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The Unvarnished Truth of being a Woman in Tech

The Unvarnished Truth of being a Woman in Tech

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Arbaz Nadeem
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August 14, 2020
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3 min read
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In our fifth episode of Breaking404, we caught up with Monica Bajaj, Senior Director of Engineering, Workday to hear out the different biases that exist in tech roles across organizations and how difficult it can get for a woman to reach a senior position, especially in tech. We also talked about the best recruiting practices that Engineering Leaders should follow in order to hire the best tech talent without any biases.

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Arbaz: Hello everyone and welcome to the 5th episode of Breaking 404 by HackerEarth, a podcast for all engineering enthusiasts, professionals, and leaders to learn from top influencers in the engineering and technology industry. This is your host Arbaz and today I have with me Monica Bajaj, the Senior Director of Engineering at Workday, an American on‑demand financial management and human capital management software vendor. She is also a Board Member of Women in Localization, a leading professional organization with a mission to create a strong place for women to develop their careers in localization and provide mentorship. Welcome, Monica! We are delighted to have you as a guest for our podcast. For our audience to know you better, let’s start off with a quick introduction about yourself and how your professional journey has been?

Monica: Definitely. I am originally from India from a city called Indore (central part of India). I did my high school and under-graduation from Indore. I came to the US almost 20 years back for work and settled here. My professional journey has been very interesting. Right after my undergrad in CS, I started my career as an Assistant professor teaching Computer science Teaching has always been close to my heart since it creates a platform of learning without any expectations. Later I did my Masters in CS at IIT Mumbai which was indeed a turning point in my career. I decided to join the tech industry in India, joined Wipro, and came to the US on an assignment. I was one of the early on developers at WellsFargo when they were going through the transformation of being an Online banking application. I started my career as a full stack developer and stayed as a developer for almost 10 plus years. In 2005 I got an opportunity at a Startup to transition my career into management. I had no idea about people management but decided to take this challenge. As I embarked on this new challenge, I realized that people management and building teams are something that I truly enjoy. I never looked back. I have been fortunate that as I moved from one industry to another, I was able to develop my engineering management experiences and align with the business needs. I have had great opportunities working for startups, mid-size, and giant tech companies such as Cisco, NetApp, Perforce, Ultimate software mostly in the enterprise space. I recently joined Workday as a Senior Director of Engineering, building their Community Platform.

Arbaz: What was the first programming language you started to code in and was the code to print “Hello World”?

Monica: My first programming language was BASIC. I never had exposure to computers until I went to college and started my undergrad in CS. We worked on BBC Microcomputers saving our programs on Floppy disks. Resources were limited in India and yes it sounds pretty old but it definitely shows the journey of innovation that has happened in just last 20 years

Arbaz: While we were looking out for guests for this podcast, out of the more than 100 potential engineering leaders that we found, just 5-10% were females. Do you think that there still exists an inequality/bias in terms of gender especially in tech roles? Also, have you ever experienced this yourself and how difficult/challenging is it to reach a senior position for women in tech?

Monica: Definitely Gender bias in the tech industry is very prevalent. If we just look at the tech industry in the mid-1980s, 37% of CS majors were women. You would think that things must have gotten better as we advanced in this century. In fact,it has dipped to 18%. Today women make up only 20% of engineering graduates. Only 26% of computing jobs are held by women and have been steadily declining. The turnover rate is more than twice as high for women than it is for men in the tech industry 41% vs 17%. 56% of women are leaving their employers mid-career ( 22% get self-employed, 20% leave the workforce, and 10% work with some startups). Only 5% of leadership positions in the tech sector are held by women; they make up only 9% of partners at the top 100 venture capital firms. On top of this, if you are a woman of color, the challenges get even harder when it comes to growth negotiations. These challenges increase as you embark into key Senior leadership roles: Principal Engineers, Architect, Directors, and Senior Directors, VPs, and above. Yes, I have personally experienced this in my career a few times. Once I was being told by my senior leader that Indian women are not meant for leadership due to cultural bias. It was heartbreaking and at the same time, it made me very angry. I did not hold back and did state that things have changed so much. This did cost me my job and I was asked to move to another group. Another story I have is where I had to deal with Cultural Bias and lack of understanding of being a mom. I was being told by my boss,” why do you need to drop kids to school and be late to work. I have pets and I leave them and they figure it out. “ I was shocked. Rather than going to HR, I resigned and moved on since I knew no action would be taken. Sometimes such experiences can lead to folks leaving industry/companies. There is a bias and women many times downplay their technical credentials. On the other hand, men do the reverse. Studies have proven that when it comes to applying for a job men apply when they meet 60% of the qualifications and women continue to have second thought even when they are meeting 100% of the qualifications.

