X 上的网友制作了一张 Clawdbot 在 Github 的标星增长趋势对比图，几乎是直线上涨，现在已经到了 98K。 Clawdbot 背后的开发者 Peter Steinberger，是一个特别有意思的老哥。iOS 生态系统最早的一批开发者之一，开发经验可以追溯到 iOS 2.0 时代。在开 源社区贡献了非常多项目。 于是，「退休」三年后，Steinberger 重新回来了。Steinberger 在最新采访中提到， 早在去年五月份，我就有了做个人 Agent 的想法，那会儿 GPT-4 被 GPT-4o 替代，当时觉得模型还不够好，但我当时又觉得，这事大公司未来几个月肯定会做。 可是等到了 11 月，我发现市面上还是没有我想要的个人智能体。 于是，我决定自己搞。这基本就是 Clawdbot 项目的起点了。 Clawdbot（最近改名叫 Maltbot），目前最热门的 AI 项目，不光是在 X 上「一夜成名」，在谷歌上的搜索量更是直接超过了 Claude Code、Codex。 2011 年，Steinberger 创立了 PSPDFKit，用 13 年时间把它从开发者工具搞成了 B2B 软件巨头。以超 ...

Core Insights - ClawdBot, a personal AI assistant, has gained significant attention in Silicon Valley and social media, with its creator Peter Steinberger facing trademark issues leading to a name change to Moltbot [2] - Users have praised ClawdBot as a revolutionary AI application, likening it to having a dedicated AI employee available 24/7 [3] - ClawdBot's unique collaborative approach allows non-coders to contribute directly, emphasizing problem-solving over traditional coding [6] Group 1 - ClawdBot can control computers almost entirely, lacking traditional restrictions, and features a complex memory system that retains user interactions [7][8] - The assistant interacts through various chat applications, including WhatsApp, Telegram, and Discord, but its open permissions raise security concerns [8][9] - The surge in ClawdBot's popularity has led many users to purchase Mac Mini computers for optimal performance, although alternatives exist [9][11] Group 2 - Peter Steinberger, the developer, has a notable background, previously running a successful B2B company before returning to the tech scene to create ClawdBot [14][12] - The project began as a personal solution to a need for a life assistant, evolving into a widely adopted tool after realizing no major companies had tackled this problem [15][19] - ClawdBot's development has been rapid, with a focus on community involvement and open-source collaboration, allowing users to contribute even without coding experience [27][28] Group 3 - The assistant's capabilities extend to automating various tasks, including managing household chores and personal reminders, significantly enhancing user productivity [43][48] - Users have reported diverse applications, from managing emails to controlling smart home devices, showcasing ClawdBot's versatility [42][46] - The project aims to empower users to maintain control over their data while providing a free and open-source solution, contrasting with larger corporate models [24][23]

这两天，个人 AI 助手 ClawdBot 席卷硅谷，国内外社交平台上全是关于它的讨论。 在试用后，网友们纷纷给出了很高的评价。"它是迄今为止最伟大的 AI 应用，相当于你 24 小时全天候专属 AI 员工。"Creator Buddy 创始人兼 CEO Alex Finn 盛赞道，"这就是他们 (Anthropic) 希望 Claude Cowork 呈现的样子。" 当前，ClawdBot 项目已经开源，现在已经斩获了 20.8k stars：https://github.com/clawdbot/clawdbot Alex 展示了给他的 Clawdbot 发信息，让它帮其预订下周六在一家餐厅的座位。当 OpenTable 预订失败时，Clawdbot 利用 ElevenLabs 的技术致电餐厅并完 成了预订。 但 ClawdBot 真正让技术圈兴奋的，并不只是"能干活" ，而是其协作方式极其激进：不会写代码的人，也能直接提 PR。原因很简单：它几乎是 100% 用 AI 写出来的，PR 在这里更像是"我遇到了这个问题"，而不是"我写了一段多漂亮的代码"。 更有意思的是，这个看似"全开源"的项目，偏偏故意留 ...

