AI之下必裁人？馬斯克偏不！

在AI時代，科技巨頭的生存邏輯正在發生劇烈分化。扎克伯格正計劃大幅裁員（可能高達20%或更多，影響1.6萬左右的員工），以應對AI基礎設施的巨額開支；而馬斯克在2026年Abundance Summit上明確表示，Tesla不會進行任何裁員或人員縮減，反而計劃增加人力，同時讓每位員工的產出變得“nutty high”（瘋狂高）。

不比不知道，一比蝦肉跳。

體現了兩家公司對AI本質的不同理解：Meta視AI為“裁員工具”和成本優化槓桿，Tesla/xAI則視其為“豐裕引擎”和人類生產力的放大器。

Meta的邏輯直白且殘酷。2026年，公司面臨AI相關資本支出（capex）飆升至1150億至1350億美元的歷史高位，並計劃到2028年累計投入約6000億美元用於數據中心等基礎設施。這些天價開支主要服務於扎克伯格的“個人超級智能”（personal superintelligence）願景，包括Llama系列模型的迭代、新Avocado模型開發、收購中國AI初創Manus（至少20億美元）和AI代理社交平台Moltbook。

扎克伯格公開表示：“過去需要大團隊的項目，現在一個頂尖人才加上AI就能完成。”這直接指向內部生產力革命，用AI工具讓剩餘員工效率暴增，從而砍掉冗餘崗位。2022-2023年的“效率年”已裁掉2萬多人，這次若執行20%裁員，將是史上最大一輪，核心目的就是騰出資金應對AI燒錢，同時為AI帶來的效率躍升做準備。

扎克伯格面對的挑戰顯而易見，並且巨大和有代表性。

ROI不確定性：Avocado等前沿模型多次延期，性能仍落後於Google Gemini系列等對手，開源Llama生態雖吸引開發者，但閉源模型在某些基準上領先，Meta被迫通過高薪挖角和收購補短板。

人才與士氣雙殺：連續裁員導致普通工程師恐慌，頂級AI人才雖拿數億美元包，但整體創新速度可能放緩。

外部壓力：巨量能源消耗、歐盟AI監管、競爭加劇，都讓6000億投入的風險成倍放大。

扎克伯格可能有的潛在機會：

如果超級智能模型落地，Meta能將AI深度嵌入Instagram、WhatsApp、Facebook，形成“AI原生社交”護城河，廣告精準度和效率將實現質的飛躍。

開源策略已建立龐大開發者社區，AI代理社交網絡（如Moltbook模式）可能開闢全新賽道，成為下一代“AI互聯網”入口。

馬斯克永遠是那個不按照常理出牌的人。馬斯克的表態與扎克伯格的形成鮮明對比。在Abundance Summit上，他回應“何時機器人造機器人”時說：“我們不計劃任何裁員或人員縮減。事實上，我們會增加人力。但Tesla每人的產出將變得nutty high。”

Tesla的戰略核心是物理世界AI（embodied AI）：端到端神經網絡驅動的全自動駕駛（FSD）、Optimus人形機器人、Dojo超級計算機，以及與xAI Grok模型的深度融合。2026年關鍵節點包括Optimus Gen 3在Q1發布（手部升級至22+自由度，集成Grok用於語音交互與推理），低量產用於內部工廠，2027年高量產。Gen 3已集成Grok實現語音交互與實時決策。Robotaxi網絡、Cybertruck擴展、Optimus工厂部署，都指向同一目標：機器人承擔髒活累活，人類專注戰略、監督、創新和更高階創造。

xAI的Grok系列強調“最大真相尋求”，利用X平台實時數據訓練，雖在編碼工具等領域曾落後，但正從基礎重啟，並與Tesla生態協同（例如Grok賦能Optimus決策與對話）。

馬斯克的底層邏輯，是馬斯克的“豐裕論”（Abundance）。AI和機器人不是替換人類，而是讓“每人產出瘋狂高”，從而支撐公司規模擴張（更多車輛、更多機器人、更多工廠）。機器人/ AI系統可以隨時迭代、“關掉”或“裁剪”，人類才是長期不可替代的創造力源頭。即使必要，他也優先保人、調機器。

