The Infrastructure Case for Triple-Digit Twist

From Tools to Throughput

For most of the modern history of biotechnology, progress has been constrained less by imagination than by tempo. Hypotheses have long been generated computationally, refined statistically, and debated conceptually at speeds that far exceed the rate at which those hypotheses can be physically instantiated and tested. Even as machine learning models began to predict protein structures, generate novel sequences, and score molecular interactions with increasing confidence, the underlying workflow of biology remained bound to human mediation: experiments designed in batches, constructs ordered episodically, validation cycles stretched across weeks or months, and iteration limited by organizational friction rather than informational scarcity.