Millions of years of biological evolution have driven the development of highly sophisticated molecular machinery found within living systems. These systems produce polymers such as proteins and nucleic acids with incredible fidelity and function. In nature, the precise molecular sequence is the factor that determines the function of these macromolecules. Given that the ability to precisely define sequence emerges naturally, the fact that biology achieves unprecedented control over the unit sequence of the monomers through evolved enzymatic catalysis is incredible. Indeed, the ability to engineer systems that allow polymer synthesis with precise sequence control is a feat that technology is yet to replicate in artificial synthetic systems. This is the case because, without access to evolutionary control for finely tuned biological catalysts, the inability to correct errors or harness multiple competing processes means that the prospects for digital control of polymerization have been firmly bootstrapped to biological systems or limited to stepwise synthetic protocols. In this Account, we give an overview of strategies that have been used over the last 5 years in efforts to program polymer synthesis with sequence control in the laboratory. We also briefly explore how the use of robotics, algorithms, and stochastic chemical processes might lead to new understanding, mechanisms, and strategies to achieve full digital control. The aim is to see whether it is possible to go beyond bootstrapping to biological polymers or stepwise chemical synthesis. We start by describing nonenzymatic techniques used to obtain sequence-controlled natural polymers, a field that lends itself to direct application of insights gleaned from biology. We discuss major advances, such as the use of rotaxane-based molecular machines and templated approaches, including the utilization of biological polymers as templates for purely synthetic chains. We then discuss synthetic polymer chemistry, whose array of techniques allows the production of polymers with enormous structural and functional diversity, but so far with only limited control over the unit sequence itself. Synthetic polymers can be subdivided into multiple classes depending on the nature of processes used to synthesize them, such as by addition or condensation. Consequently, varied approaches for sequence control have been demonstrated in the area, including but not limited to click reactions, iterative solid-phase chemistry, and exploiting the chemical affinity of the monomers themselves. In addition to those, we highlight the importance of environmental bias in possible control of polymerization at the single-unit level, such as using catalyst switching or external stimuli. Even the most successful experimental sequence control approach needs appropriate tools to verify its scope and validity; therefore, we devote part of the present Account to possible analytical approaches to sequence readout, starting with well-established tandem mass spectrometry techniques and touching on those more applicable to specific classes of processes, such as diffusion-ordered NMR spectroscopy. Finally, we discuss progress in modeling and automation of sequence-controlled polymers. We postulate that developments in analytical chemistry, bioinformatics, and computer modeling will lead to new ways of exploring the development of new strategies for the realization of sequence control by means of sequence bias. This is the case because treating the assembly of polymers as a network of chemical reactions will enable the development of control strategies that can bias the outcome of the polymer assembly. The grand aim would be the synthesis of complex polymers in one step with a precisely defined digital sequence.