Core Insights - A senior Google engineer revealed that Anthropic's Claude Code was able to replicate a system that her team had spent a year developing in just one hour, highlighting the rapid advancements in AI programming capabilities [1][3][6]. Group 1: AI Programming Capabilities - The engineer, Jaana Dogan, described how she used Claude Code to generate a system by simply providing a brief description, which closely resembled the work done by her team over the past year [3][4]. - Dogan emphasized that the industry is still in a phase of exploration regarding language models, which are expected to continue evolving and becoming more powerful [5][6]. - The rapid advancements in AI programming capabilities have led to a significant increase in quality and efficiency, surpassing previous expectations [6][7]. Group 2: Industry Reactions and Perspectives - There is a polarized reaction within the developer community regarding coding agents, with some viewing it as hype while others recognize its potential [4][9]. - Dogan's public acknowledgment of a competitor's product has sparked discussions about the implications of AI on the engineering profession, with some suggesting it could signal a technological turning point [10][11]. - Critics argue that while AI can generate code quickly, the real challenge lies in problem definition and alignment within teams, which AI does not address [12][13]. Group 3: Google and Anthropic Relationship - Google has invested approximately $3 billion in Anthropic and holds about 14% of its shares, indicating a strong partnership between the two companies [17][20]. - A significant agreement between Google and Anthropic involves Google providing up to 1 million TPU units, valued at hundreds of billions, to enhance AI capabilities [20]. - Dogan noted that the industry is not a zero-sum game, and recognizing the achievements of competitors can drive further innovation [21].

机器之心编辑部 近日，X 知名博主、Hyperbolic 联创 & CEO Yuchen Jin 发帖称，如果在他读博士的时候就有 Claude Code、Gemini 和 ChatGPT 等各类 AI 工具出现，那么 也许只要一年就能毕业，而不是用了 5.5 年。 而他之所以发出这个感慨，缘由是最近一些硅谷 AI 大厂工程师表示，在用了 AI 工具后，项目完成时长被大幅压缩…… 先是谷歌首席工程师、Gemini API 负责人 Jaana Dogan 在 X 上发文称：「我不是在开玩笑，这也不好笑。从去年开始，我们就在谷歌内部尝试构建分布式 Agent 编排器。有多种选择，大家并没有完全认同…… 我只是向 Claude Code 描述了问题，它就在一小时内生成了一个东西，而这几乎就是我们去年一年 所做的东西。」 随后，她又发文补充，提示内容不算详细，也没有具体细节，只是一段三段式的描述。但由于不能分享任何东西，也不好具体展示出来，总结来说就是在 现有一些想法基础上构建一个玩具版本，用以评估 Claude Code。 帖子一经发布，迅速引起网友讨论，有人感慨没想到当前的 AI 编码工具已经发展到如此强大的地步 ...

机器之心编辑部 近日，X 知名博主、Hyperbolic 联创 & CEO Yuchen Jin 发帖称，如果在他读博士的时候就有 Claude Code、Gemini 和 ChatGPT 等各类 AI 工具出现，那么也许只要 一年就能毕业，而不是用了 5.5 年。 而他之所以发出这个感慨，缘由是最近一些硅谷 AI 大厂工程师表示，在用了 AI 工具后，项目完成时长被大幅压缩…… 先是谷歌首席工程师、Gemini API 负责人 Jaana Dogan 在 X 上发文称：「我不是在开玩笑，这也不好笑。从去年开始，我们就在谷歌内部尝试构建分布式 Agent 编 排器。有多种选择，大家并没有完全认同…… 我只是向 Claude Code 描述了问题，它就在一小时内生成了一个东西，而这几乎就是我们去年一年所做的东西。」 随后，她又发文补充，提示内容不算详细，也没有具体细节，只是一段三段式的描述。但由于不能分享任何东西，也不好具体展示出来，总结来说就是在现有一 些想法基础上构建一个玩具版本，用以评估 Claude Code。 随后此推文获得了上百次的浏览，而该网友也发文认真做起了自我介绍，原来 Rohan Anil ...

