Six months ago, while working on an internal productivity tool, our team made a controversial (at the time) decision: we'd build our repo with no human-written code. Every line in our project repository had to be generated by Codex.
大多数人认为软件开发必须由人类编写核心代码，但作者认为完全由AI生成代码是可行的，因为他们成功地构建了一个没有任何人工代码的仓库。这个观点挑战了软件开发的传统认知，暗示AI可能已经发展到能够独立完成整个项目的程度。
Even the ideal version, industrial megaprojects at hyperhuman scale while constantly being out over your skis with leverage sounds hellish.
大多数人认为大型AI项目和工业规模的发展是进步和繁荣的象征，但作者认为这种超人类规模的项目听起来像是地狱般的体验，因为它可能导致过度杠杆化和不可持续的压力。
We will continue improving the model's biological reasoning, expanding support for tool-heavy and long-horizon research workflows, and working closely with leading scientific institutions to evaluate real-world impact.
这一长期发展规划反映了AI科学应用的阶段性特征。从基础推理到复杂工作流程支持，再到实际影响评估，展示了AI如何逐步深入科学研究的核心，最终可能改变科学发现的本质。
As the cost of software development falls, trusted partners with broad adoption can expand faster than anyone else.
在开发成本下降的背景下，广泛采用和信任成为扩张的关键因素，这暗示AI时代的赢家可能不是技术最先进的，而是能够最快建立信任生态系统的公司。
Four researchers and software engineers estimated that a skilled human engineer would take 2 to 17 weeks to reimplement gotree, as AI successfully did in this work.
这一对比数据极具启发性，它量化了AI在特定任务上相对于人类的时间优势。这种时间压缩效应可能重塑软件开发流程，但也引发了关于AI能力与人类创造力本质差异的深层思考。
It is not common for real software to be developed the way MirrorCode tasks are structured — against a precise, programmatically checkable specification.
这一重要提醒指出了MirrorCode评估方法与实际软件开发之间的差异。虽然该基准测试提供了有价值的AI能力证据，但如何将这种能力转化为实际开发环境中的表现仍是一个开放问题，这对AI在真实世界软件工程中的应用提出了挑战。
It generated a build plan, then wrote all the code in 29 seconds.
令人惊讶的是：AI模型能在不到半分钟内完成完整的应用程序构建计划并编写全部代码，这展示了AI在软件开发领域的惊人效率，远超人类开发者的常规速度。
Agent harnesses dominate agent building and tie intimately to memory.
令人惊讶的是：代理工具(harnesses)已成为构建AI代理的主导方式，并且与记忆系统紧密相连。这表明AI代理的发展方向已经从单一功能转向了具有记忆能力的复杂系统，这种转变可能彻底改变人机交互模式。
Anthropic is expected to release Claude Opus 4.7 alongside a new AI-powered design tool for building websites and presentations
令人惊讶的是：Anthropic正在将Claude从聊天和编程工具扩展到完整的创意系统，推出能够从自然语言提示创建网站、幻灯片和完整产品的设计工具。这标志着AI竞争正从文本生成向全面的创意产品开发转变，模糊了技术与非技术用户之间的界限。
For example, developers can give an agent a controlled workspace, explicit instructions, and the tools it needs to inspect evidence:
令人惊讶的是：OpenAI的Agents SDK现在允许开发者创建一个完全受控的工作环境，让AI代理可以检查文件、运行命令和编辑代码。这种能力意味着AI系统可以更深入地与计算机系统交互，实现更复杂的任务自动化，这比大多数人想象的AI能力要强大得多。
There were 1 billion commits in 2025. Now, it's 275 million per week, on pace for 14 billion this year if growth remains linear
令人惊讶的是：软件开发提交量呈现爆炸式增长，从2025年的10亿个提交激增至每周2.75亿个，预计全年将达到140亿个。这种指数级增长反映了AI时代代码生成速度的惊人变化，远超线性预测。
Anthropic says Managed Agents is designed to cut the time it takes to move from prototype to production from months to days, with early adopters like Notion, Rakuten, Asana, Vibecode, and Sentry already using it across coding, productivity, and internal workflow automation.
令人惊讶的是：Anthropic的Claude Managed Agents将AI产品从原型到生产的时间从数月缩短到几天，这种加速不仅改变了AI开发周期，还吸引了包括Notion、Rakuten等知名企业立即采用，展示了AI基础设施服务对企业AI应用的革命性影响。
In the last year, we moved from manually editing files to working with agents that write most of our code.
令人惊讶的是：仅仅一年时间内，Cursor已经从手动编辑文件转变为让代理编写大部分代码，这展示了AI编程助手发展的惊人速度，暗示软件开发正在经历前所未有的范式转变。
McClary took the process from there, contacting the supplier himself to discuss the revised design. Within a month, the new version of the Guardian flashlight was back up for sale on Amazon and on his brand's website.
大多数人认为AI会完全取代人类在产品开发中的角色，但作者认为AI实际上增强了人类决策者的能力。Mike McClary使用AI工具缩短了产品开发周期，但仍需要亲自与供应商沟通并做出最终决策，这表明AI是辅助工具而非替代品。
The first wave of image models was mostly about making cool-looking images. This next phase is about making ordinary things look real.
大多数人认为AI图像模型的发展重点是创造越来越逼真的幻想艺术或创意内容，但作者认为下一阶段的重点是让普通日常事物看起来真实，这挑战了人们对AI图像发展方向的普遍认知。
Definitely true
just going back to the AI to the extent that the that the fourth turning meets the people who are actually doing the AI and informs the AI that actually the wheel goes this way don't listen to those guys it goes this way
for - AI - the necessity of training AI with human development - John Churchill
Hoffman, R., Mueller, S., Klein, G., & Litman, J. (2021). Measuring Trust in the XAI Context. PsyArXiv. https://doi.org/10.31234/osf.io/e3kv9
According to a 2015 report by Incapsula, 48.5% of all web traffic are by bots.
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The majority of bots are "bad bots" - scrapers that are harvesting emails and looking for content to steal, DDoS bots, hacking tools that are scanning websites for security vulnerabilities, spammers trying to sell the latest diet pill, ad bots that are clicking on your advertisements, etc.
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Content on websites such as dev.to are reposted elsewhere, word-for-word, by scrapers programmed by Black Hat SEO specialists.
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However, a new breed of scrapers exist - intelligent scrapers. They can search websites for sentences containing certain keywords, and then rewrite those sentences using "article spinning" techniques.