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(Part 2) When Cabbies Make Ace Coders: Why Skill-Based Hiring Matters In Tech

(Part 2) When Cabbies Make Ace Coders: Why Skill-Based Hiring Matters In Tech

Author
Kumari Trishya
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December 24, 2020
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4 min read
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***

If in case you missed the first part of this blog, I have been talking to our CTO Vishwastam Shukla about how more recruiters and hiring managers need to use skills as the primary criterion for developer hiring. Vishy knows the importance of skills from his days as a coder, and from a very personal experience, which he narrated during our tête-à-tête.Read the first part to know more about this, and scroll down for the rest of our conversation.

***

Question 4: Sometimes when you hire based on skill, you might need to upskill and train an employee to adapt to the nuances of the business. We’ve heard this before from recruiters. Isn’t this a monetary loss to the company then?

For many recruiters, the cost of hiring a candidate is an important metric that influences their decision making. Look at it this way though: a candidate from an Ivy League college would ask for higher compensation. You can use the same money to upskill a lesser-educated candidate and mold them to your organization’s needs. In the long term, the cost: benefit ratio remains the same.There are also some intangible benefits to skill-based hiring which few talk about. It helps in building a stronger bond between employer and employee. The trust and belief you place in a candidate’s skills translates directly into ownership at work. Developers like to let their code speak for them, rather than a piece of paper. Focusing on skills also ensures the candidate values you more as an employer because you're giving them an equal opportunity to showcase their ability - something that every programmer worth their money would love to do.
When you let skills be the only differentiator rather than what's painted on a resume, you show a candidate the respect they deserve. In return, you gain a brand ambassador for life.

Vishy reiterates this with his own example. He spent 6 and a half years at the company he joined as a rookie, learning to be better. Even today, he remembers his team fondly and always gives them their due for making him the engineer he is.

It’s time we placed an equal focus on such softer aspects of employee hiring, as we do on productivity and other metrics. An IBM study shows that employees lacking opportunities to grow and develop (i.e upskill) in a role are 12 times more likely to leave. In that sense, skill-based hiring and upskilling processes can also help you retain your employees longer.

Question 5: Skills versus pedigree, which one wins then?

[ebook2]Vishy graduated from IIIT Allahabad, a premier college in India, at a time when tech education was still firmly formal. With online tools and courses available now, he thinks that there is NO justification for high-expense degrees anymore. Tech education needs to move away from the concept of formal classroom teaching, and recruiters need to understand the actual, rather than the perceived value of a college degree.Checklist for skill based hiring - HackerEarth

Today, a developer could join an online course that runs cohorts for different tech stacks, teach themselves new skills via YouTube tutorials, or use practice platforms to upgrade their skills and go beyond classroom learning. Do they not deserve an opportunity to prove their skills just because their resume says they didn’t study in a Tier-1 college?

It’s also true that college degrees can be used as a proxy for social class and status, thereby reducing social mobility and augmenting inequality. 2020 has brought the conversation around unconscious biases to the fore, and as more recruiters adopt technology to ensure bias-free hiring, we’ll see the predilection towards academic lineage reduce even further.
If intelligence wins over degrees every single time, will we then see a demise of the IITs and Harvards of the world? It might not happen in our lifetime, but there is a definite need for colleges to evolve their curricula and ‘get with the times’. They cannot be charging big money for courses that are available online for cheaper.
Instead, they should aim to roll out a niche set of programs for which the general competency is not available freely. Colleges should also introduce tailor-made programs to help students hone their skills, and include methods to objectively measure progression within their curricula. (Harvard, if you’re listening, we’ve got a new business model for you!)

Question 6: How does someone used to hiring developers based on resumes shift to an objective, skill-based hiring process?

It’s definitely hard, especially for someone who’s been doing this for a while. Up until eight years ago, resumes were the only signals recruiters and hiring managers had about a candidate’s credibility. The first step, therefore, is to look for the same signals but in different places. Look for contributions on open-source forums like GitHub, and other developer communities. Check if a candidate believes in upskilling and what their choicest modes of doing so are. Many developers join hackathons, coding challenges, and boot camps to keep themselves updated with the latest developments in tech.With experienced developers, you can also look at the flavor of work they have done at previous organizations. Most importantly, always have a wide talent pool to choose from instead of restricting yourself with selection mandates. This can be hard to do. The trick lies in using automated tools that help you reach out to a wider candidate pool and create a wide talent funnel. This way, you can significantly improve your chances of hiring right by identifying the right candidates through objective skill-based assessments and choosing the ones that match your company’s requirements for skill.Don’t forget to check if your preferred candidate can write well, in any form or shape. Vishy believes this to be a hugely underrated skill in the tech role; one which most companies wouldn't even mention in their JDs. Even when software developers write code, they are required to document it. Not just because someone else will find it hard to read their code one day, but more so because writing down what you intend to do through your code needs clarity of thought. It needs conviction. It needs you to exercise your cognitive muscles and forces you to be more right and less wrong.

****


Recommended Read: 4 steps to pick the right tech recruiting software
After this long discussion, our CTO had to go back to doing his CTO-y things, and I went back to wondering about how just a generation ago, we were trained to put so much emphasis on 'where' someone had studied, or had worked. It influenced every sphere of our lives; so much so that we forgot to check for the 'what' and 'how' at times.Skill-based hiring brings back that focus on the 'how'. Vishy says a coder's attitude is never taught. It's something they possess innately or learn subconsciously. I think the same is true of recruiters, too. We were taught a certain way of hiring, but it doesn't take a rocket scientist to know the process is flawed. If you've known that innately, or subconsciously, we hope to aid you in your shift towards a more fair and unprejudiced tech hiring process.

To SkillsVille, y'all! And let's all take a cab for good measure :)

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Author
Kumari Trishya
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December 24, 2020
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4 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 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

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

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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