模力工场 新鲜事 在 AI 狂飙的时代，追逐技术热点之外，什么才是决定未来生存的底层法则？2 月 9 日（下周一）晚 17:30，锁定模力工场视频号直播间，创始人霍太 稳将与一位神秘重磅嘉宾一同开讲，带你穿透技术喧嚣，抓住 AI 洪流中真正决定长期价值的"慢变量"。欢迎扫码预约，直播间不见不散！ 031 周上榜应用精选（附用户热评） 模力工场 31 周 AI 应用周榜来啦～本周共有 31 款应用上架新榜，所有排名均来自用户真实使用、测评与社区讨论热度。本期用户热评清晰地指出：当 前 AI 工具在 流程自动化 （如蓝耘星河、ClawdBot）和 结构化生成 （如 AI 快研侠、Lovable）上已相当成熟，堪称"数字同事"。而在 信息深度整合 与 实时性处理 方面，仍有明确的进步空间。同时，AI 正向更感性、更内在的体验领域延伸，预示着技术发展的下一个前沿。 我们从中精选出十款最具声量的应用，聚焦五大垂直领域，为你更详细地解读榜单背后的 AI 行业风向。 营销与内容创作类 1 . 蓝耘星河营销智能体 北京 关键词：AI Agent｜营销增长｜新媒体创作 小 A 推荐：一款面向自媒体和营销场景的 AI 智能体，旨 ...

Core Insights - The AI coding sector has seen rapid growth, with several leading players achieving annual recurring revenue (ARR) in the range of $100 million to $1 billion, and Emergent reaching $50 million in ARR within just seven months [1] - Emergent recently completed a $70 million Series B funding round, led by SoftBank and Khosla Ventures, with a post-money valuation of $300 million and claims of over 5 million users [1] Group 1: Emergent's Unique Features - Emergent employs a multi-agent architecture that simulates a complete engineering team, addressing challenges in cross-file reasoning and context understanding that traditional AI coding tools face [2] - The system includes specialized AI agents for planning, design, frontend, testing, and operations, ensuring that each line of code is validated through a closed-loop testing process, resulting in production-grade software [2] - Emergent's 1 million token context window and "Forkchat" feature help maintain understanding of the entire codebase and allow for project evolution without losing context [3] Group 2: Deployment and Operations - Emergent's deployment strategy utilizes managed Kubernetes and cloud automation, enabling non-technical users to push code to production with a single click, bypassing complex cloud configuration [3] - The introduction of "agent-based operations" allows AI to handle traditional operational tasks, providing 24/7 monitoring and automatic debugging to restore services without human intervention [4] Group 3: Market Context and Future Potential - The rapid decrease in software creation barriers is expected to change industry behavior patterns, as noted by Khosla founder Vinod Khosla [4] - Emergent's founders, Mukund and Madhav Jha, are positioned to leverage their experience, with Mukund previously co-founding Dunzo [4] - Another noteworthy AI product has achieved $100 million in ARR within two years, exemplifying the potential for AI to replace traditional services in the SaaS sector [5][6]

近期 Claude Code 推出的 Excel 功能非常惊艳，我们认为 Excel 可能成为继 Coding 之后，下一个迎来"aha moment"、并快速爆发的高价值领域。 本文是 Altiemeter 合伙人 Freda Duan 对 Coding 和 Excel 这两个 AI 垂直领域的深度解读，原文发布于她的 Substack Robonomics。 简单来说，正如 Coding 凭借庞大的市场规模、向相邻场景自然延展的能力以及以产品驱动的 GTM 模式，迅速崛起为最强势的 AI 应用之一，Excel 也具 备同样的条件： Coding 已经证明了这条路径下的爆发力，而 Excel 很可能是体量更大的下一站。 Intro Coding 以超出所有人预期的表现，成为至今为止最强势的 AI 垂直应用之一。它同时具备三种罕见的特质：极其庞大的 TAM、自然延展到相邻使用场景 的切入口，以及以产品驱动为核心的 GTM 模式，几乎不需要传统的销售和市场推广。 具备这种组合特征的垂直领域非常少，Excel 是其中之一。它的 TAM 甚至更大，从某种角度看，软件行业的很大一部分都可以被视为一层层叠加在 Exce ...

