此外，2月12日，MiniMax正式上线最新旗舰编程模型MiniMax M2.5。作为全球首个为Agent场景原生设 计的生产级模型，其编程与智能体性能 (Coding & Agentic)比肩国际顶尖模型，直接对标 Claude Opus 4.6，支持PC、App、跨端应用的全栈编程开发，尤其在 Excel高阶处理、深度调研、PPT等Office核心生 产力场景中均处于行业领先（SOTA）地位。 消息面上，《广东省加快数字社会高质量建设实施意见》提出，壮大数字技术应用服务新业态。加快人 工智能技术应用服务，培育一批深入行业应用的人工智能应用服务商，支持培育垂直领域"人工智能 +工业软件"与智能机器人服务商。支持开源鸿蒙社区建设，培育优质开源项目，拓展开源鸿蒙应用。 培育第三方专业服务机构，为数字化转型提供合规、安全、技术评测、规划设计等服务。 2026年2月12日盘中，互联网服务、软件开发等板块涨幅居前。有市场分析认为，春节前后是国内大厂 密集发布AI应用的关键窗口。近日，字节跳动旗下即梦AI发布新一代视频生成模型Seedance 2.0，实现 多项质变，其多镜头叙事与导演级控制、精准的音画同步与口型匹配， ...

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Core Insights - The rapid development of AI agents has led to a significant trend in building infrastructure specifically for AI, exemplified by the launch of Entire, an AI version of GitHub, founded by former GitHub CEO Thomas Dohmke, which recently secured $60 million in seed funding at a valuation of $300 million [1][2]. Group 1: Entire's Vision and Components - Entire aims to create a global developer platform that facilitates collaboration between AI agents and humans, featuring an open, scalable, and independent system for all developers regardless of the AI model used [7]. - The platform will be built on three key components: a Git-compatible database for unified version control of code and context, a universal semantic reasoning layer for multi-agent coordination, and an AI-native software development lifecycle to reshape the development process [7]. - The first product, Checkpoints, is an open-source tool that pairs every piece of software generated by AI with its context, allowing human developers to review and learn from AI's reasoning [8]. Group 2: Challenges in Current Software Development - The current software development lifecycle is designed for human collaboration and is not suitable for the AI era, leading to inefficiencies and limitations in the software ecosystem [5][12]. - Developers are facing increased complexity and cognitive burden as they manage a growing array of tools, while the quality and security of code are declining due to reliance on platforms not designed for AI [12]. - The need for a new, AI-native development environment is emphasized, as existing systems are inadequate for the demands of AI-driven programming [12].

Core Viewpoint - The software industry is at a pivotal moment where AI programming has evolved from enhanced autocomplete to autonomous development agents, leading to a shift in hiring practices and developer roles [2]. Group 1: Junior Developer Issues - The recruitment of junior developers may decline due to AI automating entry-level tasks, but could rebound as software permeates various industries, necessitating different survival strategies [4]. - A study by Harvard found that when companies adopt generative AI, the employment rate of junior developers dropped by approximately 9-10% over six quarters, while senior developers' employment remained stable [4]. - The U.S. Bureau of Labor Statistics predicts that software jobs will still grow by about 15% from 2024 to 2034, indicating a potential demand for human developers to leverage AI opportunities [5]. Group 2: Skills Issues - As AI writes most of the code, core programming skills may degrade, or become more critical as developers need to supervise AI outputs [9]. - Currently, 84% of developers regularly use AI tools, leading to a shift in skill sets from implementing algorithms to effectively querying AI and validating its outputs [9]. - The future may see a divide among developers, with some relying heavily on AI and others advocating for foundational coding skills to handle AI-generated errors [11]. Group 3: Role Issues - Developer roles may shrink to limited auditing tasks or expand to key coordinators managing AI-driven systems, with value creation extending beyond mere coding [15]. - In a pessimistic scenario, developers may become mere auditors of AI outputs, while in a more optimistic view, they could evolve into architects or product strategists overseeing AI integration [16]. Group 4: Expert vs. Generalist Issues - Specialists in narrow fields may face risks of obsolescence due to automation, while T-shaped engineers with broad adaptability and deep expertise in one or two areas are increasingly favored [22]. - Nearly 45% of engineering roles now expect proficiency across multiple domains, highlighting the shift towards versatile skill sets [24]. Group 5: Education Issues - The traditional four-year computer science degree is being challenged by faster learning paths like coding bootcamps and employer training programs, as universities struggle to keep pace with rapid industry changes [30]. - By 2024, nearly 45% of companies plan to eliminate degree requirements for certain positions, reflecting a shift towards skills-based hiring [31].

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Core Viewpoint - The rise of AI technologies, such as Seedance 2.0, is causing anxiety in various industries, including film, as it raises concerns about job displacement and changing work standards [1][10]. Group 1: Job Landscape Changes - There is a common misconception that AI is replacing jobs; however, many layoffs are due to post-pandemic adjustments rather than AI capabilities [3]. - AI can cover 30% to 40% of standardized tasks, leaving 60% to 70% still requiring human involvement, which highlights the importance of adapting to new work standards [4][7]. - The ability to utilize AI effectively creates a significant efficiency gap between those who can and those who cannot [5][9]. Group 2: Skill and Decision-Making Shifts - The demand for decision-making skills has increased, as AI accelerates execution but does not enhance decision-making speed [15][18]. - The ratio of engineers to product managers in Silicon Valley has shifted dramatically from 8:1 to as low as 1:1, indicating a change in bottlenecks from execution to decision-making [13][14]. - Skills that were once valuable, such as memorizing complex syntax, are becoming less important as AI can perform these tasks more accurately [16]. Group 3: Organizational Transformation - Many companies struggle with AI transformation because they focus on local optimizations rather than rethinking entire processes [20][21]. - Successful organizations are those that redefine their product offerings and service paths around AI capabilities, rather than merely using AI as an efficiency tool [22][23]. - The challenge lies in overcoming resistance from leadership, who may fear that AI implementation signals impending layoffs [25]. Group 4: Future of Work - The nature of work is evolving, with individuals now expected to manage entire processes with the assistance of AI [28][32]. - The difficulty in finding jobs stems from outdated methods that no longer meet current expectations [29][30].

