“Interns are the bottom of the surgical food chain” — Dr. Bailey, Grey’s Anatomy

I’m sure a lot of you are familiar with this quote from the popular medical drama, where surgical interns are made to do all the grunt work. They are treated as nobodies—but interns in the tech industry are a whole other ball game! Tech companies compete with each other to hire freshers, interns, and students. They want to build and nurture relationships with the next generation of workers as early as possible.

Consequently, campus recruiting becomes the holy grail for companies and their big chance to snap up tomorrow’s top talent!

With campus hiring coming up in a few months, we thought it would be a great idea to go behind the scenes for this event. Come, spend a day with our campus recruiters from HackerEarth, and see for yourself!

A special shoutout to our Talent Acquisition Manager, Preethi Saakre for all the insider information that shaped this blog and allowed us to go into great detail about the workings of a recruiting team during campus recruitment!

P.S. This article is an extension of the first part, Spend A Day With A Tech Recruiter, where we debunk plenty of misconceptions floating around about tech recruiters. If you haven’t read it already, here you go.

What is campus recruiting?

Campus recruitment (not to be confused with mass hiring) involves attracting, sourcing, engaging, and hiring young talent for entry-level positions. Companies with high-volume recruiting needs opt for campus hiring. Moreover, whether it’s on-campus recruiting, virtual, or hybrid, the responsibilities of campus recruiters stay more or less the same.

On the other hand, mass hiring, while interchangeably called campus hiring varies in the type of candidates companies look for. Mass hiring drives are mainly to recruit experienced candidates and are generally not open to fresh college graduates.

How HackerEarth can spice up your campus recruiting strategy

4 Ways HackerEarth’s Campus Hiring Solution Can Help Campus Recruiters Hire Better

Unlike traditional campus hiring, which happens once a year, a virtual campus recruitment drive can take place in phases throughout the year. That gives you many options to take your remote hiring strategy up a notch –

#1 Encourage students to become brand ambassadors

Invest time in students even before they graduate. Offer mentorship and networking opportunities through a student brand ambassador program. This helps you create targeted brand awareness as well as show the students that you care about them.

The HackerEarth Campus Ambassador program offers free mock interviews along with a certificate of appreciation, the opportunity to network with leading coders, and to be taught by engineering leaders at our company. Join our campus ambassadors to experience the HackerEarth advantage.

#2 Host hackathons to better engage with students

Instead of relying only on 1:1 interviews, conduct hackathons as well. Those students who couldn’t perform well in interviews might outdo themselves in a practical setting.

If you’re looking for a hands-off experience when organizing a hackathon, then HackerEarth is your best bet. All our online hackathons and hiring challenges are fully curated managed services. To put it simply, you get the engagement you need, without any bandwidth drain.

#3 Invest in a remote-ready campus recruitment platform

Virtual campus recruitment can open so many doors in terms of a wider, bigger talent pool, lesser costs, and better returns. To fully capitalize on this, you need a trusty platform to dot the i’s for you.

Enter HackerEarth’s campus hiring solution that has helped hundreds of companies ease the burden of remotely assessing students from universities across the globe. Be it assessing students through coding assessments or interviewing them with our tech video interview tool, FaceCode, we’ve got you covered.

There’s more where that came from. Bake in extra innovative elements as part of your tech recruitment strategy to capture the attention of your potential talent pool. 👇

Also read: Create The Perfect Virtual Recruiting Strategy For Universities With These Tips

A typical day for campus recruiters looks like…

Create a core team of campus recruiters and hiring managers

You need a dedicated recruiting team to drive the best results from your campus hiring drive. Put together a mix of campus recruiters and hiring managers to carry out the different stages of the process including screening, interviewing, and shortlisting candidates.

The next crucial step is to pinpoint your hiring goals and requirements. Some questions to ask that will help you identify your needs –

Who is your ideal candidate for this exercise?
Which team would need to add new employees in the next six months?
What departments (for instance, engineering or sales) are short-staffed currently?

Make a list of suitable colleges and universities

Now that you have your ideal candidate persona, figure out what colleges and universities you need to target.

Are you looking at tier 1 universities or tier 2 and tier 3 universities as well?
Are you looking to hire students from any engineering field including computer science, electronics and communications or are you looking for purely technical candidates, etc?
How many tech roles and non-tech roles are you hiring for?
What businesses in your company need fresh talent?

Try and target a diverse range of universities to build an inclusive pipeline of fresh talent.

Reach out to the respective placement coordinators

Here’s an important part of campus recruitment that has nothing to do with attracting potential candidates. Bonding with the university placement coordinators!

