There was a famous  Covid era chart (https://x.com/clcrozier/status/1251148890595708938) that I always struggle to find, showing how hard it is to estimate an S curve while living through it. in the early days it seems that everything is exploding as an exponential and you always get hypey essays about how YOU, YOU DUMB DUMB, DONT UNDERSTAND EXPONENTIALS LET ME EXPLAIN. and then as things hit invisible asymptotes those same loud voices who write viral essays have curiously moved on to other things.

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A repost and preservation of Constance Crozier's 2020 blog post explaining why forecasting S-curves is difficult while living through them. Using animated examples, the post demonstrates that even with idealized data, the best-fit S-curve estimate remains wildly inaccurate during the exponential and linear growth phases — only converging on the correct curve once the data begins to level off. The framing note observes how early-phase exponential hype tends to fade once invisible asymptotes are reached, and that domain-specific contextual knowledge is needed to make reliable S-curve predictions.

Constance Crozier: Forecasting s-curves is hard