Tech’s Dirty Little Secret: Academic Interviews, Legacy Work
The tech industry has a dirty little secret: interviewing candidates with academic methods, like linked lists or graph traversals, but most of us, except in startups, work on legacy code using basic methods like loops and `sort()`. Let’s explore this disconnect and its benefits on the new tech reality.
A Natural Shift: From Coding to Behavior
This gap evolved naturally over time as software languages became more intuitive, shifting coding from complex problem-solving to leveraging built-in tools. As a result, while the interview format stayed academic, its focus became less about coding skill and more about behavioral observation under stress. Coding challenges like reversing a binary tree test your ability to think logically and explain your approach, but they don’t prepare you for debugging uncommented PHP monoliths or updating a Java app from 2015.
Why Shift Doesn't Make Interviews Obsolete
Interestingly, this trend toward behavior under stress aligns with the rise of AI, where machines can handle coding, making the human element of how we perform under pressure, more critical than ever. The missing piece is that companies now need to evaluate how a candidate may approach legacy problems, or even test that candidates can write a clear AI prompt-verifying that the candidate has a good comprehension and proposed solution for the problem. The adaptation must balance behavioral observation with practical investigative skills, ensuring candidates can thrive in high-pressure environments on a personal level, rather than a codebase level.
Rethink Your Next Interview
The future will meet us weather are ready or not, it’s crucial to rethink how we approach candidate interviews. Here is some food for thought:
- Highlight Behavior: In interviews, focus more on observing comprehension, communication, and problem-solving under pressure.
- Master Legacy Work: Consider adding a task that is focused on legacy-focused codebase and debugging tasks.
- Test Modern Skills: Design an interivew question around building an AI prompt meant to update a bit of legacy code, This may reveal a candidates comprehensio and problem solving skills.
Tech’s dirty little secret, that academic interviews don’t match legacy work, reflects a natural shift, now amplified by AI’s rise. By focusing on behavior skills, we can better evaluate a candidate by using one of the last important human ascpects, their stress response in adversity.