If you want your pick of the season, you need to begin your recruitment right at the beginning. And who is in charge of that? Yes, you guessed it, the placement coordinators. To even get on their pre-selected list of companies, you need to woo them first.

Along with offering competitive salary packages and benefits (which almost every company would do), you need to stand out. This is where campus recruiters can shine. Use all the experience you’ve gained building and maintaining relationships with candidates and channel that here.

Create and nurture strong long-term bonds with the placement cell and build trust with the colleges well before the campus hiring season begins. So when it starts, they know whom to reach out to.

Sidebar:

The first three steps are carried out ahead of the campus recruiting season. This ensures you are prepared to tackle this head-on and deliver the best outcomes possible.

Once the campus drives begin, reach out to the respective campus placement coordinators with the job descriptions for roles, EVPs, relevant company data, if you have any cutoff percentage for students, etc. This will make it easier for them to select those students who are eligible and invite them to participate in the selection process.

Get a list of students who applied

Ask your coordinators to share a list of students who have applied for your company. Depending on the pre-defined criteria, filter the list further based on their academic performance in school and college, core specialty, etc.

Then let the placement coordinator know that this is your final list and you would like to send them a screening test post conducting your pre-placement talks.

Conduct pre-placement discussions

Why campus recruiters should improve their pre-placement talks

Send the students who’ve applied to your company relevant company information like roles/responsibilities, salary range, location of the role, etc.

Arrange for your HR lead or the engineering department head to hold a pre-placement talk for these students. Trying to get potential students hooked about working for your company by holding one single discussion can only take you so far. Especially on a day when students are under immense pressure to perform well during interviews.

Additionally, do this. For having a better shot at keeping your brand top of mind for students, plan and host several informative virtual events throughout the year. Online hackathons, virtual career fairs, and QnAs with the leadership team can all shine a light on your workplace culture, career paths, and so on.

Also read: 5 Best Practices For An Effective Hybrid Campus Hiring Strategy

Assess all the candidates who applied

If it’s an on-campus hiring drive, then the next step is to shortlist candidates through a group discussion round (which is quickly becoming outdated) and a skill assessment test.

The best part of a virtual/hybrid campus recruiting process is it is extremely candidate-friendly. Instead of rushing through the screening phase to quickly run coding assessments for students and then reveal the final selection can be tedious to carry out in a day.

When you’re remotely assessing students, you can check when they are available to take the test and send them an assessment invite, accordingly.

With an advanced campus hiring solution like HackerEarth, you get to assess students remotely through accurate online coding assessments and robust proctoring.

Also read: Importance Of Online Proctoring In University Hiring

Schedule interviews with the shortlisted candidates

During an on-campus recruitment process, the students are interviewed on the same day. Those who cleared the assessment round will have 3-4 rounds of interviews, depending on what the hiring team decides. Students who don’t meet the criteria are eliminated after each round.

The first two rounds are technical, the third round will be the managerial round with the engineering head, and the final round is the HR round. Here the student is evaluated based on culture fit and is rarely eliminated at this stage.

In a virtual or hybrid setting, if there is bandwidth the interviews take place on that day itself. Otherwise, they are scheduled within the next two days.

Set up, invite, and conduct coding interviews on a collaborative, real-time code editor such as FaceCode. This is a smart remote interviewing tool that helps you make objective, data-driven decisions thanks to AI-powered insights.

How L&T Infotech Partnered With HackerEarth To Hire Freshers | CASE STUDY

You know what happens next! Announce who made the cut

How campus recruiters feel when rolling out the offer letter

But wait…The day is not over yet

If you think you’re done for the day and you get to put your feet up, then you’re wrong 😛 Tieing up loose ends after wrapping up can be the most important step of all, especially in the traditional way of conducting campus hiring.

There is documentation to take care of, carefully putting together lists of shortlisted candidates from each panel, sending out feedback forms, and closing emails.

And you have to prepare to do this all over again, the next day, until the campus hiring season comes to an end.

Drink lots of coffee, you’re going to need it!

Also read: The Biggest Challenges Faced By Recruiters In University Hiring (+ Perfect Solutions)

There you have it…Campus recruitment simplified

As seen in this article, it takes a village to maneuver campus hiring season. Be it in-person or online, running a successful campus recruitment drive is a Herculean task.

Campus recruiters have their work cut out for them. They shoulder a lot of responsibility to do right by their company and their candidates.

With support and a solid campus recruiting strategy, it is possible to run the show seamlessly. Moreover, it is a straightforward way to engage and nurture fresh, undiscovered talent!

As always, happy hiring 🙂

I Used AI to Build a "Simple Image Carousel" at VibeCodeArena. It Found 15+ Issues and Taught Me How to Fix Them.

