一、你的生意，正在被“够用就好”杀死

如果你的核心收入来自 “交付内容”——无论是配乐、文案、设计还是短视频——那么2026年对你而言，不是技术升级，而是一场生存危机。

客户不再需要“精品”，只需要“够用”。过去，一首定制化的游戏背景音乐（BGM），从需求对接到成品交付可能需要数天时间，费用在数百元到数千元不等。而现在，甲方只需在Suno这类AI工具中输入提示词，几分钟内就能获得一首可用作demo或氛围背景的完整歌曲，而其经济成本极低。

这并非简单的效率竞赛，而是价值重心的迁移：当AI能以极低成本覆盖大量基础需求，“专业服务”的默认必要性正在消失。

二、音乐人给出的答案：跳出“生产”，升级“定义”

AI与音乐的融合，已催生出全新的行业现象。国内，AI翻唱版《大东北》全网走红，流传度甚至超过原版，倒逼原唱袁娅维等艺人“反向翻唱”AI改编旋律；海外，AI虚拟歌手 Breaking Rust 创作的《Walk My Walk》，登顶 Billboard 乡村数字单曲销售榜，歌词传递的“不屈灵魂”打动无数听众。

知名游戏音乐制作公司小旭音乐也经历了AI的冲击。降价突围行不通——甲方直接用AI零成本生成即可；拓展音乐视频业务也碰壁——AI同样能完成基础剪辑。

团队最终的破局点，在于跳出“单一内容输出”的思维：客户要的不是音乐或视频本身，而是特定场景的氛围体验。

基于此，公司转型为“线下场景氛围解决方案服务商”，覆盖游乐园主题活动、文旅项目展演、商场开业庆典等场景，整合AI生成内容（背景音乐、主题视频）与真人表演（乐队、舞蹈）、现场布置等环节，提供一站式氛围体验服务。

三、真正的危险，不是AI太强，而是你还在原地交付

许多决策者误以为“学会AI工具”就能破局。但工具只是杠杆，方向才是支点。

如果你仍在比拼“更快出图”“更便宜配音”或“更多模板”，本质上只是在为AI提供训练数据，而非构建竞争壁垒。真正的机会，属于那些用现成AI能力重构自身价值的人。

正如《易经》所言：“时乘六龙以御天”——真正的智者，不与天争力，而是顺势御之。

这一逻辑已被前沿实践验证：2025年年末，Meta以超20亿美元收购AI智能体公司Manus，创下国内AI团队最快被并购纪录。而Manus的成功，恰恰不在自研大模型，而在其“最佳体验整合者”的定位——通过多模型架构，灵活调用包括阿里通义千问（Qwen）在内的先进基座，构建出能理解意图、自主规划并执行复杂任务的智能体系统。

他们的护城河，从来不是算力，而是对用户痛点和场景的理解，以及将技术转化为价值的能力。

四、下一步：别独自摸索，先厘清你的“AI融合层”

在AI成为基础设施的今天，理清AI融合方案的关键，早已不止是找到“AI高效替代”与“人的不可替代”的平衡点，更要深入思考：你最不可替代的那一层，究竟是什么？

真正的升维，始于清醒认知：AI不会直接取代你，但会加速淘汰那些拒绝重新定义自身角色的人。与其对抗浪潮，不如驾驭它——打不过，就骑上去，然后带它去从未抵达的地方。

如果你仍在探索行业中的AI融合路径，尚未理清自己的高价值锚点，欢迎交流。我们一起梳理：在人机协同的新范式下，你该如何构建无法被自动化替代的护城河。

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I. The “Good Enough” Trap is Killing Your Margins.

If your core revenue comes from “deliverables” — code, copy, design, or scoring — 2026 isn’t just another year of tech updates. It’s a survival crisis. Not because AI is extraordinary. But because “good enough” is now almost free.

II. How Musicians Responded: Stop Producing. Start Defining.

The music industry was one of the first to feel this shock. We saw AI-generated tracks, such as Breaking Rust’s “Walk My Walk,” top the Billboard charts by tapping into raw human sentiment. We saw icons like Yuan Yawei “reverse-cover” AI versions of their own songs to reclaim the narrative.

But the most instructive response wasn’t about competing with AI on output.

It came from a pioneering Chinese game-audio studio, Xiaoxu Music, which asked a far more uncomfortable question: Why do clients hire us at all? The answer was clarifying. Clients weren’t buying music. They were buying atmosphere.

The Shift: They transformed from a content shop into an Experience Architect.

They began delivering end-to-end immersive solutions for theme parks, cultural tourism projects, shopping centres, and live events — integrating:

• AI-generated music and visual content
• Live performers and musicians
• Physical staging, lighting, and spatial design

AI didn’t replace them; it became the invisible engine inside a new, higher-value layer.

III. The “Manus” Signal: Leverage vs. Fulcrum

Many leaders still believe the solution is simple: “Teach the team AI tools.” That’s necessary — but insufficient. Tools are leverage. Direction is the fulcrum.

