1. The Phenomenon and Business Essence

Meta's latest paper, 'Neural Computers,' reveals: the research team trained a video generation model to directly simulate terminal command lines and desktop operation interfaces, producing usable results. In plain terms: AI is no longer just 'writing code' or 'answering questions'—it is beginning to sit in front of a computer like an employee, clicking, typing, and executing tasks. The current stage remains a laboratory achievement, but the direction is set. The core business fact is singular: any position involving 'humans watching screens and following procedures to operate software' has its replacement clock already started. According to McKinsey estimates, such 'process-execution' positions account for over 40% of white-collar labor costs in China's manufacturing and service sectors.

2. Dimensional Analogy: This Is an 'Electrification' Moment, Not a 'New Tool' Moment

In the 1890s, when factories introduced electricity, most owners simply treated electric motors as 'more labor-saving steam engines'—installed in the same location, driving the same drive shaft. Within twenty years, factories that restructured workshop layouts around electricity achieved 3-5x productivity gains, while factories clinging to old logic were all eliminated. The essence of the Neural Computer is identical: it is not 'faster RPA (Robotic Process Automation)' but a general-purpose operation intelligence that requires no pre-programming and can autonomously understand any interface to execute tasks. Old RPA required IT teams to write scripts for each system—high cost, expensive maintenance; Neural Computer is theoretically plug-and-play for any software interface. The key to the analogy: marginal cost approaches zero while flexibility approaches that of humans.

3. Industry Restructuring and Endgame Projection

Examining through Grove's 'Strategic Inflection Point' framework, signals have emerged: commercial products will launch within 18-36 months:

  • First出局 (out): Data entry companies, voucher processing teams in financial shared service centers, 'listing/price adjustment/reconciliation' positions in e-commerce operations. These companies' core moat is 'proficiency in manual software operation,' which is precisely the target of Neural Computer.
  • 剧烈震荡 (Violent turbulence): Regional chain store operations management positions, small factory ERP operation specialists, documentation clerks in trading companies. The higher the labor cost proportion, the more剧烈的 the turbulence.
  • 潜在受益 (Potential beneficiaries): SaaS service providers who can quickly integrate AI operation agents, and entity business owners who dare to first cut process positions and reallocate budgets to customer relationships and product R&D.

终局判断 (Endgame judgment): Within 2-3 years, the unit cost of 'human-operated software' will drop by 60-80%. Companies that complete migration first will gain a one-time structural cost advantage that competitors cannot catch—because organizational inertia moves much slower than technology migration.

4. The Two Paths for Business Owners

路径A (Path A - Proactive positioning): Now, spend 3 months and 100,000-300,000 in budget to find a trustworthy AI automation service provider, pilot transforming one standardized operational process (such as reconciliation, reporting, order entry) into an intelligent agent. After running successfully, replicate to all similar positions, and reallocate freed labor to sales or service. First-movers gain the cost reduction window.

路径B (Path B - Cost of hesitation): If choosing to wait, be sure to accomplish one thing within 12 months—calculate the total annual labor cost for all 'process-execution' positions in your company. This number is the ammunition inventory your future competitors will use to undercut your prices. Knowing the magnitude of risk is the lowest-cost preparation.