"We share EPAM's perspective: the teams that achieve exceptional results are those that rethink how they work, not just the tools they use," said Michael Scherr, Head of Business Development at Cursor. "With EPAM's deep enterprise delivery expertise and clear point of view on AI-Native SDLC, combined with our AI-Native IDE and agents, we're helping global clients scale the unique and transformative potential of Cursor." Combined with EPAM's 50,000+ engineering professionals globally, team-level maturity mod ...

「软件不应再等待被使用，而是在需要它的那一刻才存在。」 这是 Agencize AI 创始人张浩然，对于 AI-Native 时代工作流/软件该如何设计的一种回答。 多年 SaaS/无代码创业的经历，2021 年、2025 年两次登上奇绩创坛的 Demo Day，做了十几年生产力工具的张浩然，对于 AI 工作流有很多自己的想 法。 「我们想解决的不是 『做 AI 工作流』，是『根本不需要有工作流』。 所有要求用户『预先构建工作流』的 Agent 都是错的。 」 在他看来，SaaS 不会因为 Agent 而消亡，但 SaaS 会成为 AI 时代新的基础设施，Agencize AI 会为用户即时生成各类个性化的软件，连接和利用好传 统 SaaS 软件。 在 Agencize AI 产品发布之前，我们和张浩然聊了聊他对于生产力工具和工作流的看法，以及 Agencize AI 的真正竞争力。 产品官网：https://agencize.ai/ 超 19000 人的「AI 产品市集」社群！不错过每一款有价值的 AI 应用。 邀请从业者、开发人员和创业者，飞书扫码加群： 以前做这些事特别麻烦，每天只能手动处理，效率很低。 ...

从集体止血到 AI 碾压，通过这 8 个转折点，看懂 ToB 终局。 曾经，中国 ToB 行业习惯了躲在"默认增长"的幻觉里，以为终局可以被无限期推迟。但 2025 年，最后一块遮羞布被扯掉了。 这一年，有人在纳斯达克敲钟，也有人在破产重整的边缘绝望求生；腾讯不再满足于只做财务投资，而是直接下场接手销售易；当老牌软件公司还在为回 款焦头烂额时，横空出世的 Manus 已经带着 1 亿美元的 ARR 奔向新加坡。 这不是一次温和的迭代，而是一场残酷的"分化与定型"。 资本不再奖励虚无缥缈的"故事"，"活着"从默认状态变成了一种需要拼命证明的能力。只有那些能自我造血、能探索到更多的退出路径选择的企业，才有 继续下注的资格。 以下，是 2025 年中国企业软件行业在血与火中完成的生存复盘。 01 告别"故事溢价"： ToB 开启质量驱动的港股上市潮 这类企业已完成发行，正式挂牌交易，如下 | 企业名称 | 上市日期 | 上市地点/代码 | 发行价 | 募资净额 | 核心亮点/业绩 | | --- | --- | --- | --- | --- | --- | | 一直田 | 2025/8/19 | 纳斯达克(YMT ...

Core Viewpoint - The article discusses the recent strategic shift of Li Auto, indicating a departure from its previous learning from Huawei's management practices, particularly the PBC performance model, towards a new focus on becoming a leading AI terminal company [5][10][12]. Group 1: Strategic Changes - Li Auto has recently made significant organizational changes, including the founder Li Xiang taking over HR responsibilities and several Huawei executives leaving the company [5][6]. - The company is moving away from the PBC performance model and is reintroducing the OKR management system, indicating a shift in management philosophy [5][6]. - The mission of Li Auto has evolved from being a car manufacturer to becoming a global leader in AI terminals, which has necessitated changes in its organizational structure and operational methods [10][12]. Group 2: Learning from Huawei - Initially, Li Auto aimed to learn from Huawei's Integrated Product Development (IPD) model to improve its product definition and management processes, especially after facing competition from the AITO M7 [7][8]. - The IPD model provided a structured approach to product development, ensuring high quality through rigorous checks, but it also introduced inefficiencies due to lengthy decision-making processes [8][9]. - Li Auto's adaptation of the IPD model was seen as a necessary step to stabilize its operations during a period of rapid product launches [8][9]. Group 3: Transition to AI-Native Organization - As the company's mission shifted towards AI, it recognized the need to restructure its organization to be more agile and responsive, moving away from the traditional IPD model [10][11]. - The new structure involves creating smaller, more flexible teams that can iterate quickly, akin to agile development practices in the software industry [11]. - This transformation reflects a broader understanding that the nature of AI development requires a different operational approach compared to traditional hardware manufacturing [10][12].

