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Top Developers Point Out 4 Mistakes With Tech Hiring Assessments

Top Developers Point Out 4 Mistakes With Tech Hiring Assessments

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Kumari Trishya
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February 10, 2022
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5 min read
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Tech recruiting can get a bit dull at times. That’s when I turn to my tried-and-tested source of humor - Dilbert. A laugh-and-a-half helps me remember why I love doing this job - because it matters! I enjoy talking to recruiters and hiring managers and writing about real-life tech hiring problems and their solutions. Here's a recent Dilbert strip I chanced across while working on this piece.

Tech Assessments - Dilbert Cartoon

So, let’s talk about the problem at hand - Assessments - and the many ways in which recruiters can get it wrong. (Not intentionally, of course. No offense meant, amigos! I’ll leave that to Dilbert and his ilk :))

The Unintentional Mistakes Recruiters Make With Tech Assessments

Finding good tech talent is every recruiter’s dream. Sometimes, it can feel like you’re doing everything right; and yet the results are not coming in. We have asked this question to many recruiter friends and they say that many times, the problem lies in the assessment phase of the hiring funnel.Tech assessments sound simple, right? Send a developer a problem statement, ask them to hand in code submissions, review the code and voila! You have a match. In reality, quite a few things can go awry with your tech assessments. Let’s take a look:

1. Long Tech Assessments = Time Sink

Tech hiring is known to be a notoriously long process. However, before you send in another tech assessment that requires days to complete, ask yourself if that’s really necessary. The longer a take-home assessment requires to finish, the less likely it is that the candidate will complete it.Assume that candidates interested in your role are also talking to other companies, many of which will require them to complete take-home projects. As such their projects will stack up, and if your candidates are also working full-time jobs, they simply won't have enough time to complete long projects for free. Additionally, good engineers know how much their time is worth—asking for hours of free code is going to lead experienced engineers to drop off.
So, what can you do to reduce drop offs? Respect your candidate’s time. Keep your assessments short and timely as much as possible. If a certain role requires a long take-home project then consider making it a paid project to retain interest, and to not let the developer feel like their time has been taken for granted.

2. Take Home Assessments + Onsite = Too Many Expectations!

Many companies combine take-home assessments with an onsite test as well. For engineering candidates, this can turn out to be a severely demoralizing experience. Imagine spending hours on a take-home to showcase their best efforts, only to be called into an onsite interview where the manager clearly has no clue about your skills because they never looked at your submission.Recruiters in today’s day and age cannot expect candidates to be at their beck and call. If a take-home needs to be coupled with an onsite assessment, then begin by clearly defining these expectations during the initial screening round. If an engineer is walking through your office doors (virtual or otherwise) for an onsite project, they respect the time they put into the project.
How can you make the onsite experience better for your candidates? First up, understand if your candidate is ready for this. With the pandemic, many of us have become caregivers for our families, and it may not be possible for every candidate to dedicate extra time for both a take-home and an onsite test. If they do agree to an onsite, use the opportunity wisely to see how they integrate with the team. Talk through their code-writing process with them, understand their decision-making process, and become privy to how they think about software.
Don’t, and I repeat - don’t, make it just another hoop for them to jump through.

3. Picking Resumes Over Assessments for Lateral Hires

One of the biggest mistakes many recruiters and hiring managers make when selecting lateral hires is the decision to skip assessments for experienced developers. Sometimes this decision can also be taken in order to prevent any discord - experienced developers have been known to take offense at being asked to ‘prove’ their skill.Allow me to present an analogy - the recipe for baking cake is the same, innit, but not every chef cooks up the exact same dish. Oven temperatures differ. Techniques change. Even the minutest of alterations in the recipe can provide for amazing differences.

So while it’s true that experienced devs come with a proven skill-set, it does not automatically make them the right fit for your team. Technical assessments are a proven way of judging for this ‘team fit’, and you should not gloss over it just because someone has an impressive resume.
What is the secret to using technical assessments for better lateral hiring? When hiring experienced developers you are not looking at problem-solving ability, or a skill fit. Your candidate already has that. What you need to check from a hiring perspective, is what it would be like if the candidate worked on your production code in real time. The closer the prospect’s project is to the real work you and your team does, the better the signal that they are the right choice for your team.

4. Using Manual Reviews Without Proper Benchmarks

There’s proven data to show that top talent is ‘off the market’ within 10 days of them becoming ‘available’. There is a very small window to attract the best of the best, and the scope for errors is nil.Now, imagine you’re a recruiter trying to tap into this talent pool. You spend a couple of days talking to and screening candidates. Then you send across a 2-day project to a candidate. On submission, you can email it across to your hiring manager for review. The manual review takes another two days. By this time, a week has already passed and you just have 3 days to schedule interviews, and make an offer. Another company that uses automated assessments gets the edge over you because they used a much more efficient method of assessing and evaluating candidates.Developer Hiring Statistics - hackerEarthAutomation ensures speed, accuracy, and an objective bias-free evaluation process where every developer is assessed according to standardized benchmarks. Apart from efficiency, automated assessments are also beneficial in removing errors during manual reviews. In short, by using automated assessments over manual reviews you are creating an error-free process where only the top skills filter through.

Creating The Perfect Tech Assessment

We’ve spoken to many tech recruiters over the years to understand what makes a good coding assessment. Here’s what we gathered:
  • A good coding assessment is true to the role at hand, and is customized to assess the exact skills required for the role. You cannot hire exceptional people with generic assessments.
  • It needs to be standardized. So, if there are 20 applicants for a given role, all 20 should be asked to take the exact same test, so that the results can be benchmarked.
  • A good coding assessment should provide a more accurate work sample than whiteboard interviews or timed challenges can ever do.
  • With a take-home coding assessment, the key is to allow the candidate to out their best foot forward. The assumption is that by taking the test in the comfort of their homes at their own convenience, they will be under less pressure and will perform better. So, there should not be an element of unwanted stress by making the assessment more complex than is necessary.
  • At all times, it is imperative to RESPECT the candidate, their time, and their skills. If you’re asking them to code for 10 days for free, that’s not the hallmark of a good employer.
  • Using automated assessment tools and question templates can go a long way in helping you make your assessment process error-free. At the end of it all, do remember that while there may not be a one-size-fits all solution, there are some tenets that will remain permanent.
Don’t use the take-home assessment as ‘just another step’ in the hiring process. Use it wisely, so you can save time in the interview process, and not lose out on hiring the top talent due to inefficient processes. A well-crafted technical assessment can help you better evaluate your talent pool, and take some of the stress off of your hiring managers -- but it works well only when you remember to respect and stay invested in your candidates.

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Author
Kumari Trishya
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February 10, 2022
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5 min read
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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 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

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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

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...

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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