An unprovable, but true statement as described in Gödel’s incompleteness theorem. Any formal system will be incapable of capturing all true statements and so there will always be unprovable, but true statements about which the system tries to describe.
Examples of a G-statement:
- A black swan event like the 2008 financial crisis (predictable in hindsight, but no formal systems were able to capture this)
- Google finding and extracting massive value from better paid search (Gödel Incompleteness For Startups)
Links to this note
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Delightful UX Is a G-Statement
Having a delightful UX (user experience) is obviously good, yet not provable. Attempts to apply a formalization like conversion, net promoter score, or other metric usually fails to directly observe the effect of good (or bad) user experience. In that way, UX is a G-statement that we all intuitively know to be true.
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Product Work Is a Pursuit of Facts About the User, Market, and Their Problems
When building products you are always learning new things about the user, the market, and their problems. Sometimes this happens intentionally (e.g. doing user research) and sometimes it happens unintentionally (e.g. adding a feature that suddenly takes off in usage). Ideally these facts are made explicit and is accretive over time so that new facts leads to better understanding over time which leads to more successful products. This also requires flexibility and updating ones model as new information is uncovered.
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Gödel Incompleteness for Startups
An essay that relates Gödel’s incompleteness theorem (along with the Halting Problem) to startup disruption—arguing that all successful startups discover one or more G-statements and extract value by building a formal system around it.
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Gödel’s Incompleteness Theorem
A formal system (one that is consistent never yields a false statement) can not also be a complete system (containing all true statements)–there will always be statements that are unprovable yet true (i.e. G-statement).
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Conjecture Is Vital to Product Development
Product development tends to overlook the importance of conjecture. Lean startup and similar ‘lean’ movements create a culture of empiricism—only that which can be measured must be true. This might make sense for optimizing mature products, but a culture of empiricism leads to an incremental approach to building new products and, at best, leads to finding a local optima.