Economic dynamics where scarce resources flow disproportionately to entities with the greatest ability to pay and deploy, creating self-reinforcing concentrations of power. In the AI economy, gravity wells form around three critical bottlenecks: compute (with TSMC packaging capacity initially allocated to Apple and NVIDIA), power (with Microsoft and Meta securing nuclear plants through 20-year contracts), and talent (with top engineers concentrating at leading AI labs). For organizations competing in the AI era, understanding gravity wells determines whether you capture resources or scramble for scraps—those positioned at the center don't just get resources, they define what resources are worth.
The AI revolution will be dictated by three physical constraints—compute packaging capacity, energy availability, and organizational agility—that concentrate power in gravity wells. Whoever controls these choke points, not merely the best models, will shape the next decade of AI.
Conway’s Law states that organizations designing systems are constrained to produce designs mirroring their own communication structures. For example, separate sales, marketing, and support teams often yield a website organized into Shop, Learn, and Support sections—reflecting internal divisions rather than user needs.
Accretive software refers to AI platforms that automatically absorb model improvements as margin expansion by treating models as interchangeable components and routing queries to the optimal model in real time. Rather than fighting obsolescence, these platforms convert every efficiency breakthrough into customer value or profit margin.