Core Insights - The emergence of programming agents has significantly increased productivity among engineers, with many expressing that they can accomplish years of work in a matter of months using these tools [1][4][5] - Prominent figures in the tech industry, including David from Midjourney and Elon Musk, have acknowledged the transformative impact of these programming agents, suggesting that we have entered a new era of technological advancement [2][4] Group 1: Industry Impact - David, the founder of Midjourney, noted that he completed more programming projects during the recent holiday than in the past decade, highlighting the rapid advancements in AI coding tools [1] - Rohan Anil, an engineer at Anthropic, claimed that with the help of programming agents like Claude's Opus, he could compress six years of work into just a few months [5][6] - Jaana Dogan, a chief engineer at Google, echoed similar sentiments, stating that the programming agent could generate complex solutions in a fraction of the time it took her team to develop them [7][9] Group 2: Performance Metrics - The latest LiveBench benchmark tests revealed that Claude 4.5 Opus achieved the highest scores across various categories, including coding and mathematics, indicating its leading position in AI programming tools [12][13] - Claude 4.5 Opus scored 79.65 in coding and 94.52 in mathematics, outperforming competitors like GPT-5.1 Codex Max and Gemini 3 Pro Preview [13] Group 3: Competitive Landscape - There is a growing trend among tech companies to adopt and experiment with various programming agents, with some engineers at Google using competitors' tools, which has raised eyebrows in the industry [9][11] - Meta has reportedly mandated its engineers to use its own programming agent, Llama 4, indicating a competitive push within the sector [11] Group 4: Emerging Products - Domestic programming agent products are also entering the market, with ByteDance's TRAE China version SOLO being made fully available for free, reflecting the increasing competition in the AI coding space [17]

Core Insights - The article discusses the significant advancements in programming agents, highlighting their impact on productivity and efficiency in software development [2][3][6]. Group 1: Programming Agents Impact - Midjourney founder David expresses that his programming projects during the holiday season surpassed those of the past decade, indicating a transformative shift in productivity due to programming agents [3][4]. - Elon Musk comments on the emergence of programming agents, stating, "We have entered the Singularity," reflecting a consensus among tech leaders about the profound changes brought by AI [5][6]. - Rohan Anil, an engineer at Anthropic, claims that with programming agents like Claude's Opus, he could compress six years of work into just a few months, showcasing the efficiency gains possible with these tools [9][15]. Group 2: Performance Metrics - The latest LiveBench benchmark results show Claude 4.5 Opus leading in various categories, including coding and reasoning, with scores of 79.65 in coding and 94.52 in mathematics, indicating its superior performance among AI models [23][24]. - Other models, such as GPT-5.1 Codex Max and Gemini 3 Pro Preview, follow behind, with Claude consistently outperforming them in agentic coding tasks [24]. Group 3: Industry Reactions and Developments - Greg Brockman notes that Anthropic has achieved what OpenAI aimed for but could not, emphasizing the practical utility of their tools [25][26]. - Boris Cherny, a developer of Claude Code, shares insights on how to effectively utilize the programming agent, highlighting its user-friendly setup and capabilities [28][29]. - The competitive landscape is evolving, with ByteDance's TRAE China version SOLO being made freely available, indicating a growing interest in programming agents within the industry [31][32].

Core Insights - The article emphasizes the efficient use of AI coding tools by selecting the right model based on task type, restructuring workflows, and clarifying human-AI collaboration [1][3][18] Group 1: Model Selection - It is crucial to choose the appropriate coding model based on the task type; for large tasks, Codex is recommended, while Opus is better for smaller, fragmented tasks [6][8] - Codex can read through entire projects to understand logic and fix bugs, making it suitable for complex requirements [7] - For advanced users, GPT-5.2-Codex is suggested for its speed and accuracy, eliminating the need to switch between models [10] Group 2: Workflow Restructuring - A customized workflow allows the author to manage multiple projects simultaneously; ideas are directly added to Codex's queue instead of being noted down [14][15] - A key tip is to avoid rolling back changes, as iterative development is normal and time should not be wasted on reconsidering past decisions [16] - Reusing code from previous projects can save time; Codex can adapt existing code for new functionalities [17] Group 3: Human-AI Collaboration - The principle of human-AI collaboration is that AI should handle execution while humans make decisions, such as selecting libraries and designing system architecture [18][19] - The author provides examples of effective collaboration, including allowing AI to write core code while the human focuses on decision-making [20][21] Group 4: Practical Tips - Start development with a CLI tool to validate core logic before expanding to more complex features [23][24] - Maintain a documentation folder for each project to help the AI understand context and reduce repetitive communication [25][26] - For solo developers, directly committing to the main branch is recommended to avoid complications with multiple branches [27][29]

