Chai Discovery co-founder Matt McPartlon and product lead Neil Patil explain why pharma abruptly started buying AI design tools this year instead of forcing every AI-bio company to go build its own pipeline — and what specifically changed in the models to make drug design teams trust them. We trace the lineage from Chai-1, which they open-sourced for reasons that had almost nothing to do with the model itself, through the Chai-2 campaign that convinced Lilly, Pfizer, Novartis, and argenx to sign. Along the way: why their CEO says the company's real competitor is a mouse; the cryo-EM result so accurate the team's first reaction was to suspect the lab of sending back their own file; why the product looks more like SolidWorks than ChatGPT, and why Neil expects to throw most of it away; what happened when a pharma scientist saw results on a target she'd spent a decade on; why the compute market is quietly mispriced for this class of model; and the one bottleneck both guests would remove by fiat — which is not data, not compute, and not the models.