This article was written with insights from James Deverick at Sage

The current state of workplace DE&I

When it comes to diversity, equity, and inclusion (DE&I), it’s crucial to understand that these are three different ideas. Of course, they are related, but developing an effective overall DEI strategy means understanding where they overlap and where they’re distinct.

Diversity: This relates to the representation of people in the workplace according to gender, ethnicity, age, physical ability range, neurodiversity, sexuality, etc.
Equity: This is about ensuring fair treatment for all. It involves arranging your policies and practices so they don’t inadvertently disadvantage anyone.
Inclusion: Making sure everyone is included and given an equal opportunity to contribute. This means actively considering any biases weighing against this and trying to overcome them.

One challenge that often crops up when aiming to implement a DEI strategy is the asymmetry of information. That’s to say that when data silos develop in your organization, it causes problems. A lack of access to business-critical knowledge can quickly become a barrier to inclusion.

Centralizing your data with an ERP software solution is an excellent way to resolve this. This kind of tool allows you to store all your information in a secure database that links up your systems. Instead of your various teams having no clue what other departments are doing, everyone has access to company-wide data that’s updated in real-time.

This makes it much easier for staff from every area of your business to make contributions, as they all have access to the same information. ERP tools thus level the playing field, which is exactly what you need if you want to focus on DEI.

Of course, this is just one of the ways tech can help boost your DEI efforts. So, it’s now time to dig a little deeper into the broad array of benefits to be gained.

The role of empathetic technology in DE&I

Before we go any further, let’s first spend a moment exploring what exactly is meant by “empathetic technology”. This term covers the use of any tech-based tools or systems designed to understand and respond to human emotions.

The kinds of things that count as empathetic technology include:

Wearables that use physical metrics to determine a person’s mood.
Customer service chatbots.
Platforms that use AI to make an easy-to-learn user interface.

When applied in the workplace, empathetic technology can play a significant role in achieving DE&I goals.

Some major benefits you can gain from implementing this kind of tech into your strategy include:

Benefits of implementing empathetic technology

Fosters inclusion and accessibility

Key to promoting inclusion and accessibility is recognizing that individuals’ different perspectives on life have value in and of themselves. It’s crucial to find ways for all employees to participate equally, regardless of their background.

Examples of empathetic technology that can support this include:

Voice recognition and natural language processing tools. These can make workplace communication more accessible for people who have disabilities.
Multilingual language support for your key platform user interface. This can help staff whose first language isn’t the one used for general workplace communication.
Personalized content and recommendations using machine learning techniques. Catering to individual needs and preferences using tailored content makes sure employees feel valued and included.

Mitigates bias and discrimination

No matter how hard you try to avoid it, the truth is that human beings are creatures of bias. Confirmation bias, logical fallacies, groupthink—we’ve all been there.

Let’s take recruitment. You’ve probably devoted a lot of time to developing an effective hiring process that acknowledges the importance of diversity in tech. After all, you know your business will thrive if it can attract top talent.

Maybe you already use cutting-edge techniques such as values-based recruitment (which you absolutely should, by the way). But could you be doing more to make the process more equitable?

Luckily, there’s help out. Empathetic tech can go a long way toward stripping out any remaining biases in your selection procedures. That’s because AI algorithms can be trained to detect and minimize biases in your process, helping you make fairer and more diverse hiring decisions.

Once your people have settled in, empathetic technology can help you in other ways too. For example, you can use it to develop training plans to reduce the risk of discrimination in the workplace.

One approach is to use augmented reality or virtual reality platforms. These can simulate real-life scenarios to raise awareness about unconscious biases and foster empathy among employees.

Enhances collaboration and cultural understanding

The right tech can also play a significant role in breaking down barriers and promoting effective communication among diverse teams.

Let’s use chatbots as an example. The standard of chatbot tech has undergone phenomenal improvements over the past few years. When most people hear the word “chatbot”, automated customer service agents probably spring to mind, but there are other ways you can use them in the workplace to promote DEI.