In late 2025, Meta acquired Manus for over $2 billion. Manus didn’t win by building the biggest LLM. They won by being the Ultimate Orchestrator. By layering models (like Alibaba’s Qwen) and focusing on the Agentic Layer — the ability to understand intent, plan complex tasks, and execute across silos — they proved that the “Moat” is no longer in the math, but in the integration of the human problem.

As the I Ching, or Book of Changes, suggests: “Ride the six dragons to steer the heavens.” The wise don’t fight the storm; they harness the wind to go where others cannot.

IV. The Question Every Decision-Maker Must Answer

In an AI-saturated world, the strategic challenge is no longer: “What can AI replace?”

The real question is: “What layer of value am I uniquely qualified to own?” Call it your “AI Fusion Layer.” AI will rapidly eliminate roles, products, and companies that refuse to redefine themselves. So don’t wait for the rules to settle. They won’t.

If you can’t beat the wave — ride it. And take it somewhere it has never been.

Are you still figuring out your AI Fusion Layer? Let’s connect to discuss where your moat lies in the age of the Agent.

We’ve reached the final days of 2025. A familiar question comes up: “If you had to summarize this year in one word, what would it be?”

In the ancient wisdom of the I Ching, the word of the year is “Ge” (革). It translates to “Revolution,” but its etymology is far more profound for decision-makers: It means stripping the fur from rawhide to create leather.

Layoffs at major tech firms, the once-unthinkable automation of elite consulting and legal work, and long-standing AI warnings suddenly becoming lived reality — what used to feel abstract now feels personal. For decision makers, this year wasn’t about curiosity. It was about survival.

In moments like this, we need perspective — one that cuts through fear, respects human nature, and helps us act with clarity.

I. The Pivot: From “Inertia” to “Architecture”

There is a line from the 2025 blockbuster De Xian Jin Zhi that haunted many executives this year: “It is what it is, and it’s already like this.”

It is the mantra of survival inertia. It is the sound of a decision-maker acknowledging that market logic has failed and deciding to simply weather the storm. But in the era of AI rule-rewriting, inertia is fatal.

In the ancient wisdom of the I Ching, each year is associated with a guiding hexagram. 2025 corresponds to the 49th hexagram, Ge (Revolution) — a symbol of profound transformation through the deliberate removal of what no longer fits.

The Strategic Pattern Behind AI Winners

Look at where real breakthroughs happened this year:

• The Hardware contrarians: While the world fought for GPU allocation in a brute-force arms race, Lightelligence went back to first principles. They ignored the silicon rules and bet on optical computing (photonics). They didn’t try to run faster in the old race; they changed the physics of the track.

• The Service Architects: Legal AI unicorn Harvey didn’t just build a “chatbot for lawyers.” Knowing a faster horse won’t fix a broken cart, they redesigned high-stakes legal workflows — freeing attorneys from document drudgery to focus on judgment, strategy, and client trust.

Different industries. Same pattern:

Stop chasing optimization inside a collapsing framework. Start defining a new one.

II. The Anchor: Emotional Sovereignty in a “Mocha” World

Innovation requires adrenaline, but endurance requires calm.

It is no coincidence that amidst this technological velocity, Pantone selected “Mocha Mousse” (17–1230) as the Colour of the Year for 2025, a warm, grounded, unassuming brown.

Why does this matter to a tech executive? Because the greatest risk to your company right now isn’t a competitor’s algorithm; it is your own burnout.

The cognitive load of 2025 — managing AI integration, calming investor nerves, navigating geopolitical shifts — requires a psychological anchor. “Mocha Mousse” is a reminder that high-tech requires high-touch.

The most resilient founders I worked with this year were those who protected their “offline sovereignty.” Share unhurried dinners with family. Go for walks with no purpose. These are not distractions from the work; they are the fuel for the high-stakes decision-making required.

For leaders navigating AI-driven change, emotional sustainability is now a strategic asset.

III. The Structure: The Era of the “Leaderless Dragon”

At the end of 2025, there is no need to dwell on past instability, nor to be overwhelmed by future uncertainty. Use your willpower to adapt to change.

Use your hands of creation to build new rules.

In the I Ching, Qian Gua offers a powerful image: “A group of dragons without a leader — auspicious.” When centralized authority dissolves, and old power structures fade, the roots of certainty may blur — but in that ambiguity, everyone gains the chance to rise. The true good omen is not waiting for instructions, but awakening the initiative within each person — calmly observing the situation, then acting with clarity and resolve.

2025 is a year of revolution — and also the beginning of a new order. In this once-in-a-century transformation, may you and I choose not to become floating objects carried by the waves, but architects who lay the first stones ourselves.

Let us use wisdom to break through.

Let us use warmth to protect our hearts.

Let us use creativity to keep moving forward.

