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'Can They Code?' Is the Wrong Question

Coding tests answer 'can they solve this puzzle today'. A hiring decision needs 'should I hire this engineer for this role' — the gap is where mis-hires live.

HireInterviewAI Team·August 9, 2026·5 min read
A hiring manager comparing what a coding test score proves with the per-concept, evidence-backed answer a real hiring decision requires
On this page
  • What a passing coding test actually proves
  • The gap cuts both ways — and both directions are expensive
  • What evidence a hiring decision actually needs
  • How an adaptive per-concept interview closes the gap

On this page

  • What a passing coding test actually proves
  • The gap cuts both ways — and both directions are expensive
  • What evidence a hiring decision actually needs
  • How an adaptive per-concept interview closes the gap
HireInterviewAI Team

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HireInterviewAI Team

AI Interview Research

The HireInterviewAI team builds adaptive AI technical interviews that probe candidates concept by concept and report exactly which topics they understand at depth.

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Key takeaways
  • A passing coding test proves exactly one thing: this candidate solved these puzzles today. It carries no depth signal, no coverage guarantee, and no answer to "should I hire this engineer for this role."
  • The gap cuts both ways: strong engineers fail puzzle screens (false negatives you never see) and rehearsed puzzle-solvers pass them (false positives you pay for over months).
  • A hiring decision needs per-concept depth measured against the role's required depths, separate signals for debugging, review, and architecture — and honest disclosure of what was not assessed.
  • An adaptive per-concept interview closes the gap: it probes each concept to its real depth (L1–L5) and reports a profile with evidence behind every claim — competency intelligence, not a score.

A coding test answers exactly one question: can this candidate solve this puzzle today? A hiring decision needs a different question answered: should I hire this engineer for this role? The two sound adjacent. They are not — and the gap between them is where mis-hires live, in both directions.

This post is about that gap: what a passing coding score actually proves, what it costs to mistake it for a hiring signal, and what evidence a real decision needs instead.

What a passing coding test actually proves

Let's be fair first. A passing score is real information: the candidate produced working solutions to a handful of well-specified problems, under time pressure, without help you could detect. That is not nothing.

Now the list of things it does not prove:

  • Depth. The questions sit at fixed difficulty, so the score cannot tell you where understanding ends. A candidate who scraped past the bar and one who could have gone three levels deeper receive the same "pass" — the depth signal a decision needs is exactly what a threshold destroys. (Measuring it is its own discipline.)
  • Understanding vs. rehearsal. The question banks are public and the grind is an industry. A pass may measure preparation volume — pattern-matching this puzzle to a memorized solution class — rather than the reasoning the job will demand on problems no one has published solutions to.
  • Coverage. Puzzles sample one narrow band: self-contained algorithmic problem-solving. The role runs on concurrency, error handling, API design, data modeling — and above all on code someone else wrote. A coding score is silent on all of it, and the silence is unlabeled.
  • The rest of the job. Debugging a failing system, reviewing a teammate's change, defending an architecture under questioning — none of it appears in a puzzle score, and none of it can be inferred from one.

A coding test is a coarse filter that answers a narrow question honestly. The failure mode is treating that answer as if it were the hiring decision.

The gap cuts both ways — and both directions are expensive

False negatives: the engineers you filtered out. Puzzle screens reject experienced engineers whose depth lives in systems, debugging, and design rather than in timed algorithm recall — people who would have excelled in the role fail a format that never asked about the role. This cost is invisible by construction: you never meet the hire you didn't make. It is common enough to deserve its own post.

False positives: the rehearsed pass. The inverse candidate — deep question bank preparation, shallow everything else — sails through and joins the team. This cost is very visible, just slow: months of salary and onboarding before the gap is undeniable, senior time spent compensating, then a backfill that restarts the whole pipeline. The mis-hire didn't happen at the six-month mark. It happened the day a puzzle score was read as a hiring answer.

