# Management Articoli collegati

Il Centro Notizie HTX fornisce gli articoli più recenti e le analisi più approfondite su "Management", coprendo tendenze di mercato, aggiornamenti sui progetti, sviluppi tecnologici e politiche normative nel settore crypto.

85% of concentrated liquidity is underutilized — Meaning for DeFi?

A recent Dune report reveals that concentrated liquidity, designed to enhance capital efficiency in decentralized exchanges, is largely underutilized. In the first half of 2026, an average of 29.4% of liquidity across major protocols like Uniswap v3/v4, PancakeSwap v3, and Aerodrome Slipstream was idle—outside active trading ranges—resulting in no fee generation. This represents about $542 million in idle capital weekly and an estimated $150 million in lost annual fees for LPs. When considering technically available but unused liquidity, the underutilization rate rises to approximately 85%. The study indicates that much of this idle capital, particularly over $200 million untouched for more than 90 days, stems from liquidity providers not actively managing their positions. Individual investors, not automated managers, hold the vast majority of this idle liquidity (e.g., 94% on Ethereum). Automated managers maintain far more active and in-range positions. Notably, Uniswap v4 has not resolved the issue; about 30.5% of its liquidity remains out of range, and while it introduced hooks for external yield strategies, only 10% of its TVL uses them, with none currently generating yield from idle capital.

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85% of concentrated liquidity is underutilized — Meaning for DeFi?

ambcrypto10 h fa

Father of Claude Code's Latest Assessment: Team Division of Labor Rewritten in the AI Era, These 'Five Types' Are Most in Demand

"In the era of AI reshaping software development, Anthropic's Claude Code team lead, Boris Cherny, proposes a future where traditional job titles dissolve. He identifies five fluid, behavior-based roles emerging in effective, AI-augmented teams: The Prototyper (generates disruptive ideas), The Builder (scales prototypes to production), The Sweeper (streamlines and refactors to combat bloat), The Growth (iterates on launched products for market fit), and The Maintainer (ensures long-term security and reliability). Crucially, these are not fixed positions. Individuals may span multiple roles depending on the project and its lifecycle stage. A designer might be a Prototyper and Sweeper; an engineer could be a Builder and Maintainer. Team composition should shift with product maturity: early-stage products need Prototypers, Builders, and Sweepers, while scaling products require more Builders, Growth roles, and Maintainers. The discussion highlights that role fluidity is key, as professionals often switch roles across different projects or as a single project evolves. While AI tools like Claude increasingly assist with tasks like building and sweeping, human adaptability and focus on goals over rigid job boundaries are seen as essential for future teams."

marsbit06/30 05:53

Father of Claude Code's Latest Assessment: Team Division of Labor Rewritten in the AI Era, These 'Five Types' Are Most in Demand

marsbit06/30 05:53

Managing a Company Valued at Nearly a Trillion Dollars, Anthropic's CEO Has Only One Direct Report

Anthropic CEO Dario Amodei has only one direct report, his chief of staff, in a stark departure from the tech industry trend of CEOs managing many direct reports. Company executives instead report to President Daniela Amodei, Dario's sister, who handles daily operations. This structure allows Dario, a researcher by background, to focus his time on long-term strategy, research direction, and cultivating company culture, which he sees as critical as Anthropic grows rapidly and hires from larger tech firms. He spends significant time on company-wide meetings and writing about AI's societal impact. Harvard professor Raffaella Sadun suggests such a narrow span of control is suitable for companies like Anthropic that face novel, high-stakes problems requiring top-level judgment, as it protects the CEO's time as the scarcest resource.

marsbit06/12 05:11

Managing a Company Valued at Nearly a Trillion Dollars, Anthropic's CEO Has Only One Direct Report

marsbit06/12 05:11

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

After Burning Tens of Billions of Dollars in Tokens, Silicon Valley Giants Start Limiting Employee Token Usage

After burning tens of billions of dollars on AI tokens, major Silicon Valley firms are now restricting employee usage. Companies like Microsoft, Uber, and Salesforce, which heavily promoted AI for "efficiency," are facing a cost crisis. The practice of "tokenmaxxing"—pushing employees to maximize AI tool usage—led to wasteful spending on trivial tasks like checking the weather or writing birthday messages, with studies showing significant hidden costs for bug fixes and code rewrites. The core issue is a misalignment between individual productivity gains and actual business value. While employees use AI to automate tasks they dislike, such as writing reports, this often doesn't translate to increased company revenue or improved core business outcomes. For instance, AI-generated code speeds up development but also sees an 800% increase in "code churn" (code being discarded or rewritten). As a result, only 14% of CFOs report seeing a clear, measurable return on AI investments. Firms are now shifting strategies. Microsoft has revoked most internal licenses for Claude Code, while others are implementing monitoring and cost controls. New tools from companies like Harness and CloudZero aim to track AI spending and tie costs to business results. Some AI vendors, like HubSpot, are moving from token-based pricing to charging based on outcomes, such as "resolved conversations" or "leads generated." This represents a necessary correction in the AI adoption cycle. The challenge now is for companies to move beyond using AI merely to speed up old tasks and instead rethink their workflows and business models fundamentally. The future of enterprise AI depends on proving its value, not just its usage.