For instance, chatbots can be helpful as virtual trainers or guides to educate employees about different cultural norms and customs. They’re also a good option for delivering interactive modules or simulations to raise awareness about cultural diversity.

This kind of initiative helps your employees better grasp cultural differences. In the long run, this is one of the best employee retention strategies, since staff are much more likely to stay in a work environment where they feel valued and understood by their peers.

Enhances collaboration and cultural understanding

How to adopt empathetic technology in your DEI strategy

Whatever type of tech you plan to introduce into your organization, there are a few essential elements you first need to consider.

Different elemnts you should consider while adopting empathetic technology in D&I strategy

Set clear goals and objectives

Clarity is key. Define your DEI-related goals and objectives aligning with your organization’s overall strategy. Work out how empathetic technology can contribute to achieving these and develop a list of realistic KPIs.

Be specific about the metrics you want to hit, whether it’s fostering inclusion, mitigating bias, or enhancing cultural understanding. Make sure you set down in detail what the desired outcomes are and set deadlines for meeting these.

Secure support from organizational leaders to prioritize DEI

There’s no doubt that although many leaders talk about diversity in tech, they don’t all walk the walk. Unfortunately, without C-suite buy-in, any DEI strategy is doomed to fail.

So, how do you engage organizational leaders and secure their commitment to prioritizing DEI efforts? Answer: you show them evidence of its practical benefits.

Let’s consider something familiar to most businesses: the accounts team. In any organization, one of the most critical functions of this team is paying suppliers and other stakeholders accurately and on time.

DEI policies can address unconscious biases and ensure equity in accounts payable processes. These could include such day-to-day operations as invoice processing, payment approvals, and expense reimbursements.

You can use modern account payable software to keep track of transactions and automate your procedures. Doing this makes it easier to make sure that all employees and stakeholders receive fair treatment. This will bolster your company’s reputation and boost your DEI credentials.

Also, Read: D&I Lessons to Learn From Top D&I Global Organizations

Adopt a user-centered design approach

Involving employees and stakeholders in the design and development process is also a good idea. This means conducting user research to understand the needs, preferences, and pain points your tech will address.

Some people are reluctant to embrace wearable tech, for example. It’s vital to be aware that previous work experiences may have left some employees mistrustful of senior management’s motives for introducing biometric tech into the workplace.

So, it’s crucial to incorporate their feedback and perspectives. This way, the technology you invest in will be more likely to meet employee expectations and be inclusive by design.

Provide comprehensive employee training and education programs

You can never have too much in the way of upskilling and reskilling in the workplace. Offer comprehensive training programs to educate employees on the benefits and ethical considerations of using empathetic technology.

Specifically, teach them how to use this tech to enhance DEI efforts, address biases, and promote inclusive practices. Encourage open dialogue and create spaces where employees can share their honest insights.

Prioritize data privacy and security considerations

Data privacy and security are paramount when implementing empathetic technology. Ensure compliance with relevant regulations and establish watertight procedures for protecting sensitive information by taking into account the utilization of top proxies to enhance security.

Keep a two-way conversation going at all times surrounding data collection, storage, and usage. Always remember to obtain explicit consent from users, as well as regularly review and update privacy policies to nip any problems in the bud before they cause real headaches.

Ensure technology can accommodate future growth

Your empathetic technology solutions must also be scalable and adaptable to evolving DEI requirements. Regularly evaluate the effectiveness of your tech and make necessary adjustments as your organizational goals develop.

New possibilities with empathetic technology

We’ve certainly come a long way from where we started. Over the years, DE&I policies have adapted as businesses everywhere have begun to understand how crucial it is to achieve diversity in tech.

Although some challenges remain, there’s no doubt that the rise of empathetic technology is opening up new possibilities for solving them. If you’re looking to breathe new life into your current DEI strategy, it could be time to get some digital help.

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.

Empathetic Technology: The Future of Workplace DE&I?

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