Both failures share one mechanism: the test compressed everything it saw into one number, and the number couldn't carry the shape. "Passed with 82%" covers the lopsided-but-brilliant systems engineer and the rehearsed pattern-matcher alike. The decision needed the shape.

What evidence a hiring decision actually needs

"Should I hire this engineer for this role?" decomposes into three evidence requirements — this is the core of evaluating developer skills well:

  1. Per-concept depth, against the role's required depths. Not "backend: pass" but "Go concurrency: L5, error handling: L2" — compared with what this role needs. An L2 in error handling is a dealbreaker on a payments team and a shrug on a prototyping team. The same profile, two different correct decisions: that is role-fit, and it requires the profile.
  2. Separate signals for separate skills. Debugging is not puzzle-solving; reviewing code is not writing it; architecture is a different competence again — which is why design gets its own dedicated round, assessed across six dimensions at adaptive depth rather than inferred from coding answers.
  3. Honest disclosure of what was not assessed. A trustworthy report labels its own boundaries. "Not assessed: frontend, infrastructure" is a feature — the silent alternative is a reader assuming a passing score covered things it never touched.

Side by side, the two instruments answer different questions:

A coding test tells youA competency interview tells you
Question answered"Can they solve this puzzle today?""What do they actually know, and how deep?"
Depth signalNone — pass/fail at fixed difficultyEach concept probed until understanding ends (L1–L5)
CoverageWhatever the puzzles happen to touchThe concept map this role requires
Rehearsal resistanceLow — public banks, practicable patternsFollow-ups build on the candidate's own answers
OutputOne number or a verdictA per-concept profile, evidence behind every claim
BoundariesSilent on everything untestedStates what was and wasn't assessed

How an adaptive per-concept interview closes the gap

The gap closes when the instrument changes from a threshold to a probe. An adaptive interview takes each concept the role requires and raises difficulty every time the candidate answers well — from recognition to application to failure modes to expert judgment — until it finds where genuine understanding ends. That endpoint, per concept, is the score.

Rehearsal collapses under this structure, because every follow-up is built on what the candidate just said. A memorized answer survives the first question and not the second — there is no bank to grind, because the next question doesn't exist until the previous answer does.

And the output is built for the decision instead of the gate: a per-concept depth profile, with every claim backed by evidence from the interview itself, plus an explicit account of what wasn't measured. That output has a name — it is competency intelligence, and the hiring decision it powers is a human one, made on a map instead of a number.

Frequently asked questions

Are coding tests useless, then?
No — they are a legitimate coarse filter when application volume is high, and they answer their own narrow question honestly. The failure is scope creep: treating "passed the puzzles" as if it answered "should we hire this engineer for this role." Use a coding test as a filter if you must; never use it as the decision.
What is the difference between a coding test and a competency interview?
A coding test checks correctness on fixed puzzles and outputs a score or verdict. A competency interview adaptively probes each concept a role requires until it finds the candidate's real depth, and outputs a per-concept profile — "concurrency: L5, error handling: L2" — with evidence from the interview behind every claim. The first answers "can they solve this?"; the second answers "what do they actually know?"
How does an interview measure depth instead of correctness?
By raising difficulty adaptively. Each concept starts at a baseline; every strong answer earns a harder follow-up — application, then failure modes, then expert trade-offs — until answers stop holding up. Where they stop is the candidate's measured depth on that concept. Correctness-counting asks how many fixed questions passed; depth-probing asks where understanding ends.
What question should replace "can they code?"
Two questions, in order. First: "what does this candidate actually know, per concept, at what depth?" — a measurement question an adaptive interview can answer. Then: "does that profile match the depths this role requires?" — a judgment call that stays human, but finally has evidence under it.

"Can they code?" was always a proxy for the question you meant to ask. Ask the real one — what do they actually know, and does it match this role — and demand evidence with the answer. That is the difference between screening and deciding.