#DidYouKnow: 92% of recruiters use social media for hiring, and there are more than 100 portals serving as job boards.
#DidYouKnow: Over 87% of non-management and salaried employees were recruited through social media.
#DidYouKnow: Over 82% of management employees came from social media.
The above survey by the Society of Human Resource Management (SHRM) gives some deep insights into the rising importance of social media in recruitment.
What is Social HR?
Social media has seen an unparalleled rise in the last few years and has redefined the way we use the internet.
It won’t be wrong if we say it has created a parallel ecosystem for individuals and businesses alike.
Now organizations, and even the government can no longer survive on bi-monthly newspaper advertisements or get away with mere yearly employee brochures.
They need to be active on social media to cater to employees, customers, and, sometimes, even business partners.
The challenge lies in not just finding the right talent through social media but also in nurturing it while ensuring enough privacy.
Often while dealing with talent challenges, HR is unable to draw the line between maintaining the traditions of the organization while doing away with the legacy model.
Especially, when it comes to tools like social media and individual freedom of speech for employees on online platforms.
Most of the concerns about being around the privacy or freedom of the candidates.
In an age where one negative feedback on an online portal can impact your prospects of getting the best candidates, it’s extremely important for Human Resource personnel to be conscious of the choices they make.
Here’s how you can use social media for your talent management purposes and how you can improve on Social HR.
Check out this detailed video on social media for the Human resource by Kristy Bryant.
While social media is credited to be one of the reliable sources for garnering information about prospective employees, it’s also accused of revealing information like religion, caste, color, political affiliation, gender, marital status, etc.
These are the usual parameters of discrimination that work against diversity initiatives. Hence, it’s important for HR personnel to devise methods to screen talent smartly.
As Allyson Willoughby, former General Counsel and SVP of People (HR) Glassdoor, say on the use of social media in the screening process,
“Don’t do anything different with social media than you would do with a face-to-face interview.”
According to experts, the best way to deploy social media accounts in hiring processes is to involve a third party who does the screening for you.
People who do the screening need to be educated about the exact requirements for the designation they are shortlisting the candidates for.
This serves as a firewall between the employer and the candidate and ensures an unbiased approach.
When they (HR) do the background check of the candidate through social media as part of the screening process, it’s important for them to keep a check on the legal implications of the process.
Use of pre-assessment tools, like Hackerearth Recruit, can also be a great idea for HR managers looking for zero human interference in their recruitment processes.
Like the US, India also has laws against discrimination against minoritiesin recruitment, so it’s important for the organization to adhere to the terms and conditions of these policies.
How should Social Human Resource use online properties wisely
One of the key challenges that have surfaced with the deployment of social media channels for recruitment purposes is that they don’t represent the global candidate pool.
According to a recent survey, LinkedIn and Facebook have shown a smaller user base of minority communities in comparison to the general population.
Hence, diversity initiatives take a hit in situations like these.
Thus, the HR person needs to resort to traditional recruitment routes of job boards, advertisements in dailies, and mention it clearly on their website that they believe in equal opportunity.
You can even encourage your current employees to recommend their friends from minority communities and attach a greater referral bonus to such initiatives to boost your diversity efforts.
How can Social HR ensure positive image on social media
Recently, a few incidences surfaced where organizations faced the brunt of negative feedback from estranged employees.
Situations like these put the HR personnel in a tight spot as they don’t have much control over employees who have left the job and even if they do have, through some legal clauses, it’s not financially feasible for them to pursue the case against a single or a bunch of employees.
Moreover, it dampens the morale of current employees.
The bigger issue with sites such as Glassdoor or other job portals is that they don’t really delete the comments sent by the reviewers.
The question is, how does HR counter the negativity against the brand?
The wiser thing to do here would be to involve your social media managers or Online Reputation Management experts at the right time as larger organizations receive dozens of such negative comments on a monthly basis and that too on multiple portals.
Usually, digital marketing teams are equipped with tools that help you track down multiple websites in the shortest time.
Identification of negative comments sooner helps counter them faster.
A positive or humble reply to the negative comment or trying to understand the problem of the commentator gives the brand a better image.
At the same time, you can ask your current employees to write about their experience and give ratings to your brand on social media.
This will help improve your ratings and thereby counter the negativity.
But while you fix these issues online, it’s important to sit back and consider why an employee is posting negative comments.
If this happens regularly, then it’s really time to reflect on the organizational culture and make changes for the better.
Social HR - Ensuring employee engagement and development
The rise of social media has given greater ideas to organizations.
Many big organizations have come up with their own internal networking platforms to boost connectivity and employment among employees.
For example, InterGlobe Aviation (IndiGo) has its own portal, My 6E World, which offers employees opportunities to socialize with peers and access necessary documents like leave policies, etc.
Portals like these are a constructive platform for employees to vent their opinions in a controlled environment and at the same time make it easier for HR to understand the mindset and trends.
A few organizations are introducing learning courses for their organizations in their intra-networks while encouraging their employees to “compete” in a friendly way to boost employee engagement.
For example, you can give brownie points or perks for the highest scorers in the course. Some tech organizations are organizing hackathons to boost transparency in their appraisal or internal hiring processes.
Summing up, the presence of social media in recruitment or talent management initiatives cannot be denied.
Social media has penetrated deeply into the processes and is now bringing both opportunities and challenges to talent leaders everywhere.
As we said before, it’s more like a parallel ecosystem which thrives on data and information and needs equal attention, both from the employer and candidate.
People who understand its power, in the long run, will be clear winners of the Game of Talent.
The pros of using social Human Resource
Enhanced communication: Social HR tools facilitate immediate and open communication among employees, management, and HR teams. This transparency can lead to a more inclusive work environment and faster resolution of issues.
Improved employee engagement: By utilizing platforms that employees are familiar with and enjoy using, companies can boost engagement. Social HR can make it easier to recognize achievements, share successes, and foster a sense of community.
Efficient recruitment process: Social media and professional networks are powerful tools for identifying and attracting talent. Social HR practices enable organizations to reach a broader audience, showcase their culture, and engage with potential candidates in a more dynamic way.
Learning and development: Social HR facilitates continuous learning and development through easily accessible online training sessions, webinars, and shared resources. This encourages a culture of continuous improvement and knowledge sharing.
Real-time feedback and performance management: Social HR allows for more immediate feedback and recognition, moving away from the traditional annual review process. This can help employees adjust their performance in real-time and feel more valued.
The cons of using social HR
Privacy concerns: The use of social media and digital platforms raises concerns about employee privacy. There is a risk of sensitive personal or company information being shared inappropriately.
Over-reliance on technology: Heavy reliance on digital communication can lead to a reduction in face-to-face interactions, potentially harming workplace relationships and collaboration.
Potential for misuse: Without proper guidelines and monitoring, the use of social media at work can lead to non-work-related activities consuming work time or the spread of inappropriate content.
Security risks: Integrating social media into HR processes increases the risk of cybersecurity threats. Companies must invest in securing their networks and training employees on safe practices.
Cultural resistance: Implementing Social HR requires a shift in company culture, which may be met with resistance from employees who are accustomed to traditional methods of communication and management.
I Used AI to Build a "Simple Image Carousel" at VibeCodeArena. It Found 15+ Issues and Taught Me How to Fix Them.
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."
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:
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.
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.
✓ 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
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.
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.
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
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For Recruiters & Hiring Managers:
Accurately assess real-world development skills.
Gain deeper insights into candidate proficiency.
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Reduce candidate drop-off from technical friction.
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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.
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.
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