What a Coding Test Can Never Really Tell You

Technical assessments have become a standard part of hiring for software roles, and for good reason. Soft skills assessments offer a structured, comparable way to evaluate whether someone can solve a defined problem within set constraints. Yet a coding test, however well designed, only captures a narrow slice of what makes someone genuinely valuable on a team.

The Limits of a Timed Exercise

A coding test typically presents a clean, self-contained problem with a clear right answer. Real work rarely looks like this. Requirements shift midway through a project, priorities get reordered by business needs, and the hardest part of many tasks is deciding what to build in the first place, not writing the code once the direction is clear.

Someone who performs brilliantly under the artificial pressure of a timed test may struggle in the messier reality of a codebase inherited from someone else, filled with undocumented decisions and legacy constraints. Conversely, someone who performs only adequately on a test may turn out to be exceptional at exactly the kind of ambiguous, collaborative problem solving that a short exercise cannot measure.

What Gets Missed Entirely

A coding test says very little about how someone communicates when stuck, whether they ask for help at the right moment, or how they behave when a colleague disagrees. It says nothing about whether someone will patiently mentor a junior teammate, or quietly carry frustration into a code review instead of raising a concern directly.

These qualities matter enormously over the life of a working relationship, yet rarely show up in a ninety-minute exercise completed alone. This is part of why modern IT recruitment now pairs technical assessments with structured conversations about collaboration and how a candidate has handled real ambiguity in past roles.

Treating the Test as One Piece, Not the Whole Picture

None of this means coding tests are without value. They remain a useful, relatively objective checkpoint for confirming baseline technical competence. The mistake is treating a single score as a complete verdict on a candidate’s potential, rather than one data point among several worth weighing together.

The next time a promising candidate performs unevenly on a technical assessment, it is worth asking what the test could not see. A resume, a portfolio, and an honest conversation about how someone actually works often reveal far more about long-term success than any single timed exercise ever could on its own.

Designing Assessments That Reflect Real Work

Some teams have started moving away from artificial puzzle-style questions toward exercises that more closely resemble real work, such as reviewing existing code and explaining what they would change and why. This kind of exercise tends to reveal judgement and reasoning far more clearly than a purely algorithmic challenge.

Allowing candidates to use their usual tools, ask questions during the exercise, or even complete the task over a few days rather than under a strict time limit can also produce a much more accurate picture of how someone will actually perform once they join a real team facing real deadlines and real ambiguity.