Core Viewpoint - The traditional IDEs may become obsolete by 2026, as engineers who do not adapt to new AI development methods will fall behind in productivity and competitiveness [1][5]. Group 1: Future of Development Tools - The transition from traditional IDEs to new AI-driven development tools is likened to moving from handheld tools to CNC machines, emphasizing the need for precision and automation in coding [2][11]. - Current AI models are inefficient, akin to sending a single diver into a vast codebase, suggesting a need for multiple specialized roles to enhance productivity [3][19]. - The future of software development will involve task decomposition, gradual refinement, and collaboration among multiple intelligent agents rather than relying on a single AI model [22][24]. Group 2: Productivity Disparities - There is a significant productivity gap among engineers, with those using AI tools like Codex potentially being ten times more productive than their peers who do not [5][27]. - Management is concerned about the implications of this productivity divide, fearing that they may need to reduce their workforce by up to 50% if engineers do not adapt [5][27]. - The situation mirrors the decline of the Swiss watch industry, where traditional craftsmanship was rapidly overtaken by quartz technology [8]. Group 3: New Development Paradigms - The concept of "Vibe coding" is introduced, where coding is driven by dialogue and AI-generated outputs, moving away from traditional manual coding practices [29][35]. - The economic implications of Vibe coding are significant, allowing for more modular and experimental approaches to development, thus increasing the value of options available to teams [38]. - Examples from companies like Travelopia and Capital One illustrate how AI-driven development can drastically reduce the time and resources needed for project completion [41][49]. Group 4: Organizational Transformation - The integration of AI tools is reshaping technical organizations, enabling non-developers to contribute to coding and deployment processes, thus democratizing software development [44][47]. - Trust in AI increases with usage, suggesting that engineers need to practice and engage with these tools to fully leverage their capabilities [42]. - The rapid pace of code submission and the ability to resolve legacy system issues with AI-generated solutions indicate a transformative shift in how teams operate [49].

智东西1月16日报道，今天，据彭博社报道，美国Vibe Coding（氛围编程）独角兽Replit即将完成一笔新的融资交易，计划筹集大约4亿美元（约合人民币 27.87亿元）的资金，其投后估值或将达到约90亿美元（约合人民币627.15亿元），大约是上轮融资时估值的3倍。 去年9月，Replit刚刚完成一轮2.5亿美元（约合人民币17.42亿元）的融资，估值为30亿美元（约合人民币209.05亿元）。自2016年成立以来，Replit已经完 成了10次融资，累计融资总额为4.72亿美元（约合人民币32.89亿元）。 Replit还在2025年迈入了"1亿美元ARR（年度经常性收入）俱乐部"。在AI应用赛道，能迈过这一门槛的企业屈指可数，都是头部玩家，比如Perplexity、 Character.AI等。而具体到Vibe Coding这一赛道，目前仅有Cursor、Lovable和Replit三家实现了这一目标。 与传统编程依赖开发者逐行编写代码不同，Vibe Coding更强调表达意图，用户只需描述想做什么，AI会自动完成需求拆解、代码生成、调试、部署甚至 数据库配置等完整流程。 不过，Replit并非一开 ...

周四， Replit 发布了其智能体的新版本，用户仅需描述应用功能即可构建同时支持安卓和 iOS 的移动应用。该工具还能以极简操作将软件发布至应用商 店。 Replit 表示人们可利用此工具开发移动游戏、个人生产力产品及移动商店等应用。 Replit 面临着来自新兴初创企业和大型科技公司的激烈竞争，这些企业将软件工程视为人工智能服务利润丰厚的市场。 OpenAI 、 Anthropic 和微软公司均 提供旨在简化软件开发流程的人工智能工具。 另一家人工智能编程初创公司 Cursor 最近估值达到 293 亿美元 。 参考资料： 图片来源： Replit Replit 已成为构建 AI 编程工具的领军企业，这些工具可供专业开发人员和编程新手用于编写和调试软件，同时该公司也面临着其他初创公司和大型科技企 业的竞争。 知情人士透露，人工智能编码初创公司 Replit 即将达成新一轮融资协议，其估值将增至大约三倍，达到 90 亿美元，其中包括所筹集的资金。 十年前成立的 Replit 已成为所谓的氛围编程领军者，其构建的工具能让专业开发者和编程新手借助 AI 编写及调试软件。 该公司去年九月以 30 亿美元估值 筹集 ...

Core Insights - The article discusses the risks associated with AI programming tools, highlighting incidents where such tools have caused significant data loss for users due to misinterpretation of commands and lack of proper safeguards. Group 1: Incident Overview - A developer reported that using Claude CLI to clean an old code repository resulted in the complete deletion of their Mac's home directory, leading to substantial data loss [1][4]. - The command executed by Claude CLI included a critical error where it mistakenly included the home directory path, resulting in the deletion of all user files, including documents and application data [2][1]. Group 2: Broader Context of AI Tool Failures - The article notes that the issue is not isolated, with other developers experiencing similar problems using different AI tools, such as a Greek developer who lost an entire hard drive while using a Google AI IDE [5]. - A SaaStr.AI CEO also reported that the Replit tool deleted his database despite explicit instructions not to modify any code [5]. Group 3: User Reactions and Discussions - The community's response to these incidents has been mixed, with some attributing the failures to user error while others emphasize the need for better safeguards in AI tools [6]. - Suggestions for improvement include implementing confirmation steps for high-risk operations and establishing permission levels to prevent unauthorized actions [6][9]. Group 4: Preventive Measures and Solutions - Developers are exploring ways to mitigate risks, such as running AI tools in Docker containers and creating auxiliary tools like cc-safe to scan for high-risk commands before execution [6][8]. - The cc-safe tool can detect dangerous commands and is designed to prevent accidental deletions by scanning project directories [8]. Group 5: Future Considerations - The article concludes with a cautionary note about the potential for widespread issues as AI programming tools become more prevalent, stressing the importance of human oversight and careful command verification [11][9].

