Whiteboard Interviews: Why They’re Bad For Technical Interviewing

Whiteboard interviews have traditionally been a go-to method for evaluating technical candidates. However, as hiring practices evolve, more companies are questioning their validity and fairness. While these interviews aim to test a candidate’s problem-solving and coding abilities, they often fail to reflect real-world scenarios and can create unnecessary barriers for talented professionals.

Here’s a detailed look at why whiteboard interviews are falling short, supported by alternative methods that deliver better results for technical hiring.

Why whiteboard interviews will always fall short

1. Lack of real-world relevance

Whiteboard interviews often focus on theoretical questions that do not reflect the practical challenges developers face in their daily work. For example, while solving algorithmic puzzles might demonstrate logical thinking, it doesn’t showcase skills like debugging, optimizing performance, or integrating APIs. These are far more relevant in a real-world tech role.

Illustration: A company might ask candidates to write a quicksort algorithm on a whiteboard, but in reality, most developers would use pre-built library functions for such tasks and focus their time on solving more complex application-specific problems.

Whiteboard interviews also fail to consider the collaborative nature of modern software development. Engineers work in teams, consult documentation, and use advanced tools to troubleshoot and innovate—none of which are accounted for in a whiteboard setting.

2. Encourages rote memorization

Instead of evaluating problem-solving skills or creativity, whiteboard interviews tend to reward candidates who can recall academic concepts under pressure. This approach prioritizes “textbook” knowledge over practical application.

Example: A front-end developer might ace a whiteboard question on JavaScript promises but fail to demonstrate their expertise in real-world scenarios like debugging asynchronous behavior in a live application.

3. Bias in evaluation

Whiteboard interviews often amplify implicit biases in hiring. For instance, a candidate who performs confidently in a live, high-pressure environment may appear more competent, even if their technical skills are weaker than another candidate who struggles with anxiety in the same situation.

Bias also creeps in during subjective evaluations. Interviewers might unconsciously favor candidates whose thought processes align with their own, penalizing those who approach problems differently but could bring unique perspectives to the role.

Case in point: Studies show that women and candidates from underrepresented groups often underperform in whiteboard interviews due to heightened stress or lack of familiarity with the format, even when they possess exceptional technical abilities.

4. Misses soft skills and collaboration

Whiteboard interviews completely ignore critical soft skills like communication, teamwork, and adaptability—traits that are vital for success in modern tech environments. Technical brilliance is rarely enough; candidates must also demonstrate the ability to work cohesively with diverse teams and adapt to rapidly changing project requirements.

5. Lack of iterative problem-solving

In real-world development, engineers solve problems iteratively, relying on feedback and testing their solutions. Whiteboard interviews, however, demand perfect solutions in one attempt, disregarding how candidates approach debugging or refining their work.

Better alternatives to whiteboard interviews your team needs to use now

Modern hiring practices focus on assessing candidates in realistic environments, ensuring evaluations are fair, inclusive, and relevant to the role. Here are some effective alternatives:

1. Hands-on coding assessments

HackerEarth’s coding assessments allow candidates to solve real-world problems in a familiar coding environment. Recruiters can test skills like debugging, optimizing algorithms, or building scalable solutions, providing a clearer picture of job readiness.

Example: Instead of asking candidates to write pseudocode for a sorting algorithm, HackerEarth enables recruiters to test how candidates optimize database queries or fix broken code in real time.

2. Take-home projects

Assigning take-home assignments allows candidates to solve problems on their own time using the tools they’re accustomed to. These projects simulate actual job responsibilities and give recruiters a better sense of a candidate’s technical depth.

3. Pair programming interviews

Pair programming sessions involve working collaboratively on a coding task with an interviewer. This method assesses not only technical skills but also a candidate’s ability to communicate, accept feedback, and collaborate in real-time.

4. Virtual hackathons

Hackathons hosted on platforms like HackerEarth engage candidates in problem-solving while mimicking real-world challenges. They provide insights into creativity, teamwork, and technical expertise, all while offering a more enjoyable candidate experience.

Case study: A tech startup used a HackerEarth hackathon to replace traditional interviews. Candidates worked in teams to solve live problems, and the top performers were hired for their ability to think critically and collaborate effectively.

5. Role-specific assessments

Instead of relying on generic whiteboard tasks, focus on role-specific challenges. For example, assess a backend developer’s ability to design scalable APIs or a front-end developer’s expertise in creating responsive UI components. HackerEarth’s assessment platform allows recruiters to customize tasks for any technical role.

The role of HackerEarth in skill-first tech hiring

HackerEarth enables organizations to move beyond outdated hiring methods like whiteboard interviews by adopting a skill-first hiring philosophy—a process that focuses on what candidates can do rather than how they perform under artificial, high-stakes scenarios.

Skill-first hiring with HackerEarth

Real-world simulations:
HackerEarth provides coding assessments that mimic actual job responsibilities, allowing candidates to demonstrate their skills in solving real-world problems. For example, a back-end developer might be tasked with designing a scalable API, while a DevOps candidate could work on a task requiring CI/CD pipeline configuration.
Diverse assessment types:
From debugging challenges to take-home projects, HackerEarth allows recruiters to evaluate candidates holistically. By incorporating tests for coding, database management, or even domain-specific tasks, HackerEarth ensures candidates are assessed on what truly matters.‍
Bias-free evaluations:
HackerEarth’s anonymized assessments remove identifiers like name, gender, and educational background, ensuring that hiring decisions are based solely on skill and performance. This approach promotes diversity and inclusion, helping companies build stronger, more innovative teams.