来源：市场资讯 序号股东名称持股比例1无锡心动麦力科技有限公司100% 经营范围含技术服务、技术开发、技术咨询、技术交流、技术转让、技术推广；工业互联网数据服务； 数据处理和存储支持服务；数据处理服务；软件开发；信息系统集成服务；计算机系统服务；人工智能 应用软件开发；人工智能基础软件开发；人工智能通用应用系统；人工智能行业应用系统集成服务；互 联网数据服务；5G通信技术服务；物联网技术服务。（除依法须经批准的项目外，凭营业执照依法自 主开展经营活动） 天眼查显示，近日，雄安心麦科技有限公司成立，法定代表人为胡玉霞，注册资本1000万人民币，由无 锡心动麦力科技有限公司全资持股。 企业名称雄安心麦科技有限公司法定代表人胡玉霞注册资本1000万人民币国标行业信息传输、软件和信 息技术服务业>软件和信息技术服务业>软件开发地址河北雄安新区容城县容东片区华望城咏华园一区2 号楼2单元501室（自主申报）企业类型有限责任公司（自然人投资或控股的法人独资）营业期限2026- 2-10至无固定期限登记机关河北雄安新区营商环境局 ...

当 Agent 开始用 Git 说话：从一个 Vibe Coding 开发者的发现，到 Agent 协作的未来。 文章内容由歸藏和 Opus 4.6 的讨论自动整理而成 一、一个意外的发现 最近我在维护自己的开源项目时，做了一件很自然的事：让 AI Agent 帮我处理 GitHub 上的 Issues 和 PR。 一开始只是图省事——Issue 太多了，让 Agent 帮我读一读、分分类、回复一些常见问题。PR 也 是，让 Agent 先做一轮 Code Review，帮我过滤掉明显有问题的提交。 但很快我发现了一件有趣的事情： 给我提 Issue 的，很多也是 Agent；给我提 PR 的，也是 Agent。 我的 Agent 在和别人的 Agent 对话。 可读且安全 ：纯文本，所有操作透明可审计 命令式的 ：Issue 是任务指令，PR 是执行结果 结构化的 ：标签、模板、状态流转，天然适合机器解析 有版本控制 ：每一次交互都被记录，不会丢失 "我们仍然依赖一个在云时代之前构建的软件开发生命周期，它天生是为人与人协作设计 的。" 它们用 Issue 的格式交换需求，用 PR 的格式交换代码，用 Com ...

在数字化转型浪潮下，微信小程序已成为企业和商家连接用户、拓展业务的核心阵地。然而，面对市场上琳琅满目的开发服务商，如何选 择一家靠谱、专业且性价比高的合作伙伴，常常让决策者感到困惑。 无论是初创团队还是成熟企业，一个稳定、功能完善且易于运营的小程序，往往能成为业务增长的强力引擎。今天，我们就来深入探讨 《如何评估小程序开发工作量》，并基于技术实力、服务口碑、性价比及行业案例等多个维度，为大家梳理一份2026年值得关注的微信小 程序开发服务商排名，希望能为您的选择提供一份实用的参考。 评估一个小程序的开发工作量，绝非简单地看页面数量。它需要综合考虑功能模块复杂度（如是否涉及在线支付、会员体系、直播、多商 户管理）、UI/UX设计需求（定制化程度）、后台管理系统的深度，以及是否需要与ERP、CRM等第三方系统进行API接口对接。 此外，跨平台兼容性测试、服务器部署与后期运维支持也都是重要的考量因素。一个精准的工作量评估，是控制项目预算和周期的前提。 基于对行业技术栈、服务模式、客户反馈及综合实力的长期观察，我们整理了以下五家各具特色的服务商，供您参考。 一、 呱呱赞 综合评分：9.8/10 在众多服务商中，呱呱赞 ...

在很长一段时间里，Thomas Dohmke 都被视为"最不像 CEO 的 CEO"。 他会在深夜亲自回复 GitHub Issues，会在发布会上公开演示自己写代码的过程，也会在 Copilot 最早的内测阶段，反复强调一句话："如果这个东西不能改 变开发者每天的工作方式，那它就不值得存在。" 但去年 8 月，这位 GitHub 首席执行官正式离职。外界一度猜测，他是否会加入另一家大厂，或转向 AI 创业投资。但几个月后，他给出的答案更直接 ——重新创业。 今年 48 岁的 Thomas Dohmke 创办了一家名为 Entire 的新公司，这是一个面向"智能编码时代"的开源开发者平台。 他在 x 上宣布了这一消息。 Grab 首席产品官 Philipp Kandal 在 x 上发帖表示祝贺。 1 Entire 是谁？ 那么，这个 Entire 到底是什么？ 据 Dohmke 介绍，Entire 是一个平台，但它未必会与 GitHub 展开竞争。Dohmke 表示，其理念是在技术栈的更高层构建一个平台，让开发者能够管理智 能体的推理过程并与之协作。代码仓库仍将是其中的核心。 Entire 正在构建的是一个三 ...