marsbit06/01 04:06

After Burning Tens of Billions of Dollars in Tokens, Silicon Valley Giants Start Limiting Employee Token Usage

marsbit06/01 04:06

GitHub Empire on the Brink of Collapse: Source Code Leak, 18-Year Veteran Leaves, Microsoft Loses 1.5 Billion Developers

GitHub is facing an unprecedented crisis, marked by a massive exodus of developers and severe operational failures. The tipping point came when Mitchell Hashimoto, creator of Ghostty and an 18-year GitHub user, publicly severed ties, citing persistent platform outages that made serious work impossible. This departure highlights a broader pattern of user frustration. The platform's instability has drawn complaints from major corporate clients like Citibank and Intel, forcing Microsoft to issue substantial service credits. A critical incident last month saw an accidentally triggered, unreleased feature cause widespread repository rollbacks, erasing recent code changes and pushing enterprises to migrate. Security has catastrophically breached. In May 2026, hackers infiltrated over 3,800 of GitHub's internal repositories via a poisoned VS Code extension installed by a developer, leading to the attempted sale of core source code for $50,000. This follows the discovery of a critical zero-day vulnerability in March that threatened access to millions of repositories. Internally, GitHub's autonomy has collapsed. After the resignation of CEO Thomas Dohmke in mid-2025, Microsoft eliminated the CEO role, folding GitHub into its CoreAI division under the unpopular leadership of Jay Parikh. This triggered a talent drain, with key executives and engineers leaving. A disruptive migration of GitHub's infrastructure to Azure servers, pushed by CTO Vladimir Fedorov, is blamed for the recurring outages. Competitively, GitHub Copilot is under "existential threat" from superior AI coding tools like Cursor (now owned by SpaceX) and Claude Code, which offer more advanced contextual coding and automation. Ironically, Microsoft's own engineers reportedly preferred Claude Code, forcing management to revoke licenses. Financially, GitHub is a loss leader. Despite Copilot surpassing 4.7 million paid users and $3 billion in annual revenue, the AI inference costs for free services massively outstrip subscription income, hurting Microsoft's cloud margins. The recent shift from a flat fee to a pay-as-you-go model for Copilot has further alienated developers. The core question for Microsoft is whether a centralized code repository remains essential in the AI agent era. The erosion of trust, developer culture, and platform reliability threatens the very ecosystem Microsoft spent decades building.

marsbit05/22 10:52

GitHub Empire on the Brink of Collapse: Source Code Leak, 18-Year Veteran Leaves, Microsoft Loses 1.5 Billion Developers

marsbit05/22 10:52

Cloudflare CEO: How I Decided Which Employees to Replace with AI?

Cloudflare CEO Matthew Prince explains his decision to lay off over 20% of the company's staff, despite record-high growth and revenue. He frames this as a necessary adaptation to AI-driven business transformation, drawing on Peter Drucker's framework of three corporate roles: builders, sellers, and measurers. Prince argues AI primarily targets "measurers"—roles in auditing, finance, legal, compliance, middle management, and operations. AI systems can perform these measuring and oversight tasks with superior objectivity, efficiency, and scale, enabling continuous auditing and faster financial processes. This allows for consolidation and automation in these areas. Conversely, "builders" (e.g., engineers) and "sellers" are seen as secure and even more valuable. AI amplifies their productivity, and human relationships remain crucial for sales. The layoffs were not merely cost-cutting but a reallocation of resources to hire more builders and sellers. Prince highlights the company's record number of open roles and its highly AI-native intern class, who are primarily builders and sellers. He concludes that AI will reshape every company by enhancing measurement capabilities, allowing human talent to focus on creating and capturing value through building and selling.

marsbit05/22 02:26

Cloudflare CEO: How I Decided Which Employees to Replace with AI?

marsbit05/22 02:26

Tiger Research: On-Chain Risk Operators, The Market Cap Gap Between 147 Trillion and 70 Billion

