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4 Reasons Why Coding Interviews Are Broken

4 Reasons Why Coding Interviews Are Broken

Author
Wayne Brewer
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October 25, 2021
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5 min read
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Spoiler alert: I’m not a coder. And I’ve never had a coding interview.

But I work for a company whose flagship product for sale is a coding interview tool. So knowing a little bit about the ABCs of conducting great coding interviews that candidates love helps me do my job better. Which is what this blog is all about. Making sure your developer talent does their best work on the job.

Let’s face it, coding interviews in 2023 are broken. And coding interviews that candidates love? That’s the equivalent of trying to find an oasis in the desert. It’s hard to come by.

Coding interviews are like an oasis. Its hard to come by.

At this point? We can hope that with the release of coding interview tools in the market like FaceCode, recruiters will have the means to interview candidates the right way.

But for now, in 2023, tech interviews are still extremely broken. Here are a few things that are wrong with them.

Why are coding interviews broken?

#1) The interview is nothing like the job

Here’s what a typical coding interview will look like:

The candidate walks in, and the tech recruiter presents the candidate with a coding problem. The candidate tries to solve that problem in real time in front of the recruiter.

Feels like a job interview

Sounds simple enough, right?

This could work, except that most of the questions asked in these interviews rarely ever resemble the nature of the work the developer would perform on the job.

For example, developers are often asked to solve a problem using a binary tree in the solution. Most developers agree that this is not the best way to assess tech candidates in 2023. It does not allow coders to demonstrate their greater skill sets that would be more relevant to their jobs.

Instead, recruiters should focus on assessing developers on their ability to write code that does not crash, and their ability to debug and write robust code. These are ‘real’ on-the-job skills that can benefit recruiters by helping them find candidates who can do their job well. And this can benefit candidates by helping them get a taste of what a day at the job can look like for them.

Recommended read: Everything You Need To Know About Adding Job Simulations To Your Hiring Process

#2) Coding interviews are unnecessarily hard

The difficulty level of most coding interviews is high. This could work well for FAANG companies like Facebook and Google which have access to HUGE pools of highly qualified candidates. In this case, a higher difficulty level could work well to shortlist the best coders. These shortlisted candidates can then be interviewed with more specific questions and problems.

In the case of smaller tech companies, coding interviews that are unnecessarily hard rarely work in favor of either party. We live in the times of #TheGreatResignation and good tech talent is rare. For smaller companies, that makes it twice as hard to hire talented candidates that are great for the job.

Here’s what happens for companies other than FAANG who try to copy FAANG’s ridiculously difficult interview style:

  • They lose out on quality talent in a market where the supply of good coders is scarce as it is
  • The coders they do hire using these methods, find out pretty quickly that the real job is NOTHING like the interview they just gave
  • They end up becoming overqualified for their positions and quitting, making your attrition rates rise like the price of a certain dogecoin crypto in early 2021

Ben Awad, a Javascript coding ninja on YouTube does an excellent job of driving this point home. I highly recommend you check his video out on why coding interviews are broken.

Recommended read: Essential Questions To Ask Developers When Recruiting In 2021

#3) Most coding interviews still use word processors to write code

Go ahead, read that again.

Most jobs give their software developers access to IDE’s or Integrated Development Environments like Visual Studio so they can do all kinds of cool things with their code like write code, debug it, compile code, add integrations, and whatnot.

In the interview? The same devs are asked to write their code on Google Docs or worse, Microsoft Word. This isn’t me dissing Google Docs or Word. They are amazing pieces of software that I use to write online, every day. I’m writing this blog on Google Docs right now.

But for code? It’s just not it. It just won’t do. It’s like asking a candidate to ride a bicycle in the interview when the real job tests his skills in riding a motorcycle. It just doesn’t make sense.

#4) The “We only hire developers locally” mindset has got to go

Let’s face it. At this point, remote work is the future. Or at least a hybrid model of remote and in-office work is the road we’re heading towards. And that’s where the problem lies. Most recruiters and hiring managers are still not ready to accept this.

“By sticking to the locally sourced talent model, there’s a ton of untapped talent and potential out there. And when this talent is not engaged and considered as potential hires, it could prove to be missed opportunities.”

There’s an old saying that to catch the biggest fish, you have to cast your net far and wide. When we apply this to tech recruiting, well you get where I’m going with this.

Cast your net wide and hire all across the globe to access the best talent out there. Who knows, your next all-star developer might just be coding somewhere in a far-off land, who happened to run into your job post on LinkedIn.

Recommended read: Hiring Remote Developers Versus Relocation – What To Choose

Here’s how we fix coding interviews

What ends up happening as a result of these broken coding interviews, is you have candidates who would be PERFECT for the job but would never be able to pass these interviews. Or worse, they would never even have access to these interviews just because they aren’t from the local region they are being conducted.

How to fix coding interviews
The solution? We can fix coding interviews by making the interview as close as possible to the real job that the candidate is interviewing for. Simulate the exact ‘day in the job’ environment at the interview and assess the candidate(s) who excel.

Does your company use Visual Studio as its IDE of choice? Great. Give them access to VS at the interview.

Do your best developers fail at debugging their code quickly? Great, test your candidates on their ability to debug problems and the time they take to do that.

Do you give your developer team their space to finish a project within a deadline? Awesome, so stop the ‘turn up the pressure’ act on your candidates and give them enough time and space so they can demonstrate their creativity and skills and show you what they can do on the job.

Finally, the above problems are just touching the surface of the things that are wrong with coding interviews today. That being said, a majority of these problems can be solved by FaceCode– HackerEarth’s premier coding interview tool.

For instance, FaceCode’s built-in IDE ensures that you never need a word processor for coding interviews ever again. Hiring remotely? Access candidates from across the globe with FaceCode’s real-time interviewing feature. Finally, you can play around with the difficulty of the questions by choosing from the vast question library offered across 41 programming languages. Try FaceCode now, for free.

How FaceCode Can Help Improve Your Candidate Experience | FREE EBOOK

And that’s all I have to say about that. I hope you can use these tips to hire some legendary talent into your ranks in the future. Let me know if you found this article interesting and useful in the comments section.

Until next time, happy hiring!

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Author
Wayne Brewer
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October 25, 2021
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5 min read
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Vibe Coding: Shaping the Future of Software

A New Era of CodeVibe 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,...

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 code.

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 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.

Guide to Conducting Successful System Design Interviews in 2025

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...

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.

How Candidates Use Technology to Cheat in Online Technical Assessments

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Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.
  • Secure, sealed-off testing environment
  • AI-enabled live test monitoring
  • Enterprise-grade, industry leading compliance
  • Built-in features to track, detect and flag cheating attempts
Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.
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