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AI 与未来

理解 AI——从上下文工程到构建可靠的 AI 产品。

面向开发者的实用 AI 写作：如何从 AI 工具获得优质结果、理解语言模型的实际工作原理、构建可靠的 AI 驱动产品，以及驾驭 LLM、智能体和上下文工程快速变化的格局。为希望更智慧地使用 AI 的工程师而写。

AI 与未来

Cognitive Debt in AI-Assisted Development: When Code Grows Faster Than Understanding

AI coding tools can make a team produce code faster than it can understand, review, debug, and safely operate that code. This article explains cognitive debt, how it differs from technical debt and intent debt, why agentic coding makes it more visible, and the practical controls teams can use: smaller batches, better PR rationale, human-owned invariants, disposable prototypes, and AI used to repay understanding instead of only generating more work.

15 分钟阅读
AI 与未来

Your Fear of AI Is the Size of Your Ambition: Why It’s Time to Aim Dramatically Bigger

Two people can look at the same AI breakthrough and feel opposite things — terror or fuel — and the difference reveals something uncomfortable: our fear of the future is roughly the size of our ambition. If your plan is to keep doing exactly what you do, a machine that does it cheaper is frightening. If your plan is to build something dramatically bigger, it’s the best news you’ve ever gotten. This is a clear, energising case for retiring “don’t boil the ocean,” trading the 1.05x present for the 10x future, and why — through ephemeralization and the Jevons paradox — raising your ambitions tends to create more, not less.

11 分钟阅读
AI 与未来

From SDLC to ADLC: How AI Agents Are Rewriting the Software Development Lifecycle

Software development is going through its biggest shift since the graphical interface. The phases engineers once ran by hand — planning, coding, testing, deployment — are increasingly executed by AI agents working in parallel. This is a clear, visual guide to the move from the classic SDLC to the emerging ADLC (Agentic Development Life Cycle): the two lifecycles drawn side by side, the six concrete shifts happening right now, what the early numbers suggest, what it actually means for an engineer’s day-to-day, and five low-risk best practices to start moving faster — without handing over the judgment that still has to be yours.

15 分钟阅读
AI 与未来

AI Agent 全解析：它是什么、如何运作、能为你做什么

所有人突然都在谈论“AI agent”——一种不只回答问题、而是真正去完成工作的软件。但 agent 究竟是什么？它和你已经在用的 chatbot 有何不同？它真正有帮助的地方在哪里，又在哪里会悄悄制造麻烦？这是一份面向所有人的友好、轻术语指南——无论你是否懂技术：每个 agent 运行的简单循环、构成它的五大要素、从 co-pilot 到 auto-pilot 的自主程度层级、工作与生活中接地气的示例、需要注意的失败模式，以及本周就能让第一个实用 agent 运转起来的具体方法。

17 分钟阅读
AI 与未来

从 Prompt 到 Workflow：设计每周为你省下数小时的 AI Workflow

大多数人每次只用一个问题来使用 AI——也因此把它的大部分价值留在了桌面上。真正的杠杆不是一句巧妙的 prompt，而是一个可重复的 AI workflow：你设计一次、便永远复用的一小串步骤，把每周两小时的重复杂活变成两分钟的审阅。这是一份面向所有人（无论是否懂技术）的实用、案例丰富的指南：prompt 与 workflow 的区别、每个 workflow 都共有的简单结构、可直接照搬到办公室与日常生活的 workflow、从手动到全自动的三个层级、自己动手设计的六个步骤，以及一个用来证明你真正省下多少时间的简易估算法。

18 分钟阅读
AI 与未来

2026 年真正值得你关注的 AI 趋势——以及如何把它们变成实实在在的价值

每周都冒出又一个“这将改变一切”的 AI 头条，想从噪音里分辨出信号，实在令人疲惫。这是一趟冷静、有据的导览，带你看清 2026 年真正重要的 AI 趋势——agentic AI、多模态（multimodal）、嵌进你已在用的 app 里的 AI、设备端 AI，以及判断力与核查作为人类优势的崛起——再配上几乎所有文章都略过的部分：一套把任何趋势变成工作与生活中真实价值的实用框架。你会得到一个“炒作还是价值”的过滤器、价值阶梯、一个简单的价值方程、一个具体例子，以及一份 30 天计划——好让你不再追逐新闻，而开始累积复利般的收益。

18 分钟阅读
AI 与未来

AI Is Rewiring Every Software Role: How Thinking Changes for BA, PO, PM, Dev, QA and Beyond

AI isn't just a faster tool bolted onto how we build software — it's quietly moving the center of gravity of every role. The work that used to define a BA, PO, PM, developer, or QA engineer is being automated from the bottom up, and what remains is a different job built on judgment, taste, and verification. This is a clear-eyed, role-by-role look at what's fading, what's rising, and what to watch out for as teams move from AI-assisted to AI-first — so you can see what may be lost, what's added, and how to stay genuinely valuable in a changed era.

21 分钟阅读
AI 与未来

Generative AI in Daily Life and Work: A Practical Catalog of What You Can Use Today

Generative AI has quietly moved from headline to household tool — yet most people still use it for little more than the occasional question. This is a hands-on catalog of the most common, genuinely useful applications across work, learning, creativity, and everyday life, organized so you can find at least one thing to try today. No hype, no jargon — just real use cases you can apply immediately, plus the one skill that makes all of them work and the limits you should never ignore.

16 分钟阅读