馬斯克面對的挑戰更嚴峻，但他選擇正面硬剛：

執行落地極難：FSD和Optimus歷史上多次延期，物理世界噪聲、供應鏈、安全法規遠比純軟件AI複雜。

資本與能源雙重擠壓：Dojo、工廠擴張、xAI重啟都需要巨額投入，電老虎問題同樣突出。

內部動盪：xAI曾經歷聯合創始人離職、大規模審計，管理複雜度拉滿。

玩大的不要命的，永遠是馬斯克的風格核心。他可能獲得的，也是潛在爆炸級機會：

實體經濟壁壘：Optimus一旦規模化，就是“無限可複製勞動力”，重塑製造業、物流、服務業，營收天花板遠超廣告業務。

跨生態閉環：Tesla車隊數據 + X實時信息 + Grok智能 + Starlink（潛在太空計算），別人難以複製。

長期敘事：若實現“後就業時代”願景，Tesla/xAI將成為基礎設施提供者，估值邏輯徹底改變。

Meta代表“AI省錢派”，砍人類、保現金流、賭模型快速迭代。

Tesla/xAI代表“AI放大派”，保人類、用機器當苦力、賭物理世界落地。

兩者都面對相同痛點：天價基礎設施 vs 短期回報、人才撕裂、監管與能源瓶頸、泡沫破裂風險。

但機會天差地別。軟件AI守住社交/廣告王座，物理AI則可能重塑整個物質世界。

AI時代沒有安全區。科技公司最終要回答：你是把AI當作“裁員工具”，還是當作“豐裕引擎”？選對路徑並執行到位者，將成為新時代的贏家通吃者；選錯或執行力不足者，可能被歷史甩在身後。

扎克伯格的戰略，讓人瞬間聯想到上世紀80-90年代通用電氣的傳奇CEO傑克·韋爾奇（綽號“中子彈傑克”）。韋爾奇以“rank and yank”（強制排名+末位淘汰）制度聞名，通過大規模裁員、精簡組織、關閉工廠，把GE從一家老派工業巨頭打造成當時最受華爾街追捧的“效率機器”。他的核心信條是：公司不是社會福利機構，必須不斷瘦身、砍掉低效環節，用更好工具讓更少的人創造更多價值。扎克伯格今天用AI做的，正是數字時代的“韋爾奇主義”，把AI當作新一代“六西格瑪+中子彈”，追求極致股東回報和組織效率。

而馬斯克，則更接近20世紀初的亨利·福特。福特沒有滿足於生產少量昂貴的豪華車，而是發明了T型車流水線生產，把汽車從奢侈品變成普通家庭都能負擔的必需品，同時大幅提升工人工資和生產力。他相信技術進步應該帶來普遍豐裕，而不是加劇稀缺與分化。馬斯克的邏輯幾乎是現代翻版：Optimus不是用來取代人類的“裁員機器”，而是“無限可複製的勞動力”，讓人類擺脫重複勞動、專注於更高階創造，最終實現他口中的“universal high income”（普遍高收入）。他不是在省人力，而是在用技術解放人力、擴張人類可能性。

一個是管理資本主義的高手，擅長把公司打造成“精瘦高效的賺錢機器”；一個是工業浪漫主義的夢想家，執着於用技術重塑物質世界、讓豐裕成為默認狀態。

這兩種領導範式，在AI時代再次狹路相逢：韋爾奇式效率優化 vs 福特式豐裕擴張。

誰能笑到最後，或許將決定下一個百年的經濟形態。是繼續“更少的人干更多的事”，還是真正走向“更多的人干更有價值的事”。

扎克伯格的領導風格，更像越戰時期的美國陸軍司令威廉·韋斯特摩蘭（William Westmoreland）。他痴迷於“body count”（屍體計數）和KPI效率，靠大規模輪換士兵、數據驅動裁減“低效部隊”來追求勝利，結果士兵普遍感到自己是可犧牲的消耗品，士氣崩盤、逃兵率飆升、沒人願意主動衝鋒——因為今天立功，明天可能就被優化掉。這正是Meta內部的寫照：連續裁員、AI一人頂一隊，讓普通工程師天天算着“下一個會不會輪到我”，頂級人才雖拿高薪卻缺乏歸屬感，創新衝勁自然大打折扣。

而馬斯克，則活脫脫當代的喬治·巴頓（George S. Patton）。巴頓從來不躲在後方指揮，他站在最前線喊“給我沖！”，同時給士兵最好的裝備、最清晰的勝利藍圖，還公開承諾“跟着我打贏了，大家一起吃肉”。士兵們雖然知道仗會很硬，但心裡有底：老大和我們一起賭命，不會拿我們當炮灰。這就是為什麼Tesla/xAI的“將領們”（工程師、高管、Optimus團隊）敢一次次all-in延遲項目、敢從零重啟xAI、敢把工廠當戰場——他們知道馬斯克不會因為短期ROI就砍人，反而會增員、給資源、一起把“nutty high”的願景干成現實。安全感越強，衝鋒陷陣的意願就越猛。

一個靠“數字裁員”維持效率，一個靠“共同冒險”激發狂熱。

兩種軍事領導範式，在AI戰場上再次對決：是讓部下人人自危、被動執行，還是讓人人覺得“跟着老大有肉吃、有未來”，主動把命豁出去？

答案，已經寫在兩家公司2026年的組織氣氛里了。

AI Layoffs Inevitable? Musk Says Hell No!

