Reinvent. Amplify. Multiply.
Substrate 01: Intelligence Infrastructure
I’ve had the same conversation 200+ times in two years.
Different industries. Different continents. Same pattern.
Most executives are asking: “What can AI replace?”
The 5% who will dominate ask: “What can we reinvent that wasn’t possible before?”
That shift from substitution to reinvention is everything.
The Problem: We’re Having The Wrong Conversation
History repeats, but faster each time.
Electricity took 40 years to transform factories. Early adopters just replaced steam engines with electric motors and kept everything else the same. Productivity improved 5%. It took a generation before someone asked: What if we redesigned the entire factory around distributed power?
Productivity exploded 3-5x.
The internet compressed this pattern to 15-20 years. Mobile to 10-12 years. AI might do it in 5-7 years—not enough time for comfortable adaptation.
We are now in the substitution phase. Chatbots replacing customer service. Image generators replacing stock photos. 5-10-20% efficiency gains while the fundamental operating model stays intact.
The organizations that dominate won’t be those who substitute fastest. They’ll be those who reinvent what wasn’t possible before.
The Use Case Trap
The most common request I hear: “Give me AI use cases for my industry.”
This question invokes a trap.
It assumes your current operating model is correct. It treats AI as a feature to bolt onto existing workflows. It presumes the processes, org structures, and decision architectures that got you here are the ones that will take you forward.
They’re not.
“Give me use cases” is like asking “give me electricity use cases” in 1905 while keeping your factory designed around a central steam engine with belt-driven machinery. You’ll get marginal gains. You’ll miss the revolution.
Here’s what happens:
You add AI to broken processes
You get fragmented pilots with no compound learning
Intelligence can’t flow because it’s trapped in silos
You get 10% gains, complain about ROI, blame the technology
Meanwhile, a company founded today built around abundant intelligence as infrastructure eats your market
The real questions aren’t about use cases. They’re about operating models:
Not: “What are AI use cases for customer service?”
But: “How should customer service operate if intelligence is abundant, patient, and costs nearly nothing?”
Not: “Where can we add AI to our workflows?”
But: “If we rebuilt this from zero today, knowing AI exists, what would we design?”
Not: “Can AI automate this process?”
But: “Why does this process exist at all? What outcome do we actually want?”
Not: “Show me ROI on AI tools”
But: “What structural advantage do we gain by reorganizing around abundant intelligence?”
The substrate question is this: If you’re competing against a company founded today that assumes AI as baseline infrastructure, what would they build that you can’t?
That’s not a technology conversation. That’s an operating model conversation.
The Principle
After analyzing Fortune 200 transformations, here’s what separates the 5% who will dominate from the 95% who won’t:
REINVENT • Don’t substitute—rebuild from first principles
The substrate shifted. The ground beneath the ground. AI is infrastructure now and organizations founded today assume AI capabilities as baseline. They’re structured differently, staffed differently, operate at different economics. What needed 100 employees a decade ago now needs 10 people orchestrating AI systems.
AMPLIFY • Human + machine symbiosis, NOT replacement
When intelligence becomes cheap, humans don’t become obsolete, they become leveraged. A therapist serving 30 clients could serve 300, with AI handling scheduling, notes, research synthesis. The human provides what only humans can: presence, judgment, the irreducible quality of presence. This is the era of asymmetric impact. BCG’s 10-20-70 rule applies: 10% is algorithms, 20% is technology stack, 70% is human transformation. Most invest backwards.
MULTIPLY • Exponential dynamics compound faster than intuition
Inference costs dropped 280x in two years. AI performance on coding benchmarks improved 67% in one year. We’re on the second half of the chessboard where exponential growth stops looking flat and goes vertical. Pattern recognition matters more than prediction. Learning velocity matters more than knowledge stock. The organizations that thrive will be those structured to learn, unlearn, and relearn faster than the technology evolves.
What This Means For You
The future exists in superposition. Multiple outcomes are possible simultaneously. Your choices about infrastructure, about humans, about purpose will collapse the wave function toward one reality or another.
Fundamental change and incremental thinking don’t mix well.
Most organizations are making 10% bets on a 10x shift. They’re piloting AI use cases while competitors rebuild from scratch. They’re optimizing existing workflows while the substrate beneath them dissolves.
The constraint that shaped every decision you’ve ever made, that intelligence is scarce and expensive, just broke.
That constraint defined how you hire, how you structure teams, what problems you attempt to solve, what businesses you enter, what customers you serve.
It’s gone.
AI gives you the keys to unshackle yourself from assumptions you didn’t know you were making. The only question is are you thinking BIG enough?
The substrate shifted.
What will you build upon it?