Empowering collaboration and adaptability

HackerEarth also supports collaborative hiring practices, such as pair programming assessments and virtual hackathons, where candidates solve challenges in a team environment. This not only highlights their technical expertise but also evaluates how well they communicate, adapt to feedback, and contribute to group problem-solving—critical traits for thriving in modern tech roles.

Case Study: L&T Infotech leveraged HackerEarth to conduct collaborative assessments for their global tech hiring drive. By testing candidates in realistic scenarios, they identified top talent faster and achieved a 40% improvement in time-to-hire.

Data-driven hiring insights

HackerEarth’s platform provides detailed performance analytics, allowing recruiters to pinpoint a candidate’s strengths and areas for improvement. Metrics like code efficiency, logical thinking, and adaptability are captured, ensuring that the most qualified candidates are selected for the role.

Beyond coding: soft skill assessment

HackerEarth doesn’t stop at technical skills. It also enables recruiters to assess communication, critical thinking, and leadership potential through non-coding challenges and custom evaluations. This holistic approach ensures that candidates meet both the technical and cultural requirements of the role.

HackerEarth is leading the transformation of technical hiring by eliminating outdated practices like whiteboard interviews. Its tools and methodologies focus on skill-first hiring, ensuring candidates are evaluated in environments that reflect actual work conditions. By integrating HackerEarth into their recruitment process, companies have been able to hire faster, reduce biases, and build teams that are not only technically competent but also equipped to collaborate, adapt, and succeed.

So, if you too are ready to improve your TTH and adopt a skill-first hiring strategy, book your demo here!

Revolutionizing Mobile Talent Hiring: The HackerEarth Advantage

The demand for mobile applications is exploding, but finding and verifying developers with proven, real-world skills is more difficult than ever. Traditional assessment methods often fall short, failing to replicate the complexities of modern mobile development.

Introducing a New Era in Mobile Assessment

At HackerEarth, we're closing this critical gap with two groundbreaking features, seamlessly integrated into our Full Stack IDE:

Now, assess mobile developers in their true native environment. Our enhanced Full Stack questions now offer full support for both Java and Kotlin, the core languages powering the Android ecosystem. This allows you to evaluate candidates on authentic, real-world app development skills, moving beyond theoretical knowledge to practical application.

Say goodbye to setup drama and tool-switching. Candidates can now build, test, and debug Android and React Native applications directly within the browser-based IDE. This seamless, in-browser experience provides a true-to-life evaluation, saving valuable time for both candidates and your hiring team.

Assess the Skills That Truly Matter

With native Android support, your assessments can now delve into a candidate's ability to write clean, efficient, and functional code in the languages professional developers use daily. Kotlin's rapid adoption makes proficiency in it a key indicator of a forward-thinking candidate ready for modern mobile development.

Breakup of Mobile development skills ~95% of mobile app dev happens through Java and Kotlin — This chart illustrates the importance of assessing proficiency in both modern (Kotlin) and established (Java) codebases.

Streamlining Your Assessment Workflow

The integrated mobile emulator fundamentally transforms the assessment process. By eliminating the friction of fragmented toolchains and complex local setups, we enable a faster, more effective evaluation and a superior candidate experience.

Old Fragmented Way vs. The New, Integrated Way — Visualize the stark difference: Our streamlined workflow removes technical hurdles, allowing candidates to focus purely on demonstrating their coding and problem-solving abilities.

Quantifiable Impact on Hiring Success

A seamless and authentic assessment environment isn't just a convenience, it's a powerful catalyst for efficiency and better hiring outcomes. By removing technical barriers, candidates can focus entirely on demonstrating their skills, leading to faster submissions and higher-quality signals for your recruiters and hiring managers.

A Better Experience for Everyone

Our new features are meticulously designed to benefit the entire hiring ecosystem:

For Recruiters & Hiring Managers:

Accurately assess real-world development skills.
Gain deeper insights into candidate proficiency.
Hire with greater confidence and speed.
Reduce candidate drop-off from technical friction.

For Candidates:

Enjoy a seamless, efficient assessment experience.
No need to switch between different tools or manage complex setups.
Focus purely on showcasing skills, not environment configurations.
Work in a powerful, professional-grade IDE.

Unlock a New Era of Mobile Talent Assessment

Stop guessing and start hiring the best mobile developers with confidence. Explore how HackerEarth can transform your tech recruiting.

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing c

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable or Hostinger Horizons enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

Develop an understanding of basics of system design and architecture
Familiarize yourself with commonly asked systems design interview questions
Read about system design case studies for popular applications
Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

Plan the extent of the topics and scope of discussion in advance
Clearly define the evaluation criteria and communicate expectations
Quantify constraints, inputs, boundaries and assumptions
Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

Ask follow-up questions to challenge a solution
Probe candidates to gauge real-time logical reasoning skills
Make it a conversation and take notes of important pointers and outcomes
Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

Encourage candidates to explore and consider alternative solutions
Work with the candidate to drill the problem into smaller tasks
Provide context and supporting details to help candidates stay on track
Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.