History has never been written by observers. It is written by those who walk through the darkness — and still choose to light the way.

Step by step.

Ready to Shape Your 2026?

As we move from the year of “Disruption” to the year of “Reinvention,” the window for strategic positioning is narrowing. Let’s turn these insights into your competitive advantage.

For Our Valued Clients & Partners: It’s time to activate your roadmap. Please use your 2025 Value Code to schedule your exclusive 2025/2026 Year-End Strategy Session. We will dive deep into your specific “tanning process” and calibrate your operations for the distributed agency of the coming year.

For New Visionaries & Prospective Partners: If you are ready to move beyond the “raw hide” of AI and into market-ready leadership, we invite you to connect. We are currently opening a limited number of briefings on:

1. The 2025 Winners’ Ledger: Deconstructing the most successful case studies of the year.
2. The China Frontier: Vital policy updates and navigating the evolving regulatory landscape.
3. Strategic Collaboration Sessions: Identifying high-alpha partnerships for the 2026 cycle.
4. The “Mocha” Moment: An exclusive New Year’s Eve online meditation to sharpen your executive focus for the year ahead.

Contact Us

2025年即将合上最后一页。每到岁末，圈内朋友总问：“若用一个字总结这一年，会是什么？”今年的答案，不约而同地指向同一个字：革。

这一年，AI浪潮席卷而来，大厂裁员的消息与咨询行业金领被智能工具替代的案例交织，曾经被视作遥远警示的图灵奖得主辛顿的AI警告，正在化作每个创业者切身可感的生存压力。

低迷的气氛里，我们需要一种穿透迷雾的视角——或许可以从千百年来的东方智慧、一部年度电影的精神内核，以及一抹年度色彩的隐喻中，找到前行的底气。

一、 破局：从“惯性生存”到“主动制革”

“应该是这样，已经是这样了。”电影《得闲谨制》中，肖战饰演的莫得闲这句口头禅，像一面镜子照见了动荡年代里许多人的生存惯性。这个原本只想在战火中苟全性命的工匠，栖身于名为“戈止镇”的避世村落，却终究逃不过时代洪流的裹挟，从被动求生走向主动抗争。恰如今年我们所处的商业环境，许多人习惯了既定的商业模式与增长路径，直到AI重构行业规则、市场逻辑发生剧变，才猛然发现“已经是这样了”的惯性，早已成为前行的桎梏。

这份时代的剧变，与《皇极经世》所推演的2025年值年卦——革卦，形成了跨越时空的呼应。《周易》第四十九卦革卦，以“水火相息”为象，象征两种根本力量的对峙与转化。变革从来不是灾难，而是新生的前奏。

《说文解字》释“革”为“兽皮治去其毛，革更之”——将生皮转化为可用之革，靠的不是天赐，而是人的主动作为。真正的变革，是剔除不再适配的部分，以智慧重建价值体系。

这一点，在2025年的人工智能应用元年尤为清晰。面对大模型的算力瓶颈，中国曦智科技没有卷入GPU的军备竞赛，而是回归物理原理，以光子芯片这一底层范式革新寻求突破，其宣称在特定计算任务上实现了能效的跨越式提升，并已在金融仿真、药物发现等前沿领域展开探索。

无独有偶，法律AI先锋 Harvey 面对顶级律所的谨慎，并未停留在工具替代，而是致力于重构律师的工作流——通过将AI深度融入研究、审阅与推理环节，帮助律师从海量文档中解放出来，将精力聚焦于真正需要高阶判断与战略决策的领域。

二者路径迥异，但内核相通：它们都放弃了在旧规则下的苦苦追随，转而成为新规则的定义者。

二、守心：以内在定力滋养持久创造

我们再也回不到没有AI的从前。但历史从无回头路，只有一代代人以血肉与智慧铺就的前行轨道。我们的祖先曾“做的事没人晓得，拿血和着，写在泥巴里”，才换来今日我们站在牌桌上的资格。恐惧未知是人之常情，但创业者之贵，在于明知不可为而为之的勇气。毛泽东曾言：“困难是纸老虎。”此语今日听来，并非轻慢现实，而是提醒我们：办法永远生长在行动的土壤里。

九层之台，起于累土。真正的变革从不靠一夕顿悟，而在日复一日的微小坚持。“人心不死，灯芯不灭”——只要初心尚在，心力未竭，便始终握有翻盘的筹码。

而这份在变革中坚守的心力，需要温暖的滋养与内在的平静作为支撑。值得玩味的是，潘通（Pantone）将2025年度代表色定为 “摩卡慕斯”（PANTONE 17-1230） —— 一种温润、沉静、略带甜意的棕调。它不张扬，却深具包容；不炽烈，却持久温暖。

在全球震荡的背景下，这一选择仿佛是一声温柔的提醒：在追求颠覆的同时，勿忘回归内在的平静与人际的温度。与家人共度的晚餐、与挚友深夜的长谈、一次不带功利目的的散步……这些看似“无用”的时刻，恰是滋养创造力的隐秘源泉。

