For various reasons, powerful companies in Japan home to amazingly advanced technology and manufacturing capabilities in several industries have failed to become as global as their peers overseas.

One of the challenges in achieving their globalization goals is their inadequate talent management strategy.

Like everywhere, Japanese HR professionals are trying to do justice to everything from recruiting to engaging to retaining talent in everchanging competitive markets to help organizations remain innovative.

What’s stopping businesses in Japan from moving forward

Traditional hiring practices

White-collar recruiting typically begins at the graduate level, where companies ready promising students from prestigious universities for “lifelong employment.”

In this “Shinotsu” culture, new graduates are recruited systematically every April based on their ambition, communication skills, and character.

Unfortunately, these fresh hires come with no specific job skills. According to a 2015 Robert Walters survey, nearly 50% of the employers had difficulty finding candidates with the required technical knowledge.

Firms then lack the flexibility to adapt to the changing requirements, and the training period to get them to work ready can be time-intensive.

Job positions are usually filled by internal candidates.

For recruiters, when there is a lack of adequate domestic talent, hiring foreign workers is not seen as an attractive option by most companies. (But this is changing!)

Rigid business practices

The Japanese “Tateshakai,” or vertical society, age, and seniority are sacrosanct. This can be demotivating for young, creative employees who also can’t get ahead based on skill alone.

Personal desires have no place in the traditional workplace where conformity, teamwork, and loyalty are all important attributes.

The egalitarian compensation companies and tenure-based promotion are not quite enough for the newer generation. Furthermore, social alienation and fear of failure prevent many young workers from becoming the entrepreneurs they would like to be.

For recruiters contacting potential employees can be difficult as “individual ambition” is frowned upon and the stigma of disloyalty is a huge barrier.

Most companies follow a job rotation/multi-tasking system that ends up producing generalists rather than specialists.

Dwindling and inadequate talent pool

The same survey showed that 72% of Japanese companies have been affected by talent shortages. Companies will suffer when looking for talent in emerging technologies such as artificial intelligence, self-driving technology, financial planning analysis, and web analytics.

The Hays 2016 Global Skills Index showed a significant talent mismatch in Japan (with a score of just 9.8) resulting in “wage pressure in high-skill occupations and talent shortage.”

A shrinking workforce, low birth rate, lack of creative confidence, and the inability to communicate fluently in English have contributed to a labor squeeze hampering economic development.

The current labor force in several sectors is quite ill-equipped to deal with the pressures of competition and globalization. In jobs which require employees to be bilingual, there are few candidates to choose from.

(This will an urgent need as Japan gets closer to the 2020 Tokyo Olympics and 2019 Rugby World Cup.)

Cultural impact

An intensely private people, the Japanese show very little engagement on social sites such as LinkedIn (less than 1% of the population is on it!).

However, sites such as Twitter, Facebook, and YouTube which offer anonymity have more success. Then again, for contacting them this becomes a challenge.

For recruiters, sourcing and attracting talent are significantly impacted by cultural factors. Apart from privacy and confidentiality issues, winning employees’ trust and convincing them to change jobs can be daunting.

Company culture favors recruitment of qualified candidates via referrals, and job advertisements typically have poor response rates in Japan.

For companies that don’t command strong brand reputation, attracting a candidate is not easy.

In Japan, changing jobs is an important decision and often candidates need time to speak with families before accepting an offer.

This can be frustrating for hiring professionals.

How the HR function can reassess its recruitment strategies

In the last decade, Japanese companies have been rigorously rethinking their hiring practices and revamping the traditional talent management system to deal with the changing economic environment.

To boost its innovative culture, social norms are now shifting to become more supportive of a vibrant startup ecosystem.

HR professionals understand that the values, both business and social, which were once dominant are no longer on the front burner.

Let’s look at some of the new recruitment approaches of talent acquisition professionals in Japan companies:

Embracing diversity

With its working population decreasing, Japan is embracing diversity and inclusion to meet the goal of sustainable economic growth. In light of Abe’s “womenomics,” HR professionals in firms such as Daiwa Securities Group Inc. are working to boost women involvement and mobilize the elderly population by modifying policies; examples include providing childcare and flexible work arrangements and initiating executive leadership training programs for women.

For example, Snack food maker Calbee Inc. had 20% women managers in 2014 compared to 5.9% in 2009. In a bid to improve diversity, the company also had the drive to recruit people who graduated five years ago.

