本文来自PRO会员通讯内容，文末关注「机器之心PRO会员」，查看更多专题解读。 Agent 创企 Sierra 创始人、Salesforce 前联席 CEO、OpenAI 董事会主席 Bret Taylor 近日参与 Lenny's Podcast 的访谈，他以「大模型创业已死路一条，除非你能像马 斯克那样砸几十亿美元」的结论为起点，探讨了创业者在当前 AI 浪潮中应如何精准定位，找到真正属于自己的机会。 目录 01. 基础模型是创业死路，「长尾 Agent 公司」才是机会？ Bret Taylor 为何称「应用 AI」才是创业者的生路？「长尾 Agent 公司」将如何取代传统 SaaS？... 为什么对开发者最友善的Python 反而成为AI的瓶颈？什么是 AI 编程的新范式？... 01 基础模型是创业死路，「长尾 Agent 公司」才是机会？ 1、Bret Taylor 的履历贯穿了过往二十年的科技浪潮。在近期的访谈中，他复盘了自身以往的成功和失败的经历，并在此基础上以创业者的身份剖析了当前 AI 时代的机会，即 真正的蓝海在于能交付业务成果的 Agent，商业模式的核心将是「按成果付费」，而传统的市场 ...

"我当时并不在场，我是后来被叫去调解的。"Bret Taylor 回忆起那次 OpenAI 的"逼宫"危机时说道。 "能参与拯救这样一家从非营利研究实验室走出来的、却抓住全球关注的机构，是非常值得做的是一件 事。"Taylor 表示。 Taylor 身上的标签非常多：助理产品经理、集成电路产品经理、工程师、首席产品官，以及三家企业的 联合首席技术官，其中还包括一家上市公司。他的履历十分丰富： Taylor 曾担任 Salesforce 公司联席 CEO，同时也担任过 Salesforce 首席产品官（CPO）与首席运营官 （COO）。他加入谷歌时担任的是助理产品经理，用周末时间开发出了谷歌地图。现在他是 OpenAI 的 董事会主席，还曾担任过 Twitter 的董事会主席。 Taylor 曾创立三家公司，一家社交网络公司、一家名叫 Quip 的生产力文档服务商，还有现在的 Sierra （去年 10 月，路透社报该公司年营收已超过 2000 万美元）。他还为 Friend Feed 发明了点赞按钮、新 闻推送功能等。 当初 OpenAI 遭遇危机之时，Taylor 原本并不打算再参与 OpenAI 的董事会 ...

Core Viewpoint - The article discusses the complexities and dynamics within OpenAI, particularly during a crisis involving the board and the return of Sam Altman, highlighting the importance of leadership and decision-making in the tech industry [2][3][4]. Group 1: OpenAI Crisis and Leadership - Bret Taylor, a key figure in OpenAI's board, was initially reluctant to get involved but felt compelled to help after reflecting on the significance of OpenAI's impact on the AI landscape [2][3]. - Taylor emphasized the need for a transparent and fair process to address the crisis, aiming to restore trust among employees and stakeholders [3][4]. - The crisis led to a collective employee response, with a public letter demanding Sam Altman's return, indicating the strong connection between leadership and employee morale [3][4]. Group 2: AI Market Dynamics - The AI market is expected to evolve into three main segments: foundational models, AI tools, and application-based AI, with a particular focus on the potential of AI agents [5][33]. - Foundational models will likely be dominated by a few large companies due to the high capital requirements for training these models, making it a challenging area for startups [34][35]. - The AI tools market presents risks as larger infrastructure providers may introduce competing products, necessitating careful strategic planning for smaller companies [36][37]. Group 3: Application-Based AI and Business Models - The application-based AI market is seen as the most promising, with companies developing AI agents to handle specific business tasks, leading to higher profit margins [37][38]. - The shift towards AI agents represents a significant change in how software is perceived, moving from tools that assist humans to systems that can autonomously complete tasks [41][42]. - The concept of "outcome-based pricing" is gaining traction, where companies charge based on the results delivered by AI agents, aligning business goals with customer satisfaction [44][46].

Group 1 - The AI market will evolve into three main segments: models, tools, and applications, with new startups in the model market facing significant challenges unless they can secure substantial funding [4][11][12] - The transition from Google Yellow Pages to Google Maps illustrates that creating entirely new experiences is more valuable than merely digitizing past experiences [4][56] - Agent technology will become a primary form of AI products, offering measurable productivity improvements for businesses, similar to SaaS models, which may yield higher profit margins [4][18][21] Group 2 - AI products should be priced based on results rather than token usage, aligning the goals of both suppliers and customers [4][29][31] - Current AI programming tools often hinder productivity due to a lack of context, necessitating a focus on root cause analysis to improve outcomes [4][33][35] - The programming landscape may require a new system that better accommodates AI capabilities, moving beyond traditional languages like Python [4][42][45] Group 3 - Successful market strategies for AI companies should align with product types, emphasizing the importance of direct sales in many cases [4][47][51] - The evolution of Google Maps from a failed local search product highlights the necessity of differentiating new products by addressing the question of why customers should use them [4][56][58]