三、开路：群龙无首，人人皆可为光

岁末之际，无需为过往的动荡焦虑，也不必为未来的未知惶恐。革卦的智慧早已告诉我们：变革之时，顺天应人则大亨贞；《得闲谨制》的故事也在提醒，每个平凡人都能在绝境中完成蜕变；而摩卡慕斯的温暖，则为我们在变革中守住了心灵的锚点。

《易经·乾卦》有云：“现群龙无首，吉。” 当权威消解、路径模糊，反而人人皆可成为光。真正的吉兆，不在于被动的等待指引，而在于每个个体觉醒自身的能动性——以清醒之眼观势，以坚韧之心应变，以创造之手立新。

2025年，是革故之年，亦是鼎新之始。

愿你我在这场百年未有之大变局中，不做被浪潮裹挟的浮萍，而为亲手制革的匠人——以智破局，以温守心，以创开路。毕竟，历史从不由旁观者书写，而由那些在黑暗中仍敢点灯的人，一笔一划，得闲谨制。

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一、最优解的困境：为何 “为你好” 换不来认同？

你一定遇过这样的困境：苦口婆心劝父母按时吃药、用健康设备，他们却敷衍、回避，甚至抵触。明明是 “为你好” 的最优选择，为何换来沉默或反抗？科技的进步似乎给了我们所有解决方案 ——AI 答疑、远程监控、数据监测，但我们恰恰忽略了最核心的变量：人。

直到读到《李飞飞传》中那个扎心的故事，我才读懂这道困境背后的人性密码。

二、一场本可避免的手术：李飞飞母亲的 “尊严反抗”

人工智能教母李飞飞的母亲心脏欠佳，经历过多次手术。一次术后，医生强调康复关键是用 “诱导性肺量计” 训练肺部，方法简单、益处明确。可无论是医生叮嘱还是李飞飞劝说，母亲始终阳奉阴违 —— 有人监督时吸一口气，人一走仪器就被弃置一旁。

最终，左肺积液引发感染，她不得不承受额外的引流手术，一场本可避免的创伤。

回家后，李飞飞终于等到母亲的心声：

“当病人太可怕了。不是痛，而是失控。病房里，我的身体甚至念头都不属于自己。医生、护士，连你都在给我下指令，那种失去尊严的感觉，我忍不了。我不是拒绝仪器，是在抵抗失控。那一刻，健康都没有尊严重要。”

三、抗拒的本质：人不是系统，是需要自主的 “生命体”

这段话如同一道闪电，照亮了长久以来的认知盲区：人抗拒的从来不是 “好处”，而是 “被安排” 的感觉。

随着年岁增长，父母逐渐失去体力、记忆、社会角色，唯一能紧握的，只剩“还能为自己做主”的尊严。而我们脱口而出的“最优解”——哪怕裹着爱的外衣——在他们听来，却是“你不行了，得听我的”。这不是沟通失效，而是人性深处对自主权的本能捍卫。

科技加速的时代，这种认知偏差被无限放大。AI 自动化任务、算法预测行为、数据优化习惯，我们渐渐相信所有问题都有 “最优解”，所有人都该遵循 “最优路径”。这种思维不仅支配着我们自己的生活，更被投射到他人身上 —— 我们试图用数据优化父母的行为，用流程规范团队的习惯，用效率标准要求伴侣的选择，却忘了人从来不是可以被编程的系统。

四、商业镜像：AI 管理的 “人性反弹” 与 30% 效率提升启示

这股 “抵抗失控” 的暗流，正从家庭蔓延至整个商业社会。某互联网大厂曾推出一套精密的 AI 管理系统，能实时量化评估员工效率，自动优化工作流。工具的初衷无疑是提升效能，结果却引发强烈抵触。员工感到自己不再是创造者，而是被观测、被校准的‘系统组件’。

直到产品迭代，引入员工自主设定目标与弹性调整流程的模块，将一部分控制权归还，团队效率反而实现了超过 30% 的真实提升。

这恰是一个时代的隐喻：当科技试图消除一切 “不确定性”，人性中那股对 “自主定义” 的渴望，便成了最顽固的 “系统误差”。

五、温度大于最优解：从家庭到团队的 “自主赋能” 实践

真正推动人改变的，从来不是冰冷的最优解，而是带着温度的理解与尊重。父母不是拒绝健康，而是拒绝 “被安排”。我给父母推广呼吸练习时，没有下指令，而是每天抽出半小时陪他们一起练，把健康任务变成家庭互动；出差时，我录制了呼吸跟练版，让他们能自主选择练习时间。

