One of the easiest ways to overestimate a piece of software is to evaluate it on the day it is written. The tests pass. The implementation is reasonably clean. Everyone agrees the requirement has been satisfied, and the code moves into the repository with that brief, wonderful feeling that the problem has been solved. Then six months pass and somebody asks for another permission type, another workflow, another notification channel, or a slightly different API contract. That is usually when I learn what I actually built. Two implementations can solve the same requirement perfectly today while making tomorrow’s change radically different in difficulty. One has clear responsibilities and a reasonably obvious place for the new behavior. The other requires somebody to understand five unrelated abstractions, modify code in three layers, and hope the integration tests remember whatever the original author knew. Interview exercises naturally hide much of this because they compress software into an hour. You are rewarded first for making something work, which is entirely reasonable. Professional engineering adds another requirement: somebody else will eventually have to understand what you wrote well enough to change it. That is the lens I would bring to the Atlassian Software Engineering Interview. Atlassian’s own current engineering interview material explicitly describes coding evaluation in terms of both data structures and code design, and it emphasizes clean code, trade-offs, problem-solving, and how candidates think rather than proficiency with one particular language. For applicable roles, its System Design interview similarly focuses on how candidates explore constraints such as reliability, cost, scaling, and technical choices, alongside communication and collaboration. The exact process varies by role and level, so I would use the recruiter’s guidance for logistics rather than assume every candidate sees an identical loop. What interests me more than the...