The genomics pipeline as a production system. Sample → sequence → align → impute → genotype → parentage/trait, scheduled or triggered by new data, with retries, version pinning, and alerting.
A sample-state ledger. One authoritative record per sample of where it is (received, sequenced, passed coverage, imputed, called) and, if it stopped, why.
Lead and support the engineering managers. Our EMs are experienced managers, and your job is to make them more effective. Give them the context, support, and clear expectations they need to build high-functioning teams with real accountability for outcomes. Unblock them across teams, back their hard calls, and hold them to a consistent bar. Hire the managers we'll need as we grow.
Alerting and service-level objectives for the farm pipeline. What “decisions on the farm by time T” means per herd, instrumented and alerted. A run that never started, never finished, or finished late should reach a person before anyone on the farm notices.
The release path. Building out a path where staging runs on every commit and software engineers...