Arbaz: These are really motivational stories and shocking at the same time. It’s really great to hear how you fought all of them. These numbers are really horrifying numbers. We often discuss how women empowerment has been a movement off late. Just a follow-up to that, have you seen any particular changes that companies are taking to bring these differences down?

Arbaz: You’ve worked with top companies including Cisco, NetApp, Perforce, Ultimate Software and now you are with Workday. What is the biggest technical or product challenge you have experienced? How did you overcome it?

Monica: The biggest technical challenge any organization faces today is bringing in Digital transformation. Digital transformation is imperative for all businesses and lets us not delude ourselves that the tech industry does not need it., It applies from the small to medium to enterprise and definition changes similar to the definition of the following Agile development process. Digital transformation is hard but if you have the right strategy and clear vision it can do miracles. The key focus has to be Customer experience, Operational Agility, Culture and Leadership, Workforce Enablement, and Digital Technology Integration. As an engineering leader, I had an opportunity to be a part of this journey in my recent role. One of the goals while building a product was to move from an application-centric view to a services-based view. While building this new product on a Microservices based architecture, it was also important to convert a monolith module to a microservice and integrate with other Microservices in the new architecture. It has a significant benefit because the services are autonomous, specialized, can be updated, deployed, and scaled to meet the demand for specific functions of an application. It definitely required organizational transformation around convincing, and prioritization clashes with other initiatives. On the technology and process side, we uncovered a few challenges around integration, deployment, and migration of these services to Kubernetes. Automation was a must requirement to go with. I had the state of art DevOps team who was an integral part of the development process right from the design phase. This really helped us in making sure that we have the strategy around deploying, monitoring, and alerting of these services.

In the current situation at Workday, I have an opportunity to stand a new platform for an existing product called Workday Community. Choices are Buy Vs Build, keeping an equal focus on the existing product and the future development, Defining the game changers and enriched user experience for our customers and most important keeping in mind the sentiments of the current team to come along in this journey of transformation.

Arbaz: Two things that we most often see engineering leaders focused on are: Technical Debt and High Quality of Code. Keeping this in mind, how do you maintain a balance of technical stability (minimize technical debt) while still delivering quality code at a high velocity?

Monica: As smart financial debt can help us reach our life goals faster, not all technical debt is bad. The key thing is managing it well while delivering at a high pace to meet the customer needs and balancing with emerging opportunities. There are three kinds of Tech debt:

Deliberate Tech debt ( where we incur tech debt to reduce time to market)

Accidental Tech debt: More of a design tech debt. It is important to thoroughly consider nuances around design else it can lead to rework. Refactoring of the system can help

Bit rot: This is where the functionality just ages over years due to incremental changes, workarounds. Most of the organizations face this kind of tech debt.

In my mind, the evaluation of tech debt and its consequences is more of an art than a science.

In order to maintain the overall stability, I make sure that I address 20% of my stories focused on Tech debt in every sprint planning. This again entails negotiations, prioritization against new feature development. If we start seeing that the team is losing velocity it is a good indicator that tech debt may exist. Test coverage, code smells, code coverage helps in uncovering the gaps around design, and functionality. Developer productivity is important to keep in mind which includes best engineering practices, managing tech debt well, creating reusable components, and building an architecture that allows for decoupling if needed.

Arbaz: That’s really a great approach. At the end of the day, it’s important to keep the balance correct. Just deviating a little bit from our technical talks and getting to know Monica, the person, a little more. What is your favorite leisure-time activity and how do you make sure that you keep that hobby in-tact and not let it die under your workload?

