Hi, I’m Anas, the founder of ReviewIQ. I’m working on the step between finishing a coding course and trusting your own judgment on unfamiliar code.
The exercise asks you to identify mistakes, explain what could break, and propose a fix before any answers are shown. AI grades the written findings against the exercise’s planted issues, then shows caught/missed feedback and explanations.
A review is more useful when it connects three things: the assumption being made, a concrete case where that assumption fails, and a test for the proposed fix. Listing suspicious-looking lines alone doesn’t explain the risk.
The current guest exercise is one fixed Backend/Python/Mid-level challenge, free to complete before signup. An account is needed to save the result and continue. This is hands-on practice and feedback, not a course, credential or job guarantee.
Try it: ReviewIQ — Build code-review judgment
The screenshot below is an actual founder test: 4.3/10, 1 issue caught and 2 missed. These are demonstration results, not customer performance.
For people designing AI-assisted practice: would you reveal missed issues immediately after submission, or offer another attempt first? How would you discourage learners from inventing bugs just because an exercise says there are hidden mistakes?