Core Insights - Bret Taylor, Chairman of OpenAI and founder of Sierra, shared insights on the future of the AI industry and practical advice for entrepreneurs during a 90-minute interview [1] Group 1: AI Market Segmentation - Taylor identified three main segments of the AI market: frontier model market, tools layer market, and application-based AI market [2] - The frontier model market will be dominated by a few super-scale companies and large labs, making it difficult for startups to compete [2] - The application-based AI market, particularly in the Agent domain, is expected to become a primary form of AI products due to its high automation and measurable results [2] Group 2: Importance of Agents - Taylor emphasized the significance of Agents in enhancing customer experience and service efficiency, promoting a results-oriented billing model that aligns supply and demand [2] - Sierra's AI Agents have been successfully applied in various fields such as customer service, legal review, and content marketing, demonstrating substantial commercial value [2] Group 3: AI Programming and Development - Taylor noted that while AI will take on much of the software development work, human roles will shift to operating code generation machines, requiring a deep understanding of technology and business [3] - He suggested that existing programming languages like Python may not suit AI's needs, advocating for a new programming system tailored for complex systems and flexibility [3] - Entrepreneurs should not wait for foundational model advancements but should proactively design engineering solutions to realize AI's potential [3] Group 4: Product Design and Market Strategy - Taylor shared experiences from Google Maps development, highlighting the importance of creating new user experiences rather than merely digitizing existing models [3] - He advised entrepreneurs to choose appropriate market entry strategies based on product types, emphasizing the importance of direct sales to effectively reach and serve large enterprise clients [3] Group 5: AI's Impact on Education - Taylor believes AI tools like ChatGPT will promote educational equity by providing personalized tutoring for every child [3] - He cautioned parents and educators to focus on fostering children's initiative and encouraging constructive use of AI tools [3] Group 6: Entrepreneurial Insights - Taylor's insights provide valuable guidance for entrepreneurs in the AI era, emphasizing the need to stay abreast of technological trends while deeply understanding business needs [5] - Innovation and engineering design are crucial for realizing AI's potential, alongside addressing social issues like educational equity [5]

Core Viewpoint - The current era is likened to a "10x speed internet bubble" driven by AI, presenting a golden opportunity for startups to challenge established giants [3][31]. Group 1: AI and Startup Opportunities - AI is creating a transformative environment similar to the advent of personal computers and the internet, allowing startups to emerge and thrive [3][15]. - The emergence of large language models represents a fundamental technological breakthrough that can reshape the economic landscape, providing startups with the chance to disrupt established players [15][32]. - The current market dynamics are characterized by explosive growth, with AI companies rapidly evolving and generating significant revenue [34][35]. Group 2: Entrepreneurial Insights - Many B2B companies' claims of being "customer-centric" are often misleading; true value is determined by financial metrics rather than superficial claims [3][21]. - Entrepreneurs should focus on understanding real customer needs rather than merely developing technology for its own sake [20][21]. - A core thesis is essential for startups; without a clear vision, it becomes challenging to interpret customer feedback and market signals [28][30]. Group 3: AI Market Segmentation - The AI market can be divided into three segments: frontier models, AI tools, and applied AI companies, each with distinct opportunities and challenges [36][38]. - Applied AI companies should avoid the costly mistake of pre-training models from scratch, as existing solutions are often more efficient and cost-effective [42]. - The future of AI development will likely involve a clear division of labor, with research focusing on foundational models and application development concentrating on building intelligent agents [42][43]. Group 4: Future of Software Development - The industry is in search of a new "LAMP" stack for AI development, similar to the foundational technologies that emerged for web development [44][47]. - The evolution of AI tools and systems will lead to more accessible and efficient development processes, akin to the advancements seen in web technologies [45][46]. Group 5: Vision and Impact - The driving force behind innovation is the desire to influence the world positively, rather than merely pursuing financial gain [48]. - The current technological revolution is seen as an opportunity to shape the future, with the potential for AI to significantly lower the cost of intelligence [49][50].

Core Viewpoint - Mazda is set to launch the upgraded SUV "CX-5" in Europe by the end of 2025, followed by releases in Japan and the United States in 2026, aiming to enhance revenue amid challenging market conditions due to automotive tariffs [1][2][3]. Group 1: Product Features - The new CX-5 measures 4.69 meters in length and 1.86 meters in width, comparable to Toyota's RAV4 and Honda's CR-V [3]. - The vehicle will feature a touch screen display and will be the first Mazda model to incorporate Google's automotive services, including Google Assistant and Google Maps [1][2]. - A new 4-cylinder engine and hybrid system are planned for release by 2027, designed to meet new emissions regulations in Europe and the U.S. while providing high environmental performance and driving capabilities [3]. Group 2: Market Context - The U.S. automotive tariffs are creating a challenging business environment, prompting Mazda to focus on its key model, the CX-5, to improve sales performance [3]. - The CX-5 has historically been a strong performer, accounting for nearly 30% of Mazda's global sales in 2024, indicating its significance to the company's overall strategy [3].