Financial Data and Key Metrics Changes - The company reported third quarter revenue of $189 million, a year-over-year increase of 22%, with 18% organic growth excluding acquisitions and currency impacts [21][22] - Adjusted gross profit was $101 million, up 28% year-over-year, with an adjusted gross margin of 53.3%, reflecting a 260 basis point increase year-over-year [22][23] - Adjusted net income was $26 million, a $2 million year-over-year increase, with adjusted fully diluted earnings per share for the third quarter at $0.46 compared to $0.43 in the same period of 2024 [25][26] Business Line Data and Key Metrics Changes - Process Analytics led growth with over 50%, including more than 30% growth at CTECH, while Filtration grew over 20% [7][18] - Consumable demand remained robust with greater than 20% growth, and Capital Equipment also had over 20% growth [8][21] - Chromatography revenue grew mid-teens, driven by large column demand from key CDMO and pharma accounts globally [17] Market Data and Key Metrics Changes - Biopharma revenues grew over 20% year-over-year, with emerging biotech revenue at the highest level in nearly three years [11][21] - Asia Pacific saw approximately 50% growth, while the Americas grew 20% and EMEA was up low double digits [11][22] - China revenue returned to growth in Q3, although orders were slightly down, with expectations for recovery in 2026 [22][39] Company Strategy and Development Direction - The company is focusing on digitization as a key pillar of its strategic plan, with ongoing investments in analytics and process control technologies [12][19] - A partnership with Novasign was announced to integrate digital twin capabilities, aiming to optimize process development and manufacturing [13] - The Strategic Account Strategy initiative has successfully engaged 20 large pharma and CDMO accounts, leading to increased cross-selling opportunities [14] Management Comments on Operating Environment and Future Outlook - Management expressed optimism about the recovery of small biotech and the overall health of the ecosystem, with a focus on capitalizing on growth strategies [11][39] - The company is raising the midpoint of its organic growth guidance for 2025, reflecting strong performance across franchises and geographies [10][27] - Management remains committed to balancing cost efficiency and margin expansion while investing in future growth opportunities [30][31] Other Important Information - The company expects adjusted effective tax rate for the year to be between 21% to 22%, about 100 basis points lower than previous guidance [25][31] - Cash position at the end of Q3 was $749 million, up $40 million sequentially, driven by strong operating cash flow performance [26][31] Q&A Session Summary Question: Can you talk about the cadence of order momentum across the quarter? - Management noted that orders grew more than 20% for the second consecutive quarter, with strong growth across all franchises and no significant changes in order patterns throughout the quarter [35][37] Question: Can you reconcile the sales guidance increase versus narrowing EBIT margin? - Management highlighted that while they are pleased with margin performance, they are making strategic investments in infrastructure and operations to support future growth, which impacts margins [42][44] Question: What is the outlook for onshoring activity and larger scale projects? - Management indicated that they are well-positioned to participate in upcoming onshoring projects, with expectations for first orders to come in the second half of 2026 [46][48] Question: How do you evaluate the performance of mid-sized CDMOs? - Management acknowledged strong performance from large-scale CDMOs but did not specifically address mid-sized CDMOs, indicating that large-scale accounts were the primary drivers of growth [92] Question: What trends are being observed in the Asia Pacific region? - Management confirmed that Asia Pacific represents about 15% of sales, with plans for further investments and a new office opening in Singapore, indicating a commitment to growing in the region [65][66]