There are more than two jobs for every job applicant in Tokyo.

The talent shortage is worse in smaller companies. However, rigid hiring practices are changing; HR is considering foreigners (and bots).

In 2017, Japan had over a million foreign workers. Japanese HR are also stepping up mid-career hiring efforts to fill positions.

Creating a global rotation system

Japanese firms are slowly moving toward global HR practices.

Companies such as Shiseido, Komatsu, Nissan, and Sony send top executives for an international stint to broaden their experience and skill set.

HR can ensure training of core employees to successfully function globally, be comfortable in cross-cultural settings, and be able to make sensible, management decisions independently.

For foreign ops, employees hired locally also need to be given career advancement and rotational opportunities and not just left to higher management, which is mostly Japanese.

Doing more than recruiting and internal placement

Traditional HR philosophies are not helping to manage a younger or diverse workforce.

HR can enforce policies where Japanese employees are required to communicate with foreign co-workers in English (as Mitsubishi Corp. does). HR should identify employees (regardless of their nationality) who can be pushed for global executive training and deployed overseas.

HR needs to create a compelling employer brand to attract the right talent. A Gallup survey shows that Japan has a really low (7%) percentage of engaged people.

HR professionals must address issues such as long working hours, low take-home pay, rigid corporate culture, seniority-based promotion, harassment, and unfair reward systems to reduce disengagement.

Long-term engagement will result in more actively engaged employees, lower attrition, and better productivity due to increased motivation.

The current business landscape in Japan

Japan's business landscape is marked by a blend of traditional practices and modern challenges. Despite being a global leader in technology and manufacturing, Japanese firms often struggle with globalization due to rigid hiring practices and a conservative business culture. The traditional "Shinotsu" recruitment system, focusing on hiring fresh graduates for lifelong employment, poses challenges in acquiring specialized skills quickly. Additionally, the vertical societal structure ("Tateshakai") impacts workplace dynamics, often stifling young, innovative talent.

Japan also faces demographic challenges like an aging population and low birth rates, which exacerbate talent shortages, especially in emerging technologies. While there's a gradual shift towards more inclusive and diverse hiring practices, including mid-career hiring and increased women's participation, the transition is slow. These factors collectively create a unique business environment in Japan, requiring innovative strategies to navigate successfully.

How HackerEarth can make your talent search easier in Japan?

HackerEarth offers solutions that can significantly ease the talent search in Japan's unique business environment. By leveraging its comprehensive suite of technical assessment and remote interviewing tools, HackerEarth can help Japanese companies overcome traditional recruitment barriers.

For instance, HackerEarth's platform can assist in identifying highly skilled candidates regardless of their educational background, which is particularly valuable in a market dominated by the "Shinotsu" system. Its skill-based assessments and coding tests allow companies to focus on practical skills rather than just academic pedigree. This approach is beneficial for identifying talent in emerging technologies, where there's a current shortage in Japan.

Furthermore, HackerEarth's platform supports diversity in hiring, enabling companies to tap into a broader talent pool, including mid-career professionals and underrepresented groups. This aligns well with the changing dynamics in Japan's workforce. Additionally, its user-friendly interface and efficient screening process make it easier for companies to adapt to global HR practices, facilitating a smoother transition into modern recruitment methodologies.

Conclusion

HR has to work with the business leaders to ensure the success of their initiatives—flexibility, skill-based recognition, self-development, challenging work opportunities, social projects, strong language skills, diversity, candidate experience, and individual enterprise.

Japan has gone from being a seller’s market to a buyer’s one. Potential recruits are asking more questions and are more focused on individual career advancement than before.

Source: Japan Today

“Recruitment today is about processes, technology, and people who represent your brand and messages on your behalf,” says Lanis Yarzab, VP Asia–Pacific operations, Pontoon Solutions.

HR need to actively build an attractive employee brand and showcase the company culture via social channels to ensure that a consistent, positive message is delivered.

Japanese companies are ripe for the automation of the recruitment processes such as screening and some unbiased, skill-specific hiring which can leave the HR to deal with more value-adding services.

Instead of developing talent (not buying) or leveraging internal talent through job rotation, HR needs to use tools for objective assessment and do some strategic workforce planning if organizations are to stay innovative.

Hire talent in your organization with HackerEarth Recruit. Be unbiased.

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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.

Hiring and recruitment challenges in Japan

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