Next generation sequencing is a rapidly expanding field with new techniques continuously emerging and increased availability of commercial kits. Over the last decade the cost per sample for sequencing has dropped massively, allowing the application of NGS-based methods in the pharmaceutical drug development pipeline. Here, these techniques can span from early-stage target identification and disease understanding to primary endpoints in clinical trials. The requirements for these workflows include large numbers of samples as well as consistent, reliable, and robust data generation. To handle projects with hundreds to thousands of samples on a regular basis, automating NGS-related workflows is the key to generating quality datasets that can be used to enhance our understanding of drug and disease mechanisms with confidence. While accessibility to off-the-shelf NGS protocols has increased, often provided with pre-verified workflows on well-established systems, we must ask the question whether the current understanding of “good” is good enough to meet the evolving needs of the pharmaceutical industry. When committing to the high-cost for NGS automation it can be difficult to find solutions for both the currently available global standard of NGS automation as well as future proofing for unseen demand in a fluid field. To combat this, we have broken out of the standard enclosed automated box that is a liquid handler and created dynamic work environments that allow for both automated and semi-automated use at the same time, seamlessly integrating groundbreaking technical development with standard off-the-shelf workflows.