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My Learning Journey

I wanted to understand what separates working code from good code. So I used VibeCodeArena.ai to pick a problem statement where different LLMs produce code for the same prompt. Upon landing on the main page of VibeCodeArena, I could see different challenges. Since I was interested in an Image carousal application, I picked the challenge with the prompt "Make a simple image carousel that lets users click 'next' and 'previous' buttons to cycle through images."

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Within seconds, I had code from multiple LLMs, including DeepSeek, Mistral, GPT, and Llama. Each code sample also had an objective evaluation score. I was pleasantly surprised to see so many solutions for the same problem. I picked gpt-oss-20b model from OpenAI. For this experiment, I wanted to focus on learning how to code better so either one of the LLMs could have worked. But VibeCodeArena can also be used to evaluate different LLMs to help make a decision about which model to use for what problem statement.

The model had produced a clean HTML, CSS, and JavaScript. The code looked professional. I could see the preview of the code by clicking on the render icon. It worked perfectly in my browser. The carousel was smooth, and the images loaded beautifully.

But was it actually good code?

I had no idea. That's when I decided to look at the evaluation metrics

What I Thought Was "Good Code"

A working image carousel with:

Clean, semantic HTML
Smooth CSS transitions
Keyboard navigation support
ARIA labels for accessibility
Error handling for failed images

It looked like something a senior developer would write. But I had questions:

Was it secure? Was it optimized? Would it scale? Were there better ways to structure it?

Without objective evaluation, I had no answers. So, I proceeded to look at the detailed evaluation metrics for this code

What VibeCodeArena's Evaluation Showed

The platform's objective evaluation revealed issues I never would have spotted:

Security Vulnerabilities (The Scary Ones)

No Content Security Policy (CSP): My carousel was wide open to XSS attacks. Anyone could inject malicious scripts through the image URLs or manipulate the DOM. VibeCodeArena flagged this immediately and recommended implementing CSP headers.

Missing Input Validation: The platform pointed out that while the code handles image errors, it doesn't validate or sanitize the image sources. A malicious actor could potentially exploit this.

Hardcoded Configuration: Image URLs and settings were hardcoded directly in the code. The platform recommended using environment variables instead - a best practice I completely overlooked.

SQL Injection Vulnerability Patterns: Even though this carousel doesn't use a database, the platform flagged coding patterns that could lead to SQL injection in similar contexts. This kind of forward-thinking analysis helps prevent copy-paste security disasters.

Performance Problems (The Silent Killers)

DOM Structure Depth (15 levels): VibeCodeArena measured my DOM at 15 levels deep. I had no idea. This creates unnecessary rendering overhead that would get worse as the carousel scales.

Expensive DOM Queries: The JavaScript was repeatedly querying the DOM without caching results. Under load, this would create performance bottlenecks I'd never notice in local testing.

Missing Performance Optimizations: The platform provided a checklist of optimizations I didn't even know existed:

No DNS-prefetch hints for external image domains
Missing width/height attributes causing layout shift
No preload directives for critical resources
Missing CSS containment properties
No will-change property for animated elements

Each of these seems minor, but together they compound into a poor user experience.

Code Quality Issues (The Technical Debt)

High Nesting Depth (4 levels): My JavaScript had logic nested 4 levels deep. VibeCodeArena flagged this as a maintainability concern and suggested flattening the logic.

Overly Specific CSS Selectors (depth: 9): My CSS had selectors 9 levels deep, making it brittle and hard to refactor. I thought I was being thorough; I was actually creating maintenance nightmares.

Code Duplication (7.9%): The platform detected nearly 8% code duplication across files. That's technical debt accumulating from day one.

Moderate Maintainability Index (67.5): While not terrible, the platform showed there's significant room for improvement in code maintainability.

Missing Best Practices (The Professional Touches)

The platform also flagged missing elements that separate hobby projects from professional code:

No 'use strict' directive in JavaScript
Missing package.json for dependency management
No test files
Missing README documentation
No .gitignore or version control setup
Could use functional array methods for cleaner code
Missing CSS animations for enhanced UX

The "Aha" Moment

Here's what hit me: I had no framework for evaluating code quality beyond "does it work?"

The carousel functioned. It was accessible. It had error handling. But I couldn't tell you if it was secure, optimized, or maintainable.

VibeCodeArena gave me that framework. It didn't just point out problems, it taught me what production-ready code looks like.

My New Workflow: The Learning Loop

This is when I discovered the real power of the platform. Here's my process now:

Step 1: Generate Code Using VibeCodeArena

I start with a prompt and let the AI generate the initial solution. This gives me a working baseline.