"氛围编程"可以说是今年最热最出圈的话题了。然而，从"用 LLM 快速拼装应用"爆红，到现在也不过才六个月，就明显开始"退潮"了。 最直观的体现，是全线产品的用户流量出现大幅下滑。 降幅最大的当属 Lovable，其流量在近几个月内从 3500 万掉到不足 2000 万，几乎砍半。其它几个明星产品也没好到哪里去，Bolt.new 下降了 27%，而 Vercel v0 自 5 月以来下降了 64%，Cursor、Replit、Devin 等平台也未能独善其身，唯一例外的是仍在依靠投放驱动的 Base44。 连 Bolt.new 的 CEO 也公开承认，"所有平台的用户流失率都非常高"，并表示当务之急是构建能留住用户的业务模式。 过去一年，行业经历了资本驱动的"超高速增长期"，公司估值与用户数同步飙升；然而当热度在短短几个月内迅速回落，我们或许正在见证一场真正的价 值回归。 | 12wk Change | ela | 5/23 | 616 | 6/20 | 714 | 7/18 | 8/1 | 8/15 | 8/29 | 9/12 | 9/26 | 10/10 | | --- | --- | --- | --- ...

从人力资源到会计行业，越来越多非技术从业者开始使用 ChatGPT、Gemini、Claude、Replit 等工具自己制作应用。皮查伊认为，氛围编程让使用者能直接 把想法做成模型，而不仅仅是描述。"过去只能用语言解释，现在可以先做出一点雏形再展示。" IT之家 11 月 28 日消息，据《商业内幕》今日报道，谷歌 CEO 桑达尔・皮查伊认为，氛围编程（Vibe coding）正在为非技术背景的工作者打开同样的大 门，就像博客曾让普通写作者找到职业入口，YouTube 也让更多人把内容创作变成事业一样。 这种方式甚至开始改变科技公司内部的流程。Meta 的产品经理已经用氛围编程做原型并展示给扎克伯格。皮查伊透露，谷歌内部首次提交代码变更的员工 数量也明显增加。 皮查伊在一档谷歌开发者播客中表示，氛围编程让创作应用和网站变得更加愉快，人们即便没有编码基础，也能随时尝试搭建原型。技术正在变得更易接 近，更有趣，而且还会不断进化，从而让人再度兴奋起来。 不过，随着氛围编程的快速普及，把编码工作交给 AI 也带来风险。IT之家从报道中获悉，皮查伊强调，大型关键系统仍必须由专业工程师负责，因为安全 与准确性都无法被忽视 ...

Core Insights - The article discusses how Replit, an AI programming platform, is transforming the coding experience by allowing users to interact with AI agents that can write code based on simple prompts, effectively making AI the new "programmer" [4][7][18]. Group 1: AI Programming Experience - Replit aims to eliminate the complexities of setting up development environments, allowing users to focus on their ideas and projects [6][10]. - Users can input their project ideas in plain English, and the AI agent will interpret these inputs to create a task list and execute the necessary coding tasks [16][18]. - The platform supports multiple programming languages and automatically selects the most suitable technology stack based on user input [8][9]. Group 2: AI Agent Capabilities - The AI agents are designed to perform tasks autonomously, effectively taking on the role of the programmer [18][19]. - The agents can run for extended periods, with improvements in their ability to maintain coherence and complete complex tasks over time [22][26]. - Innovations such as "context compression" and the introduction of verification loops have enhanced the agents' long-term reasoning capabilities [24][28]. Group 3: Future of AI in Programming - The next iteration, Agent4, aims to allow users to deploy multiple agents simultaneously, enhancing collaborative coding efforts [45]. - The article suggests that the programming field is on the verge of explosive growth, with AI enabling individuals without technical backgrounds to achieve advanced coding capabilities [45][46]. - There is a discussion on the potential of AI to reach a level of general intelligence (AGI), but concerns remain about the current limitations in transferring learning across different domains [47][50].