Monica: Gardening and Outdoor activity such as hiking and road trips. I believe that if you prioritize it and if it means something for you, it will happen irrespective of your workload. In fact more than a hobby, I continue to learn leadership lessons from my garden. Organizations are like gardens and they need a lot of love and care similar to growing plants in your garden.

Arbaz: Recruiting and engineering, while we are partners, we operate differently. How do you work together? How do you align recruiters and hiring managers to achieve the overall objective of hiring a talented developer? From your perspective when you’re on that table with your recruiter, are you seeing alignment, or are you seeing discordance and how are you handling that?

Monica: Hiring the right people should be the highest priority for any business. I have a great partnership with our recruiting teams. I strongly believe that the onus is on the hiring manager since he/she knows the best what they need from the candidate. In order to make sure that the recruiter has a good understanding of what to look for I work with our recruiting team to define the traits, technical skills, and the overall recruiting process.( Phone screen, technical challenge, panel interviews). It is very important that the messaging around the role, team and company culture is consistent during all the conversations that recruiter and the hiring manager have with the candidate.

Arbaz: There is a lot of debate on the coding interviews right now having algorithm problem-solving skills, and you don’t necessarily use data structures in your real-world coding. But companies globally do emphasize on having questions around Data structures and Algo in the assessment. Do you think it’s a good approach? How do you reconcile the two and do you think the problem-solving questions give you a good idea of their future performance?

Monica: I think Data structures and Algorithms are fundamentals or core plumbing. While interviewing, I want the candidate ( for a developer or QA role) to go through a problem and see if they can apply the core principles of software engineering such as algorithms, testing, debugging logging, scale, performance. As a hiring manager, I like to see how an individual is able to think out of the box and be creative. It also helps individuals agility around picking new technologies and come up with the best approach to solve the problem. In fact, the candidate should be able to speak to their resume, hence better storytelling. Having the candidate go through live examples in their resume speaks for collaboration, cultural fit, observance, team building.

Arbaz: What is the most challenging part of any technical assessment and interview? If there is anything that you would like to change in the assessment and interview process, what would it be?

Monica: The most challenging part of technical assessment is to ensure that the entire panel is of the same understanding around the expectations and level of any given role. As a hiring manager, it is our job to ensure that. In terms of bringing a change in this interview process: I am not a big fan of the process where rather than focusing on the job role and the candidate’s experience, the companies start asking these random questions such as “ How will you deploy software on Mars or how will you move Mount Fuji ?” Companies do not realize that the candidate is also interviewing them so it is fair game on both sides. You always want to hire smarter people than you so that you can bring in new talent and ideas rather than converting them or making them fit in your model of thinking. I consider this as “ hurting their creativity and hence diminishing the impact they can make if they get hired”. If you approach a candidate, you need to value and embrace their experience and see how it aligns to fit your business and organizational needs.

I want to bring in a diversity of thought and creativity. I do not want candidates to be pre-programmed to speak the buzzwords that the company is looking for or the structure that they publish.

Arbaz: It’s wonderful how you shed light on how important it is to foster learning and growth for talent and the candidate is also assessing the company. Now as the Senior Director of Engineering at Workday, do you still code, and if not do you sort of miss coding? We would love to know how the role changes because a lot of times developers have this thing of – Do I need to go in the path of a developer, a senior developer, a principal engineer instead of like a chief architect, or do you want to go down the developer, engineering manager, director, and CTO journey. And sometimes you can end up being a CTO or VP of engineering from multiple paths. So how did you choose to go which path you wanted to take?

Monica: No, I do not code and neither do I miss it. ( Most of the companies offer two tracks in any given role. If you love to be close to only technical aspects ( coding, architecture, design ) you can grow as an Individual contributor such as architect, principal engineer, and be on a technical track. However, if you are more inclined towards people management, mentor, and be able to invest in people, hire the best talent, you can be on the management track. Many of us get lost when we have to make a call at this turning point of being a manager and not doing hands-on every day. It is hard to let go of things that you are comfortable with. I was a developer by career for more than a decade and then I got my first break into management ( due to my dev and tech skills). Soon I realized that I enjoyed people management and never looked back. One important thing I would like to share is keeping a fine balance between being hands-on and being a manager. Managing an organization cannot be a part-time job. You can easily fall into the trap of being hands-on since you are comfortable with it. You may think that you are contributing but in fact, you might be hurting them by taking their space and creativity and also ignoring your first priority of investing in your people.

