Transparency
Editorial policy and methodology
Our public resources are designed to help candidates practise a specific interview skill. This page explains how we decide what to publish and how we keep it useful.
What we publish
We publish practical frameworks, worked examples, checklists, and practice prompts for behavioral, technical, product, data, and system design interviews. A page must give the reader something they can do: clarify a question, structure an answer, test an assumption, or review a practice attempt.
How content is developed
Topics are selected from recurring preparation problems rather than search keywords alone. We outline the decision a candidate needs to make, explain the reasoning behind the framework, include limitations and trade-offs, and finish with prompts for independent practice. We avoid presenting generic encouragement, copied material, or guaranteed outcomes as advice.
Review and updates
Pages are reviewed when they are published and revisited when the product changes, a method needs clarification, or readers identify a missing edge case. Updates should improve accuracy or usefulness, not inflate a page with repetitive text. The publication date and update date shown on guide pages are intended to reflect the current editorial version.
AI feedback and responsible use
The practice product can identify patterns in a response, such as structure, clarity, pacing, and coverage. AI feedback can be incomplete or wrong; it is not a hiring decision, a professional credential, or a promise of success. Candidates should verify suggestions against their own experience and the requirements of the role.
Corrections and reader feedback
If a guide contains an error, unclear instruction, or inaccessible example, please tell us what needs attention and include the page URL. We use reader feedback to prioritize revisions and will correct material issues as part of the next content review.
Contact the team about a guide →