, high-skill tasks. While AI boosts speed by 9x for high-school-level tasks, this jumps to 12x for college-level work, indicating that knowledge-intensive roles are most impacted. The report highlights a critical shift towards "deskilling," where AI handles the analytical core of jobs, potentially leaving humans with diminished, routine tasks. However, effective human-AI collaboration extends AI's effective task horizon from 2 hours to 19 hours, showcasing a 10x improvement in handling complex projects. Globally, a divide exists: wealthier nations use AI for productivity enhancement, while poorer regions primarily use it for education. Anthropic forecasts AI could drive 1.0-1.2% annual US productivity growth, echoing 1990s tech boom levels. The key takeaway is that the future belongs not to those replaced by AI, but to those who master defining problems and collaborating with it.

marsbit01/16 11:17