Stress-Testing Investment Hypotheses

Kanishk approaches research with an explicit hypothesis-testing mindset. He forms early views, identifies what would need to be true for each to hold, and actively looks for the data that would disprove them, not just confirm them. This has shown up in his VC sector research, where he caught a misleading read on APAC agri-tech attractiveness by looking past static penetration levels to growth trajectory. It showed up in his consulting work, where he identified a tertiary benefit stream in an AI business case that a senior partner had not factored into his pushback. His framework is conditional and layered: he structures hypotheses as chains of logic, where each sub-point needs to hold to a reasonable degree before the overall conclusion is valid. He is alert to the points in that chain where oversimplification is most likely to occur. The result is research that is harder to poke holes in, because the holes have already been found and addressed.