Core Insights - Youdao, Inc. reported an earnings per share (EPS) of $0.011, surpassing the estimated EPS of -$0.00007 [1][6] - The company achieved a net revenue of approximately $228.8 million in Q3 2025, exceeding estimates and reflecting a 3.6% year-over-year increase [2][6] - Youdao's strategic investments in Youdao Lingshi and online marketing services have driven significant growth, with online marketing services seeing a 51.1% year-over-year increase in net revenues [3][6] Financial Performance - The operating profit for the first three quarters of 2025 grew nearly 150% year-over-year, attributed to the "AI-Native" strategy [2] - Youdao Lingshi experienced over 40% year-over-year growth in gross billings [3] - The company's price-to-earnings (P/E) ratio is approximately 33.83, and the price-to-sales ratio stands at about 1.37 [4] Financial Structure - Youdao has a negative debt-to-equity ratio of -0.89, indicating a unique financial structure, yet has maintained profitability for five consecutive quarters [5] - The current ratio of 0.55 reflects the company's ability to cover its short-term liabilities with its short-term assets [5]

Core Insights - Cursor has achieved over $100 million in annual revenue within two years without a traditional sales team, showcasing a significant shift in productivity paradigms in the AI programming tool industry [1] - The company is recognized as a model of "AI-Native" organizations, emphasizing a complete restructuring for the AI era rather than merely adopting existing tools [1][27] Section 1: AI-Native Product Entry - Unlike most AI programming teams that focus on building large models or platforms, Cursor started by creating a complete code editor (IDE) from scratch [4][6] - The decision to build a new IDE was based on the belief that a significantly better tool could persuade engineers to switch from their established environments [6][8] - Cursor's strategy focused on creating a core interface that engineers would use frequently, rather than trying to cover all possible paths from the start [7][8] Section 2: AI-Native Organizational Development - Cursor prioritized recruitment over assembling a full team after funding, dedicating significant time to developing a hiring system [13][15] - The company actively sought out potential hires rather than waiting for applications, employing creative strategies to engage candidates [16][18] - A unique hiring mechanism involved a two-day trial period for candidates to work on real projects, allowing both the company and the candidates to assess fit [20][22] Section 3: AI-Native Technical Path - Cursor's technical approach focused on utilizing external APIs instead of developing their own models initially, aiming to deliver a usable product quickly [23][25] - The company believed that gathering user data through real-world application would inform future model development, rather than starting with model training [25][26] - Cursor successfully launched its internal model, Composer, after three years of building a user base and collecting data, demonstrating the effectiveness of its reverse modeling approach [26] Conclusion - Cursor's success is attributed to its focus on organizational structure as the foundation for AI product development, rather than solely on technological advancements [27][28] - The company exemplifies that the true competitive edge in the AI-native space lies in organizational reconstruction rather than just technical upgrades [29]

Group 1 - The core theme of the 2025 "The State of AI" report by ICONIQ Capital focuses on how to effectively build and scale AI products, transitioning from the question of whether to adopt AI to how to implement it [3][5]. - The report categorizes companies into "AI-Native" and "AI-Enabled," identifying "High Growth Companies" based on specific revenue and growth criteria [5][6]. - High Growth Companies must have annual revenues of at least $10 million, with varying growth rate requirements based on revenue brackets [6]. Group 2 - AI-Native companies are found to have a faster product lifecycle and greater success in scaling their initial AI products compared to AI-Enabled companies, with 47% of AI-Native products achieving market validation versus only 13% for AI-Enabled products [7]. - The report emphasizes the importance of balancing experimentation, market speed, and performance in the development of AI products [7]. Group 3 - The report outlines five main chapters focusing on the end-to-end process of AI product development, market pricing, organizational structure, budgeting, and internal productivity [6]. - It highlights the evolving demand for talent within AI companies and the differences in hiring trends between last year and this year [5]. Group 4 - The pricing logic for AI products is still maturing, with many companies exploring hybrid pricing strategies, and there is a notable retention of free products in the market [5]. - The allocation of AI budgets varies significantly depending on the product stage, with high-growth AI companies facing specific challenges [5]. Group 5 - The report indicates that not all AI companies fully utilize AI tools internally, with certain departments showing higher adaptability to AI technologies [5]. - It identifies the most popular AI tools among AI companies and discusses the varying levels of AI adoption across different functions [5].