The most common thing a perfect-score candidate hears in their first month is "why did you write it this way?"
Algorithm problems hand you fixed inputs, fixed outputs, and one right answer. Real work hands you requirements that shift under you and several answers that are all defensible. That gap is why the people who clear the interview and the people who do the job well are not always the same set. Hiring managers know this. They keep running coding tests anyway, because nothing cheaper has replaced them.
The test measures baseline problem-solving, not job ability
A coding test checks whether you can take a frozen spec and turn it into correct logic inside a time limit. You have to reason about time complexity, pick a data structure that fits, and catch the edge case that breaks the naive version. Those are real skills, and a developer without them struggles.
The problem is that most of what makes production work hard isn't in there.
The difficulty in production code comes from uncertainty. Figuring out what a line in the spec actually means. Predicting what breaks when you touch legacy code that has been running for four years. Tracing why another team's API behaves differently from its documentation. Nobody writes out the inputs and outputs for you. You have to work out which question to ask before you can answer anything.
Algorithm problems have a correct answer. Production doesn't.
A coding test asks "find the longest subsequence in this array that satisfies the condition." One answer, and a grader that knows it.
Production asks "how do I design this so that when the requirements change in three months, I'm not rewriting it from scratch?" There's no answer, only tradeoffs. Make it extensible and you pay in complexity today. Keep it simple and you accept that you may throw it away later.
You can see the same split in code review. An algorithm problem ends at pass or fail. Production code gets judged on whether a teammate can read it in six months, whether it matches team conventions, whether it has tests. Writing alone for a grader and writing for people who will keep editing your code are different jobs.
Take variable names. In a contest, calling things a, b, and tmp costs you nothing. In production, a meaningless name is a direct bill charged to the next person's debugging time. When you finish a function at work, the question isn't only "is this correct" but "can someone else change this safely." No autograder scores that second one.
Companies keep using them because filtering is expensive
Verifying each applicant's actual ability takes real time. Reading a portfolio takes time. Digging through their past project code takes more. Add a few rounds of interviews and the cost climbs fast.
A coding test is a standardized way to cut a large pile of applicants down quickly. It's not precise, but for screening "does this person have basic logic and can they write code," it's efficient.
There's also fairness, which is harder to dismiss than it sounds. An open-ended interview leaves a lot of room for the interviewer's gut feeling. A fixed problem with automated scoring gives both sides less to argue about. Coding tests survive less because they predict job performance and more because they filter a lot of people cheaply without looking arbitrary.
Preparing for both means splitting them by season, not by day
If you're job hunting, there's no reason to skip coding test prep. Fail the first gate and you never get to show anything else.
Pouring every hour into it and arriving with nothing else is a separate problem.
The balance that actually works: do algorithm practice in concentrated blocks around the interview season. The rest of the time, finish small projects end to end. Ship something. Take a bug report and fix it. Leave a review on someone else's code. That does more for your first six months on the job than another hundred practice problems.
The coding test is the key to the door. What you need in the next room, you prepare separately.
Leaning on it too hard backfires on the hiring side too
If a company keeps cranking up test difficulty to filter harder, it starts rejecting people who would have been strong on the team but don't test well. The reverse happens too: someone trained specifically on contest problems clears the bar and then takes a long time to become useful. Both outcomes cost the company and the candidate.
That's not an argument for dropping coding tests. The usual alternatives have their own holes. Portfolios can be faked or ghostwritten. Take-home assignments get criticized for demanding unpaid hours from people who are already working full time. The workable position is to treat the coding test as one filter among several, and to stop reading its result as a full measure of what someone can do.
More companies now ask candidates to walk through past work instead of doing live coding, or pair the test with a collaboration simulation. That shift comes from the same recognition: trying to catch everything with one instrument wastes time on both sides of the table.
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