正如《掌控习惯》中詹姆斯・克利尔所言：

习惯养成的核心是重复，但重复的前提是自愿与愉悦。

这一逻辑在团队管理、创业决策中同样适用。我们追求效率、规模与可复制性，但真正的组织凝聚力，源于让每个成员感受到 “我的选择被尊重，我的价值被看见”。创始人若只强调 “最优路径” 而忽略团队的情感认同，再完美的计划也难以落地；高管若只追求 “效率提升” 而无视员工的适应节奏，反而会引发抵触。

六、估值新维度： “人性系数” 如何定义价值？

拉高视角，这一洞察甚至能重塑我们评估科技公司的维度。一个产品的真正价值，不仅在于算法多精准、数据多庞大，更在于它是否增强而非削弱使用者的主体性 —— 是让人更依赖、更被动，还是在赋能的同时，让人感受到更多的掌控与尊严？

这将是未来区分伟大产品与平庸工具的关键准绳，是商业的胜负手，也是投资人亟需纳入考量的 “人性系数”。

在这个算法试图规划人生的时代，请谨记：人之所以为人，不在于追求最优解的理性，而在于保有恐惧、情绪与尊严的温度。

无论是对待父母、团队还是伴侣，真正的关心，从来不是 “我为你安排了最好的路”，而是“我理解你的选择，也愿意陪你同行。” 这，才是科技洪流中最值得守护的人性底线。

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We’ve all felt this frustration: you lay out the perfect health plan for your parents — take the medication on time, use the monitor, follow the doctor’s instructions. The solution is clear, the reasoning is airtight. Yet what comes back is all too familiar: silence, avoidance, a gentle “I know, I know…,” or a quiet refusal.

We live in an age where AI seems to have an answer for every problem. Models analyze our decisions, devices track our vitals from miles away, and remote systems flag warning signs before symptoms arrive.

But there’s one dimension no algorithm can fully account for: the human response. People don’t move on logic alone — they move on emotion, identity, and the need to feel in control. And that’s often where the “best solution” meets quiet resistance.

Fei-Fei Li, a globally recognized AI pioneer, shares a powerful personal story about her mother that reveals this truth with heartbreaking clarity.

Part I: A Surgery That Didn’t Need to Happen

Her mother had long suffered heart issues and endured multiple surgeries. After a recent operation, the doctor emphasized one essential step for recovery: using an incentive spirometer, a simple device that helps patients strengthen their lungs and avoid complications.

The instructions were simple, the benefit clear — “Just use it. It’s good for you,” everyone said. Yet she resisted: lifting the device only when watched, setting it aside the moment she was alone. As a result, she endured a second surgery that never should have happened.

After returning home, the mother finally revealed her truth:

“In that hospital room, my body, even my thoughts, no longer belonged to me. Doctors, nurses, even you — you were all giving me orders. I felt stripped of my dignity. I wasn’t refusing the device. I was refusing that feeling of being powerless.”

In that moment, dignity mattered more than health. She was pushing back not against the practice, but against the feeling of being arranged.

Part II: The Business Mirror — This Isn’t Just Personal — It’s Strategic

The same dynamic we see in families echoes through organizations. 

A major tech company rolled out an AI management system to track productivity, optimize workflows, and automate task assignments — all in the name of “ruthless efficiency.” 

The system worked, but the results were catastrophic for morale.

Employees felt they were no longer creators, but components inside a transparent, ever-watchful machine. They feared becoming adjustable, measurable, and replaceable parts.

In version 2.0, they flipped the script: AI became a co-pilot, not a commander. Teams set their own goals, shaped their workflows, and retained meaningful control. Result? A 30% sustained boost in efficiency — plus faster innovation.

Part III: Why the “Best Solution” Isn’t Enough

Across every context — health, leadership, innovation — the same principle holds:

People don’t change because a solution is brilliant.
 They change when they feel seen, respected, and included.

My parents weren’t rejecting breathing exercises. They were rejecting being instructed. So instead of teaching them, I practiced with them —  half an hour every day. When I travelled, I recorded an audio guide so they could choose their own pace.

James Clear writes in Atomic Habits: “Repetition is the foundation of change.” But repetition requires desire, not pressure.

This applies universally:

• Teams adopt AI when they feel part of the design.
• Employees innovate when their pace is respected.
• Partners collaborate when their autonomy is protected.
• Families accept guidance when dignity is intact.

Part IV: The New Altitude of Value — Introducing the Human Quotient (HQ)

For founders and investors, this is not “soft philosophy.” It is a hard valuation principle that determines the longevity and success of your venture. We need a new metric to evaluate technology: The Human Quotient (HQ).

Traditional technology assessment focuses on precision, scale, and data: How accurate is the model? How fast is the computation?

The HQ asks the deeper question:

Does this technology expand human autonomy or shrink it?

This distinction will define the difference between enduring companies and disposable tools. The next generation of trillion-dollar companies will be those that build systems where humans feel amplified, not arranged.

Part V: What We Cannot Automate

As AI becomes more predictive and prescriptive, it’s tempting to believe the “best solution” will always win.

But humans don’t operate like code. We carry pride, fear, intuition, and dignity.

