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.
This is similar to the ideas from lean startup where the goal is to efficiently validate critical assumptions by building the minimum required to learn from users.
Facts don’t necessarily need to be provable to be valuable, just correct (a G-statement). Gödel Incompleteness For Startups argues that the unprovable yet true facts are the most scarce and therefore most valuable.
Links to this note
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What is product/market fit?
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An expression for Bayesian thinking where you think in ranges of outcomes based on prior information. When new information arrives, to get a more accurate range of solutions you ‘update your priors’.
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A product design partner is an early user and potential customer that provides regular organized feedback about your product. In return, they get a hand in designing the product to fit the needs of their organization, early access to the product, and discounted pricing once it launches.
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Whenever there are a hundred things or more in a process someone is doing, there is a recognition that “there must be a better way”. A hundred items are the upper bound of what one can reasonably track manually. A hundred items indicate that the process is more complicated than one thought.
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