Arbaz: Which software framework/tool do you admire the most and consider as a gift from God?

Monica: IaaS: Infrastructure as a code. Modern Marvel of Cloud engineering where you don’t have to worry about maintaining the infrastructure, worry about the scale and other services such as monitoring, security, logging, disaster recovery, load balancing, backup, etc. It allows a greater level of automation and orchestration also speeds up the overall delivery process.

Arbaz: Considering the current scenario around the COVID-19 outbreak where companies have asked their employees to work remotely, what do you think is the biggest problem/challenge with managing remote engineering teams? What do you think is the best way to keep a team of engineers motivated?

Monica: With COVID, the boundary between homework and work from home has been blurred. The working hours have become much longer due to flexibility and hence the balance between family and work does get impacted. More importantly, since everyone is at home, it can get harder for folks to focus on their work more so if they have space limitations or little kids. Communication with the entire team has also become all virtual. I joined Workday 5 weeks back and I was virtually onboarded and now I am learning and building relationships with my team via a virtual platform. I agree that nothing beats in-person engagements. If you look at the pros, it has given an opportunity for people to save their commute from 2-3 hours everyday to none which is indeed priceless. For many people, it has improved the overall quality of life but given us a pace where we can stop, admire, and focus things around us. It has allowed people to rejuvenate themselves rather than chasing the rat race of life.

When it comes to your teams, stay in touch, be transparent, Value them, and continue to express gratitude.

Arbaz: If not engineering, what alternate profession would you have seen yourself excel in?

Monica: I would be a Master Gardener. My parents are avid gardeners so I would say that I inherited some of those traits from them. I love outdoors, I need quiet time where I can just sync in my Garden. I feel it is a way for me to communicate with Mother Nature. You are constantly growing and learning about these plants. I feel the same way in my career where I continue to learn and grow every day.

Arbaz: What would be your 1 tip for all Engineering Managers, VPs, and Directors for being the best at what they do?

Monica: Try to hire people who are not clones of yourself.

Arbaz: It was a pleasure having you today as part of this episode, I really appreciate you taking your time. It was informative and insightful, and I definitely enjoyed listening. I hope our listeners also have a great time listening to you. Thank you. So, this brings us to the end of today’s episode of Breaking 404. Stay tuned for more such awesome enlightening episodes. Don’t forget to subscribe to our channel ‘Breaking 404 by HackerEarth’ on Itunes, Spotify, Google Podcasts, SoundCloud and TuneIn. This is Arbaz, your host signing off until next time. Thank you so much, everyone!

About Monica Bajaj

Monica Bajaj is an engineering leader with a wide variety of experience around building high performing globally distributed Engineering teams aligning with product delivery and customer satisfaction. Her prime focus has always been around developer productivity and enriched experience for customers. Monica is currently Senior Director of Engineering at Workday where she is responsible to build a Community 2.0 platform along with other partner teams. Prior to Workday, she worked at various Tech giants such as Cisco, NetApp, and Ultimate Software. She also serves as a Board member at WomenInLocalization, a global organization focused on Women mentorship and localization activities. She is a featured mentor on Plato and Everwise mentorship platforms.

Monica holds a CS undergrad from Indore and grad from IIT Mumbai in India.

Finding outdoor activities keeps her refreshed. When she is not working, she is either gardening, hiking, or mentoring. She can be reached on:

Twitter: @mbajaj9

LinkedIn: https://www.linkedin.com/in/mobajaj/

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August 14, 2020
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How I used VibeCode Arena platform to build code using AI and leant how to improve it

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:

  • 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.

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

The Mobile Dev Hiring Landscape Just Changed

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:

Article content

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.

Article content

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.

Vibe Coding: Shaping the Future of Software

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

Vibe Coding Difference

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.​

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