Why the Belief Is Absolute

The conviction rests on observable trends. Every few percentage points of model improvement unlocks new business applications. One YC founder pivoted three times in six months, each time responding to capabilities that made previously impossible workflows suddenly viable. A pricing expert estimated that 40% of AI-focused companies adjust strategy within two weeks of major model releases.

The cost-to-intelligence ratio drops with every release. What required a team of engineers six months ago now runs on a single API call. Companies are watching their unit economics transform in real time.

This matters because: When businesses can reliably predict that AI will get both better and cheaper, they make fundamentally different investment decisions. The scaling laws become the foundation for multi-year bets.

The Human Dependency Paradox

Despite accelerating capability, AI remains dependent on human expertise. Every company we visited employs forward-deployed engineers who spend 8-12 weeks inside client organizations, mapping the gap between documented processes and actual workflows.

One engineer discovered a "seven-step refund process" that actually had twenty-three steps, including decisions based on recognizing repeat callers by voice. The technology can handle the task—but only after humans translate business reality into a form AI can process.

This matters because: The micro-level transformation isn't about replacing humans with AI. It's about reconfiguring how human knowledge gets captured and deployed. Companies that master this translation create durable competitive advantages.

Outcome-Based Economics

As AI agents handle complete tasks autonomously, pricing shifts from access to outcomes. Companies now pay per resolved support ticket, not per seat. Per qualified lead, not per user license.

This makes performance directly measurable and comparable. It also forces companies to quantify the added value of labor—a confronting exercise for some. Switching costs drop once workflows are defined and benchmarks established.

This matters because: When every vendor's performance becomes quantifiable and comparable, competition intensifies. Traditional moats like customer relationships matter less than demonstrable results. This accelerates business model innovation across entire industries.

Speed as Existential Requirement

One founder, discussing a build-or-buy decision, stated: "If it takes us more than three weeks to build, we buy it." For many European founders, three weeks is considered a short development timeline. This gap reveals the stark difference in how speed is perceived between US and European tech ecosystems.

Investors aren't betting on plans. They're betting on founders who can figure things out faster than competitors. If something is failing, companies need to know immediately.

This matters because: Speed becomes self-reinforcing. Fast-moving companies force competitors to move faster. The baseline pace of business evolution accelerates, pulling entire sectors into shorter strategy cycles.

The European Disconnect

These four changes—reliable capability growth, human-AI workflow integration, outcome-based pricing, and compressed strategy cycles—are already reshaping how Silicon Valley companies operate. The macro-level consequences follow directly: as thousands of companies simultaneously adapt to these new realities, labor markets shift, skill demands evolve, and economic transitions accelerate.

The best way to predict the future is to create it. That's what's happening in San Francisco. The belief in scaling laws isn't merely a forecast—it's a force actively shaping the strategies of thousands of companies, directing billions in capital, and restructuring business models. Whether this future is inevitable or self-fulfilling remains unclear. But its construction is already underway.

When we asked what keeps people awake at night, the answer consistently pointed to managing the economic transition. New jobs will emerge, but the short-term net effect on employment is anticipated to be negative.

In the Netherlands, this rapid pace is largely underestimated. Most CEOs don't grasp it. Government and society underestimate it. Many politicians fail to understand the employment implications, treating economic transition as a theoretical discussion rather than present reality.

The Dutch companies succeeding in Silicon Valley have absorbed this worldview. They understand why the certainty exists—not as hype, but as extrapolation from consistent trends. They've seen how it translates into concrete business changes: faster pivots, outcome-based contracts, workforce reconfigurations.

For Dutch leaders who haven't made this trip: the task isn't to blindly accept Silicon Valley's certainty. It's to understand the four forces driving it, and to ask what major changes your organization needs to anticipate. The scaling laws may be treated like gravity in San Francisco. But gravity affects everyone, whether you believe in it or not.