Core Insights - Gaode Map has emerged as a significant player in the transportation service industry, ranking first in the traffic scale among top 10 applications as of March 2025, surpassing competitors like Baidu Map and Didi Chuxing [1][3] - The company has achieved profitability for the first time, a notable milestone in the competitive landscape of map services, where even leading platforms like Google Maps struggle with monetization [1][2] Group 1: User Base and Market Position - As of March 2025, Gaode Map boasts 873 million monthly active users, positioning it as the fourth largest application in China's mobile internet landscape, following WeChat, Taobao, and Alipay [3] - Despite its large user base, Gaode Map faces challenges in monetization due to the inherent nature of navigation tools, which require significant investment in technology and marketing to realize their commercial potential [4][7] Group 2: Business Strategy and Monetization - Gaode Map is transitioning from a navigation tool to a comprehensive lifestyle service platform, integrating various services such as instant delivery and commercial authorization fees to enhance revenue streams [4][6] - The company has implemented a tiered pricing model for its commercial services, with the advanced version priced at 100,000 yuan, indicating a strategic move towards diversified revenue generation [4] Group 3: Competitive Landscape - Gaode Map's competitive position is complicated by its role within Alibaba's ecosystem, where it serves as a traffic conduit rather than an independent service platform, limiting its strategic autonomy [8][12] - The competitive environment is intensifying, with platforms like Douyin and Meituan encroaching on Gaode Map's market share by integrating their services into navigation functionalities [8][9] Group 4: International Expansion and Challenges - Gaode Map's international efforts are constrained by its alignment with Alibaba's broader strategy, which may limit its ability to adapt to local market conditions effectively [9][12] - In contrast, Didi Chuxing has successfully expanded its international operations, demonstrating a more autonomous approach that has led to profitability in overseas markets [11][12]

Core Viewpoint - Over-reliance on AI tools like ChatGPT can significantly reduce brain activity levels, impair memory, and lead to "cognitive inertia" [1][25][28] Group 1: Research Findings - A recent MIT study utilized EEG, NLP analysis, and behavioral science to confirm the negative cognitive impacts of AI tools [3][25] - The study involved 54 college students divided into three groups: LLM group (using OpenAI GPT-4o), search engine group (using Google without LLM), and pure brain group (no tools) [11][13] - Results indicated that the pure brain group exhibited the strongest neural connections, indicating higher cognitive load and deeper thinking [17][20] Group 2: Cognitive Effects - Participants relying on LLM showed the weakest neural connections and significantly reduced independent thinking [18][25] - Over-reliance on LLM led to shallow memory encoding, with 83.3% of LLM users unable to accurately recall their papers [21] - In contrast, only 11.1% of pure brain users faced similar recall issues, although they took longer to write [22] Group 3: Long-term Implications - The study suggests that long-term dependence on LLM alters brain information processing from "actively generating information" to "passively filtering information," weakening independent thought and problem-solving skills [28][30] - The research team emphasizes the importance of balancing AI tool usage with independent thinking, recommending AI for grammar checks and initial research rather than core content generation [30][31]

Core Insights - The article emphasizes that linear effort does not guarantee linear returns, and that success is more about the right choices, talent, and passion rather than just time spent [1][2][5] - It highlights the concept of superlinear returns in entrepreneurship, investment, and technology, where a few winners dominate the market due to exponential growth and threshold effects [6][8][15] Group 1: Key Concepts - Warren Buffett critiques the "10,000-hour rule," suggesting that time investment alone is insufficient for success; the right direction and personal interest are crucial [2][5] - The article discusses the difference between linear returns (simple accumulation of effort) and compound returns (exponential growth), emphasizing that without inherent talent, repeated effort may not lead to significant breakthroughs [5][6] - Paul Graham's insights on superlinear returns reveal that performance is not always proportional to effort, as seen in competitive markets where only the best products succeed [6][8][10] Group 2: Strategies for Nonlinear Success - The article outlines strategies for achieving nonlinear success through linear efforts, such as deliberate practice, establishing positive feedback loops, and leveraging technology [29][30][34] - It provides examples like Google Maps and Amazon, where initial linear efforts led to significant competitive advantages once critical thresholds were reached [19][24] - The importance of identifying strategic inflection points and high-leverage activities is emphasized, as these can lead to exponential growth opportunities [33][34] Group 3: Implications for Individuals and Companies - Individuals are encouraged to focus on areas of passion and expertise while seeking opportunities that can yield exponential returns [25][37] - The article warns against the dangers of blind linear effort without strategic thinking, suggesting that success in the modern economy requires a mindset that seeks to integrate efforts into systems with nonlinear potential [39][36]