This report by Tiger Research examines the evolution of risk management in decentralized finance (DeFi) lending. It highlights a power shift from protocol developers to specialized professional risk operators who manage on-chain capital. The era of protocols and community governance solely dictating DeFi lending is ending. A new professional asset management layer has emerged. While the sector is nascent, capital and distribution channels are rapidly consolidating around top risk operator teams, whose past performance is now a key criterion for institutional entry. The industry's development, accelerated by modular infrastructures like Morpho, has led to a clear division of labor mirroring traditional finance: distribution channels (e.g., exchanges), strategy/risk management (the risk operators), and product infrastructure/asset custody (smart contract protocols). This structure lowers the entry barrier for traditional institutions. Currently, the total value managed by risk operators is approximately $70 billion, dominated by a few leading teams like Steakhouse (RWA focus), Sentora (AI models), and Gauntlet (crisis management). Competition now centers on collateral standards, distribution access, and crisis response capabilities. The report outlines three primary entry paths for institutions: 1) **Distribution Model**: Leveraging external risk operators as backend service providers (common for exchanges). 2) **Asset Supply Model**: Onboarding real-world assets to DeFi as collateral. 3) **Independent Operator Model**: Building an in-house team to become a risk operator (e.g., Bitwise). The core opportunity lies in the strategy/risk management layer, where traditional financial institutions can leverage their existing expertise in due diligence and risk assessment without deep technical development. A vast opportunity gap exists: the global traditional asset management industry manages ~$147 trillion, while the entire DeFi sector is only ~$800 billion, with the risk operator niche at ~$70 billion. This disparity signifies immense growth potential. Once robust risk frameworks and clearer regulations are established, even a minor allocation from traditional markets could trigger exponential DeFi growth. Early movers who help build these foundational systems will gain significant rule-setting influence and first-mover advantages.

marsbit05/20 07:40

Tiger Research: On-Chain Risk Operators, The Market Cap Gap Between 147 Trillion and 70 Billion

marsbit05/20 07:40

YC Partner: How to Build a Self-Evolving AI-Native Company

YC Partner Tom Blomfield argues that the future lies in building AI-native companies designed as self-evolving systems, not just applying AI to traditional, hierarchical "Roman legion" structures. The core idea is to extract and codify all organizational knowledge—scattered across emails, Slack, documents, and human minds—into a central, AI-readable "company brain." This enables the creation of recursive AI loops that sense changes (from emails, support tickets, data), make decisions, execute via tools, and learn from feedback, all with minimal human intervention. YC exemplifies this with an agent that monitors failed queries, autonomously diagnoses the issue (e.g., needing a new database or index), writes code, submits it for review, and deploys fixes—optimizing the company while founders sleep. This shift redefines organizational structure: the bottleneck becomes token usage and context quality, not headcount. Middle management for coordination is largely obsolete. The critical human roles are individual contributors (ICs) and those handling high-risk, real-world judgments at the system's edge. Key steps include recording all organizational activity for AI, creating self-improving artifacts (like an AI-generated, living handbook), and treating internal software as temporary and disposable, while preserving valuable business context and data. The fundamental question for founders is whether to build their company as this new type of intelligent, self-optimizing system from the start.

marsbit05/20 06:36

YC Partner: How to Build a Self-Evolving AI-Native Company

marsbit05/20 06:36

Altman Drops Bombshell While Musk is Away: He Once Wanted His Children to Inherit OpenAI

In a California court, Sam Altman testified for the first time in the ongoing legal battle between Elon Musk and OpenAI. Altman made a striking claim: Musk once suggested that control of OpenAI could one day be passed down to his children. This statement reframes the long-standing conflict not as a simple governance dispute but as a foundational power struggle. Altman sought to counter the narrative that OpenAI betrayed its original non-profit, idealistic mission. He argued that from the beginning, it was Musk who sought increasing control over the organization, including a larger equity stake and ultimate decision-making authority. Altman opposed this, citing OpenAI's core principle that AGI should not be controlled by any single individual. He also addressed the key point of contention about OpenAI's shift to a for-profit structure, claiming Musk was aware of and initially supportive of exploring such a model to secure the massive funding needed for advanced AI research. Altman framed the change as a practical necessity, not a betrayal. Further testimony revealed internal concerns after Musk left OpenAI's board, with worries he might take retaliatory action. Altman critiqued Musk's management style as unsuitable for a research lab, damaging morale and culture. Throughout his testimony, Altman's focus appeared to shift from technological idealism to the realities of organizational governance and resource requirements. Regarding his brief ouster in 2023, Altman stated he seriously considered joining Microsoft but ultimately returned because OpenAI was too important to abandon.

marsbit05/13 04:11

Altman Drops Bombshell While Musk is Away: He Once Wanted His Children to Inherit OpenAI

marsbit05/13 04:11

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