In Silicon Valley, we make products by building a minimal viable product ( mvp ): the smallest feature set that is your best educated guess at what your customer needs. You then take your mvp to customers, iterate quickly, and iterate often. This is a great method for building many products — especially consumer digital products where you can make quantifiable changes in days and weeks and test against a lot of users. In agriculture, this methodology simply doesn’t work. You get one growing season per year, on average, and your product can’t fail in the middle of it, or you are out. Thus, there is a gap between the very identifiable problems of agriculture and the solutions currently available. This is more than a data gap: frankly, it is a methodology gap.

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