In the AI era, the survival logic of tech giants is undergoing a dramatic split. Zuckerberg is planning massive layoffs—potentially up to 20% or more, affecting around 16,000 employees—to offset skyrocketing AI infrastructure costs. Meanwhile, at the 2026 Abundance Summit, Elon Musk explicitly stated that Tesla has no plans for any layoffs or headcount reductions; instead, the company intends to increase staffing while driving per-employee output to “nutty high” levels.

You don't know until you compare—and the contrast is stark. This highlights fundamentally different views on AI's essence: Meta treats it as a “layoff tool” and cost-optimization lever, while Tesla/xAI sees it as an “abundance engine” and amplifier of human productivity.

Meta's logic is blunt and brutal. In 2026, the company faces AI-related capital expenditures (capex) surging to a historic high of $115–135 billion, with plans to invest roughly $600 billion cumulatively in data centers and infrastructure by 2028. These astronomical outlays primarily serve Zuckerberg's vision of “personal superintelligence,” encompassing iterations of the Llama series, development of the new Avocado model, the acquisition of Chinese AI startup Manus (at least $20 billion), and the AI-agent social platform Moltbook.

Zuckerberg has publicly stated: “Projects that once required large teams can now be done by one top talent plus AI.” This points directly to an internal productivity revolution—using AI tools to supercharge the remaining workforce and eliminate redundancies. Following the “Year of Efficiency” in 2022–2023, which already cut over 20,000 jobs, a 20% round would mark the largest in company history, aimed at freeing up cash to sustain AI spending while betting on efficiency gains from the technology.

The challenges Zuckerberg faces are obvious, massive, and highly representative:

• ROI uncertainty: Frontier models like Avocado have been delayed multiple times (now pushed to at least May), with performance lagging behind rivals such as Google's Gemini series. While the open-source Llama ecosystem attracts developers, closed-source models lead in certain benchmarks, forcing Meta to rely on high-salary poaching and acquisitions to plug gaps.

• Talent and morale double hit: Continuous layoffs breed panic among regular engineers, and even top AI talent—despite multimillion-dollar packages—may see slower overall innovation.

• External pressures: Enormous energy consumption, EU AI regulations, and intensifying competition multiply the risks of that $600 billion bet.

Zuckerberg's potential opportunities are equally clear:

• If superintelligence models land, Meta can deeply embed AI into Instagram, WhatsApp, and Facebook, creating an “AI-native social” moat with dramatically improved ad precision and efficiency.

• The open-source strategy has built a vast developer community, and AI-agent social networks (like the Moltbook model) could open entirely new lanes, becoming the gateway to the next “AI internet.”

Musk is forever the guy who plays by his own rules. His statement stands in sharp contrast to Zuckerberg's. At the Abundance Summit, responding to “When will robots build robots?” he said: “We're not planning any layoffs or reductions in personnel. In fact, we will increase our headcount. But the output per human at Tesla is going to get nutty high.”

Tesla's strategic core is embodied AI (physical-world AI): end-to-end neural networks powering Full Self-Driving (FSD), the Optimus humanoid robot, Dojo supercomputers, and deep integration with xAI's Grok model. Key 2026 milestones include the Optimus Gen 3 unveiling in Q1 (hands upgraded to 22+ degrees of freedom, integrated Grok for voice interaction and reasoning), low-volume production for internal factory use, and high-volume ramp in 2027. Gen 3 already incorporates Grok for voice interaction and real-time decision-making. Robotaxi networks, Cybertruck expansion, and Optimus factory deployments all aim at the same goal: robots handle the dirty, repetitive work while humans focus on strategy, oversight, innovation, and higher-level creation.

xAI's Grok series emphasizes “maximum truth-seeking,” trained on real-time X platform data. Though it lagged in areas like coding tools, it's being rebuilt from the ground up and synergizes with Tesla's ecosystem (e.g., Grok empowering Optimus decisions and dialogue).

Musk's underlying logic is his “Abundance” theory: AI and robots don't replace humans—they make each person's output “nutty high,” enabling explosive company-scale growth (more vehicles, more robots, more factories). Robots/AI systems can be iterated, shut down, or “laid off” at will; humans remain the irreplaceable source of long-term creativity. Even when necessary, he prioritizes protecting people and adjusting machines.

Musk's challenges are even more severe, yet he charges straight ahead:

• Execution is extremely difficult: FSD and Optimus have historically delayed repeatedly; real-world noise, supply chains, and safety regulations are far more complex than pure software AI.

• Capital and energy double squeeze: Dojo, factory expansion, and xAI reboots demand massive investment; power-hungry “electric tigers” remain a bottleneck.