Step 2: Analyze Across Several Metrics

I can get comprehensive analysis across:

Security vulnerabilities
Performance/Efficiency issues
Performance optimization opportunities
Code Quality improvements

This is where I learn. Each issue includes explanation of why it matters and how to fix it.

Step 3: Click "Challenge" and Improve

Here's the game-changer: I click the "Challenge" button and start fixing the issues based on the suggestions. This turns passive reading into active learning.

Do I implement CSP headers correctly? Does flattening the nested logic actually improve readability? What happens when I add dns-prefetch hints?

I can even use AI to help improve my code. For this action, I can use from a list of several available models that don't need to be the same one that generated the code. This helps me to explore which models are good at what kind of tasks.

For my experiment, I decided to work on two suggestions provided by VibeCodeArena by preloading critical CSS/JS resources with <link rel="preload"> for faster rendering in index.html and by adding explicit width and height attributes to images to prevent layout shift in index.html. The code editor gave me change summary before I submitted by code for evaluation.

Step 4: Submit for Evaluation

After making improvements, I submit my code for evaluation. Now I see:

What actually improved (and by how much)
What new issues I might have introduced
Where I still have room to grow

Step 5: Hey, I Can Beat AI

My changes helped improve the performance metric of this simple code from 82% to 83% - Yay! But this was just one small change. I now believe that by acting upon multiple suggestions, I can easily improve the quality of the code that I write versus just relying on prompts.

Each improvement can move me up the leaderboard. I'm not just learning in isolation—I'm seeing how my solutions compare to other developers and AI models.

So, this is the loop: Generate → Analyze → Challenge → Improve → Measure → Repeat.

Every iteration makes me better at both evaluating AI code and writing better prompts.

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What This Means for Learning to Code with AI

This experience taught me three critical lessons:

1. Working ≠ Good Code

AI models are incredible at generating code that functions. But "it works" tells you nothing about security, performance, or maintainability.

The gap between "functional" and "production-ready" is where real learning happens. VibeCodeArena makes that gap visible and teachable.

2. Improvement Requires Measurement

I used to iterate on code blindly: "This seems better... I think?"

Now I know exactly what improved. When I flatten nested logic, I see the maintainability index go up. When I add CSP headers, I see security scores improve. When I optimize selectors, I see performance gains.

Measurement transforms vague improvement into concrete progress.

3. Competition Accelerates Learning

The leaderboard changed everything for me. I'm not just trying to write "good enough" code—I'm trying to climb past other developers and even beat the AI models.

This competitive element keeps me pushing to learn one more optimization, fix one more issue, implement one more best practice.

How the Platform Helps Me Become A Better Programmer

VibeCodeArena isn't just an evaluation tool—it's a structured learning environment. Here's what makes it effective:

Immediate Feedback: I see issues the moment I submit code, not weeks later in code review.

Contextual Education: Each issue comes with explanation and guidance. I learn why something matters, not just that it's wrong.

Iterative Improvement: The "Challenge" button transforms evaluation into action. I learn by doing, not just reading.

Measurable Progress: I can track my improvement over time—both in code quality scores and leaderboard position.

Comparative Learning: Seeing how my solutions stack up against others shows me what's possible and motivates me to reach higher.

What I've Learned So Far

Through this iterative process, I've gained practical knowledge I never would have developed just reading documentation:

How to implement Content Security Policy correctly
Why DOM depth matters for rendering performance
What CSS containment does and when to use it
How to structure code for better maintainability
Which performance optimizations actually make a difference

Each "Challenge" cycle teaches me something new. And because I'm measuring the impact, I know what actually works.

The Bottom Line

AI coding tools are incredible for generating starting points. But they don't produce high quality code and can't teach you what good code looks like or how to improve it.

VibeCodeArena bridges that gap by providing:

✓ Objective analysis that shows you what's actually wrong
✓ Educational feedback that explains why it matters
✓ A "Challenge" system that turns learning into action
✓ Measurable improvement tracking so you know what works
✓ Competitive motivation through leaderboards

My "simple image carousel" taught me an important lesson: The real skill isn't generating code with AI. It's knowing how to evaluate it, improve it, and learn from the process.

The future of AI-assisted development isn't just about prompting better. It's about developing the judgment to make AI-generated code production-ready. That requires structured learning, objective feedback, and iterative improvement. And that's exactly what VibeCodeArena delivers.

Here is a link to the code for the image carousal I used for my learning journey

#AIcoding #WebDevelopment #CodeQuality #VibeCoding #SoftwareEngineering #LearningToCode

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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.

Spend A Day With A Tech Recruiter During Campus Hiring

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