Real care — whether in families, teams, or organizations — is never: “I’ve already planned the best route for you.”

Real care is: “I understand your choices, and I’m willing to walk with you.”

In an era defined by AI and automation, the most powerful force isn’t processing speed, predictive accuracy, or algorithmic efficiency — it’s the irreducible core that no machine can replicate:

• Human autonomy.
• Human dignity.
• Human connection.

As technology reshapes everything, remember: the future won’t be won by the smartest system, but by the one that best serves the human spirit.

一、开篇：现象背后决策者必须正视的战略信号

2025 年初，全球技术圈出现了一个反常现象：开发者写代码的时间越来越少，但软件迭代速度却越来越快。推动这一变化的，并非某种新的编程语言或框架，而是由AI原生开发理念催生的新范式——Vibe Coding（氛围式编程）。

当特斯拉前 AI 负责人 Andrej Karpathy 说出这个词时，它像是为时代命名：人类不再逐行编写代码，而是通过自然语言向AI传递业务意图，由系统自动转化为可执行逻辑。

它不是玩笑，而是范式切换。

这种转变在中美市场呈现出截然不同的战略取向：

• 美国某头部CRM平台借力Vibe Coding，将企业系统实施周期缩短近40%，追求效率最大化；
• 中国某国有银行在AI生成代码过程中嵌入监管规则校验机制，使金融系统合规审计通过率提升至98%以上，优先保障风险可控。

这种在“效率优化”与“风险控制”之间的不同侧重，正在塑造未来五年全球科技企业的竞争格局。对决策者而言，关键挑战不在于是否采用 AI 编程工具，而在于如何基于本地实践环境，制定适配自身战略目标的技术路线。

二、编码四阶段演进：区域实践路径的分化与延续

Vibe Coding 的演进历程，反映出不同市场在技术采纳上的结构性差异。

1. 语法时代（2020年前）：标准化协作 vs 个体经验积累

全球开发者长期面临重复性编码负担——从 Java 接口适配到 iOS 兼容性调试，大量时间消耗于非核心任务。但应对方式存在差异：

• 阿里巴巴在 2018 年推出开源插件 P3C，推动代码规范统一，有效减少了因风格不一致或模式误用导致的问题，体现了对团队协作效率的重视；
• 在美国，开发者更倾向于依赖个人经验与社区共享资源。“Cheat sheet”、“Developer roadmap”等知识整理型项目广受欢迎，反映出对个体能力建设的侧重。

2. 模式时代（2020–2023）：通用能力扩展 vs 垂直场景适配

中国路径侧重垂直场景提效：阿里巴巴等企业针对高频业务（如“618满减规则+库存扣减”）构建领域专用代码模板，实现“输入意图，一键生成”。这种做法源于实际需求——许多团队发现，通用 AI 生成的代码常需大量调整，唯有紧密结合业务上下文，才能确保交付质量。

美国路径聚焦通用能力放大：GitHub Copilot 至2023年已触达千万级开发者，其核心逻辑是利用全球开源代码中的常见模式，辅助个体提升产出效率。YC 导师普遍将其视为早期团队加速MVP开发的关键工具。GitHub 研究显示，开发者借此平均可节省约18%的开发时间。

两种路径体现出不同的技术采纳逻辑：

• 一种强调通用智能的广泛适用性，
• 一种追求特定场景下的执行确定性。

3. 意图时代（2023–2025）：资本驱动 vs 合规导向

• 在美国，AI 原生开发工具成为风险投资热点。红杉资本在《State of AI 2024》中指出，“开发者正从写代码转向描述行为”，并将相关工具列为关键投资方向。Cursor 等新型 IDE 凭借“自然语言生成多租户 SaaS 系统”的能力快速获得市场关注。
• 在中国，AI 代码生成的落地更强调治理与合规。阿里巴巴、华为等企业在金融、政务等高敏感领域引入代码安全审查机制，对 AI 输出实施审计与权限管控。部分初创企业反馈，为满足大型客户供应链准入要求，需投入额外资源完成合规认证——在此类场景中，确定性优先于速度。

两种路径反映了不同的优先级设定：

• 一方更关注创新速度的提升潜力，
• 一方更注重执行过程的风险管理。

4. Vibe时代（2025–）：组织形态演化 vs 执行效率深化

• 在美国，小型团队借助 AI 工具实现高杠杆产出。多家 5 人以下团队在数月内完成传统需数十人才能交付的产品，重新定义了技术团队的规模效率边界；
• 在中国，AI 应用更多聚焦于现有业务流程的优化。例如，阿里“鹿班”帮助淘宝商家通过自然语言生成营销页面，设计周期缩短 70%；SHEIN 利用 AI 优化供应链逻辑，持续降低库存周转天数。其核心思路是：在既有体系内最大化执行效能。

