What could make knowledge-compounding economically powerful
If a laboratory develops one useful capability, it has one potential product. If that capability becomes a reliable component used in many Circuits, it may support multiple products. If later researchers can preserve and build upon its evidence, it may reduce repeated research cost. If customers pay for lawful uses, part of the resulting economic surplus may finance more experiments. These effects create a possible feedback loop.
The compounding effect is conditional. Reusing a component must save more resources than it costs to qualify, store, support and license it. A network of farms must produce real new utility, not just recycle the same code under new names. Customers must have actual problems they are willing to pay to solve. Financial valuations must not be inflated by repeated internal transactions among related parties. The value of an unsuccessful experiment lies in genuine learning, not a fictitious dollar amount assigned to failure.
The complete system creates a way to observe the cycle rather than merely describe it. An operator can measure qualified discoveries, independent reproductions, real customer use, actual receipts, net costs, contributor allocations and the incremental output of reinvested research. When those records are sound, the economic significance can be examined on its merits.