• Internal turbulence: xAI has seen co-founder departures and large-scale audits, with management complexity at maximum.

Playing big and fearlessly is forever Musk's core style. The explosive opportunities he could seize:

• Physical-economy moat: Once Optimus scales, it's “infinite replicable labor,” reshaping manufacturing, logistics, and services—with revenue ceilings far exceeding advertising.

• Cross-ecosystem closed loop: Tesla fleet data + X real-time info + Grok intelligence + Starlink (potential space computing) is nearly impossible to replicate.

• Long-term narrative: If the “post-employment era” vision partially materializes, Tesla/xAI becomes infrastructure provider, fundamentally shifting valuation logic.

Meta represents the “AI cost-saving faction”—cut humans, preserve cash flow, bet on fast model iteration. Tesla/xAI represents the “AI amplification faction”—protect humans, use machines as grunt labor, bet on physical-world landing.

Both face the same pain points: astronomical infrastructure vs short-term returns, talent fractures, regulatory and energy bottlenecks, bubble-burst risks. But the opportunities differ vastly: software AI holds the social/advertising throne; physical AI could reshape the entire material world.

There is no safe zone in the AI era. Tech companies must ultimately answer: Do you treat AI as a “layoff tool” or as an “abundance engine”? Those who choose the right path and execute flawlessly will become the era's winners-take-all; those who choose wrong or falter may be left in history's dust.

Zuckerberg's strategy instantly recalls Jack Welch (“Neutron Jack”), the legendary 1980s–90s GE CEO. Welch was famous for “rank and yank” (forced ranking + bottom elimination), using mass layoffs, organizational streamlining, and factory closures to turn GE into Wall Street's most beloved “efficiency machine.” His core creed: Companies aren't social welfare institutions—they must constantly slim down, cut inefficiencies, and use better tools to let fewer people create more value. What Zuckerberg is doing with AI today is the digital version of Welchism—treating AI as the new Six Sigma + neutron bomb in pursuit of ultimate shareholder returns and organizational efficiency.

Musk, by contrast, aligns more closely with early-20th-century Henry Ford. Ford didn't settle for producing a few expensive luxury cars; he invented assembly-line production, turning automobiles from luxury items into affordable necessities for ordinary families while dramatically raising worker wages and productivity. He believed technological progress should bring universal abundance, not exacerbate scarcity and division. Musk's logic is a modern echo: Optimus isn't a “layoff machine” to replace humans—it's infinite replicable labor that frees people from repetitive toil for higher-level creation, ultimately achieving his “universal high income.” He's not saving labor; he's using technology to liberate it and expand human potential.

One is a master of managerial capitalism, skilled at forging companies into lean, high-efficiency profit machines; the other is an industrial romantic dreamer, obsessed with using technology to reshape the material world and make abundance the default state.

These two leadership paradigms clash head-on once again in the AI era: Welch-style efficiency optimization vs Ford-style abundance expansion. Who laughs last may well determine the economic shape of the next century—whether we continue with “fewer people doing more” or truly move toward “more people doing more valuable things.”

Zuckerberg's leadership style resembles William Westmoreland, the U.S. Army commander during the Vietnam War. Obsessed with “body count” metrics and KPI efficiency, he relied on mass troop rotations and data-driven culling of “low-performing units” to pursue victory—resulting in soldiers feeling like disposable consumables, morale collapse, skyrocketing desertion rates, and no one willing to charge forward voluntarily (today's hero could be tomorrow's optimization target). This mirrors Meta's internal reality: continuous layoffs and “one person + AI does a team's work” make ordinary engineers constantly wonder “Am I next?” Top talent gets sky-high pay but lacks belonging, naturally dampening innovative drive.

Musk, on the other hand, is a living embodiment of George S. Patton. Patton never hid in the rear—he stood at the front lines yelling “Follow me!” while equipping soldiers with the best gear, clearest victory maps, and open promises: “Win this fight with me, and we'll all eat well.” Soldiers knew the battles would be brutal, but they had rock-solid confidence: the boss gambles his life alongside ours and won't use us as cannon fodder. That's why Tesla/xAI's “generals” (engineers, executives, Optimus teams) dare to all-in on delayed projects, reboot xAI from scratch, and turn factories into battlefields—they know Musk won't cut heads for short-term ROI; instead, he'll add people, provide resources, and charge together toward that “nutty high” vision. The stronger the sense of security, the fiercer the willingness to charge.

One sustains efficiency through “digital layoffs”; the other ignites fanaticism through shared adventure.

These two military leadership paradigms clash again on the AI battlefield: Do you make subordinates live in fear, executing passively? Or do you make them feel “Follow the boss—there's meat to eat and a future ahead,” willingly risking everything?

The answer is already written in the organizational atmosphere of both companies in 2026.