三、结语：战略视角下的技术路径选择

Vibe Coding 正加速全球软件产业的结构性调整—— 美国推动通用开发范式的技术标准制定，中国则以垂直领域深度与行业定制化精度实现精准落地。这种分歧不仅是技术路径差异，更体现了软件定义世界中两种不同的 “价值实现逻辑”。

孙子兵法有云：“势者，因利而制权。”

用现代商业语言诠释便是：“真正的杠杆并非与生俱来，而是通过对当下市场优势的识别与利用主动构建而成。”

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Ⅰ. The Shift: From Authoring to Directing (The Strategic Signal)

The software industry is currently facing a paradoxical phenomenon: developers are spending less time writing code, yet software iteration speed is accelerating faster than ever before. This change is driven not by a new programming language, but by the AI-native paradigm known as Vibe Coding.

As former Tesla AI Director Andrej Karpathy coined the term, it provided a name for the era: humans no longer write code line by line; we transmit business intent via natural language to an AI, which automatically translates it into executable logic.

This is not merely a development tool; it’s a paradigm shift.

This transformation presents two opposed strategic pathways in the global market:

The US Path: Efficiency Maximization

The US Strategy is Efficiency-Driven, a manifestation of the Silicon Valley mandate: maximize speed and scalability. The focus is on Core Logic and Customization as the ultimate lever for competitive advantage. For instance, a top CRM platform successfully utilized AI-generated customized logic to reduce enterprise system implementation costs by over 40%. This is not a cost-cutting measure; it is a capital acceleration strategy.

The overriding goal is the strategic pursuit of efficiency maximization to secure a competitive edge through market velocity, rapid product iteration, and organizational reinvention.

The China Path: Risk-Controllability Priority

In contrast, China’s approach emphasizes system stability, auditability, and governance. The focus is on Compliance and Safety. A major state-owned bank, for example, embedded regulatory checks directly into AI-generated code, resulting in audit pass rates exceeding 98%.

The foundational goal is ensuring risk and compliance alignment so that the speed of AI does not introduce fragility into critical sectors.

This difference—speed-focused optimization versus stability-focused governance—is an important signal for global tech executives.

II. The Evolution of Code: Where U.S. and China Diverge Strategically

Vibe Coding did not appear overnight. It is the natural continuation of decades of shifts in how software is produced. Yet beneath this evolution lies a deeper truth: U.S. and Chinese enterprises made fundamentally different choices at each stage, and these choices now shape their Vibe Coding trajectories.

1. The Syntax Era (pre-2020): Repetition Reveals Two Philosophies

For over a decade, developers in both markets were weighed down by repetitive, low-value tasks — from Java interface plumbing to iOS compatibility debugging. But how each ecosystem responded foreshadowed today’s strategic split.

The U.S. doubled down on individual leverage.

Developers relied more on personal expertise and community-driven resources such as cheat sheets, “developer roadmap” repositories, and decentralized best-practice guides. The design assumption leaned toward individual autonomy in workflow decisions.

China prioritized collective efficiency.

As early as 2018, Alibaba open-sourced the P3C plugin to enforce unified coding conventions across teams. By eliminating style inconsistencies and common anti-patterns, P3C dramatically reduced avoidable defects. It became an early symbol of China’s preference for organizational consistency over individual preference.

These early choices — individual ability vs. collective efficiency — laid the strategic foundation for the next decade.

2. The Pattern Era (2020–2023): General Intelligence vs. Vertical Precision

As AI-assisted coding entered the mainstream, both markets again made opposite bets.

The U.S. pursued generalized innovation.

GitHub Copilot scaled to tens of millions of developers by 2023, accelerating coding through pattern prediction across the global open-source corpus. GitHub’s research showed an average 18% productivity gain, with a significantly higher impact for tasks that involve boilerplate code. YC mentors even called Copilot an “MVP accelerator” for early-stage teams.

The underlying belief: If a tool enhances individual capability, innovation will propagate organically.

China focused on deep vertical optimization.

Chinese companies built domain-specific templates tied tightly to real business logic—such as complex “618 promotion rules + inventory deduction” workflows—allowing developers to input intent and instantly generate compliant code. Many teams reported that generic AI outputs required heavy rework, while business-bound templates delivered predictable, ready-to-ship results.

This produced a second divergence:

• The U.S. bets on general-purpose intelligence spreading across industries.
• China bets on execution certainty through domain-specific depth.

3. The Intent Era (2023–2025): Capital Acceleration vs. Compliance Firewalls

As natural-language development became feasible, the two markets moved even further apart.

The U.S.: Innovation accelerated by capital.

Sequoia’s State of AI 2024 highlighted a structural shift: “Developers are moving from writing code to describing behaviour.” Tools like Cursor—capable of generating multi-tenant SaaS systems from natural language—became new VC darlings. The investment thesis was simple:

Intent → Execution = exponential innovation speed.

China: Regulatory alignment and risk containment.

