"No matter how complicated a problem is, it usually can be reduced to a simple, comprehensible form which is often the best solution"
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An Wang, a pioneer of computer engineering and founder of Wang Laboratories, captured a core discipline of both science and business: complexity yields to clarity. His career began in the austere early days of computing, when memory was scarce, processing power was limited, and messy designs simply did not run. Working at Harvard and later licensing inventions related to magnetic core memory to IBM, he learned that the surest path through constraints was to isolate the essence of a problem and build around it. That habit carried into Wang Laboratories, whose success in office computing came from products that ordinary users could understand and trust.
Reducing a problem to a simple, comprehensible form is not a plea for naivete. It is the art of choosing the right abstraction, the one that preserves what matters and discards what does not. The result is often the best solution because it aligns with how humans reason, makes systems easier to test and maintain, and lowers the chance that hidden interactions will break under stress. Engineers call this KISS; philosophers call it Occams razor. Wang frames it pragmatically: clarity is a competitive advantage.
The careful qualifiers matter. He says usually and often. Some domains resist drastic pruning; oversimplify a medical model or a financial risk engine and the mistakes will be costly. Yet the discipline of seeking simplicity is still the most reliable way to expose the true difficulty. When a design remains tangled after rigorous reduction, you have learned something vital about the problem rather than about your confusion.
The practical method is universal: define goals and constraints precisely, strip away decorative features, pick a model that makes the core relationship obvious, and let implementation follow that spine. From debugging code to crafting policy, the solution that people can explain and reason about is the one that scales. Wang made a career proving that clarity is not just elegant; it is effective.
Reducing a problem to a simple, comprehensible form is not a plea for naivete. It is the art of choosing the right abstraction, the one that preserves what matters and discards what does not. The result is often the best solution because it aligns with how humans reason, makes systems easier to test and maintain, and lowers the chance that hidden interactions will break under stress. Engineers call this KISS; philosophers call it Occams razor. Wang frames it pragmatically: clarity is a competitive advantage.
The careful qualifiers matter. He says usually and often. Some domains resist drastic pruning; oversimplify a medical model or a financial risk engine and the mistakes will be costly. Yet the discipline of seeking simplicity is still the most reliable way to expose the true difficulty. When a design remains tangled after rigorous reduction, you have learned something vital about the problem rather than about your confusion.
The practical method is universal: define goals and constraints precisely, strip away decorative features, pick a model that makes the core relationship obvious, and let implementation follow that spine. From debugging code to crafting policy, the solution that people can explain and reason about is the one that scales. Wang made a career proving that clarity is not just elegant; it is effective.
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| Topic | Reason & Logic |
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