Earning the confidence to ship
You cannot prove software correct – you can only build enough justified confidence that shipping it is a responsible decision rather than a hope. That is what quality work is, and it rests on process as much as on tests: the test disciplines (test-driven and behaviour-driven development, embedded testing) that surface defects early, and the process around them – clear requirements, real review practice, traceability, and verification gates like Specify-and-Verify – that turn “we think it works” into evidence you can stand behind.
Where the product runs on hardware or carries safety obligations, the bar is higher: embedded testing, continuous integration, and safety-and-security practice, because a defect there is a recall, not a hotfix. And compliance has stopped being a paperwork afterthought – for a growing class of systems, the EU AI Act decides whether they are allowed to ship at all.
AI raises the pressure rather than changing the discipline. When implementation is generated, code looks finished and confident before anyone has shown it works, so the gap between plausible and verified – always where defects lived – gets wider and busier. The track adds enough fluency in the tools your teams use (Claude Code, Cursor, Copilot, Junie) to review their output credibly rather than from the outside.
Without verification, speed does not prevent failure – it only defers it to a more expensive moment. Where the stakes are physical, the Embedded systems school carries the safety-and-security variants; for the developer workflow these practices sit inside, see the AI-Assisted Software Development path.