Chinese enterprises reinforced governance frameworks to manage uncertainty in AI-generated code. Alibaba, Huawei, and major financial institutions embedded code-security reviews, audit trails, and permissions controls into the development pipeline. Startups entering large enterprise supply chains reported significant compliance investment as table stakes.

Here, the divergence becomes structural』: The U.S. chases the speed threshold where innovation compounds. 『China builds a compliance framework where innovation aligns with system stability. These differing priorities reflect variations in regulatory environments, industry structures, and investment incentives.

4. The Vibe Era (2025– ): Organizational Reinvention vs. Execution Intensification

In 2025, Vibe Coding enters its fourth stage.

The U.S. path: “Small teams, larger output.”

Sub-5-person teams now ship products that previously required dozens of engineers and months of work.

The definition of “technical leverage” is being rewritten:

The unit of innovation is no longer the team, but the individual amplified by AI.

The China path: Scaling operational throughput.

Large enterprises use Vibe Coding workflows to enhance existing systems at scale.

Examples include:

• Alibaba’s “Luban,” which reduces design cycles by 70%.
• SHEIN’s AI-optimized supply-chain logic is improving turnover speed.

The logic:

• The U.S. uses AI for new-market creation and product velocity.
• China uses AI for system-level refinement and execution density.

Both strategies are rational, and both create competitive advantages.

III. Closing: The Strategic Commandment

Vibe Coding is accelerating a global shift in software development, where the U.S. focuses on universal development paradigms while China emphasizes domain-specific precision and governance. These differences stem from structural market conditions rather than cultural characterization.

A classical strategic principle applies here:

Sun Tzu’s The Art of War states:

 “势者，因利而制权。” In modern business terms: “True leverage is not inherent; it is manufactured by recognizing and exploiting current market advantages.”

I. Opening: The Next Wave After AI

While Artificial Intelligence has defined the last decade, it remains constrained by classical computation — unable to fully capture the complex probability spaces that govern natural phenomena, such as molecular quantum behaviour.

Quantum systems, by contrast, compute through superposition and entanglement — the very mathematics of uncertainty.

When AI merges with quantum algorithms, the outcome is more than faster processing — it marks the dawn of a new paradigm for reasoning, creativity, and discovery.

II. Case — Insilico Medicine: Quantum + AI, Redefining Drug Discovery

Drug development is notoriously slow and costly — often taking over 10 years and costing around $2 billion per approved drug, with high failure rates due to the limitations of classical simulation.

Quantum computing aims to change that.

According to McKinsey, by 2035, quantum applications in life sciences could create up to $2 trillion in value, driven by advances in molecular simulation and protein folding.

In my book Strategic Development of Technology in China, I introduced Insilico Medicine, a pioneer in AI-driven drug discovery and among the first to explore integrating quantum computing with generative AI.

Its Variational Quantum Eigensolver (VQE) — a leading hybrid quantum-classical algorithm — has demonstrated improved molecular energy estimation accuracy, potentially enhancing drug target modeling.

By 2025, Insilico used a quantum-enhanced generative model to design novel molecules targeting KRAS mutations, one of the toughest challenges in oncology, achieving verified biological activity in early testing.

By combining quantum’s computational power with AI’s predictive intelligence, Insilico exemplifies how the two technologies can create a powerful synergy — accelerating discovery and redefining what’s possible in drug development.

III. Turing Test 2.0 — From Industrial Tools to Cognitive Engines

McKinsey’s long-term outlook (2040+) envisions quantum computing not merely as a faster processor, but as a cognitive amplifier — enabling humanity to simulate aspects of reality once unreachable by classical computation.

The true test of intelligence may ultimately lie at the intersection of information theory and the laws of nature.

Redefining the Test of Intelligence

The Classic Turing Test
Evaluates whether a machine can mimic human conversation well enough to appear intelligent — rooted in a deterministic, logic-based framework.

The Quantum Turing Test (QTT)
Extends this idea to ask whether an artificial system can model and reason within a quantum world of uncertainty and indefinite causality — a challenge that touches the frontiers of quantum gravity and computational theory.

Though still theoretical, the QTT expands our understanding of what “intelligence” could mean in a universe that resists deterministic explanation.

The New Definition of Intelligence

This shift reframes intelligence itself — 
 from seeking absolute, predictable answers,
 to building self-consistent, adaptive models capable of operating amid fundamental uncertainty.

IV. Conclusion: Embracing the “Superposition Mindset”

The story of quantum is the story of humanity learning to master uncertainty.

From Einstein’s doubt — “God does not play dice” — to Insilico Medicine accelerating drug discovery with quantum-inspired algorithms, science has transformed uncertainty into strategy.

For decision makers, the key is adopting a Superposition Mindset:

In an age of rapid technological change, the future isn’t binary — it’s entangled, with multiple possibilities unfolding at once.

To lead in the quantum-AI era, we must invest for the long term and cultivate the ability to think, decide, and build amid uncertainty — not despite it.