This is a guest post by Harshala Chavan, founder of Merrative.

A stronghold of technical concepts is necessary to write about any specific technology. But writing and coding are distinct skill sets, and hence, few experienced developers indulge in professional writing.

At Merrative, it took us multiple paid trials, hours of recruitment work, and a loss of USD 1000+ with unsatisfactory work to find our first 15 technical writers. In response to this, we designed a system to hire technical writers for our marketplace.

Read more to know how we scaled our technical writer talent pool from 15 to 150 and tips for hiring a technical writer.

Who is a technical writer?

A technical writer understands the underlying technology of a product to write technical documentation, blogs, whitepapers, or other communication formats.

At Merrative, we believe that talented tech writers should have the necessary expertise in the technical subject to understand how a product or feature works and write about it in simple, clear, and concise language. A technical writer is usually employed across companies in industries such as Technology, Healthcare, Finance, etc.

Job description of a technical writer

What sets technical writers apart from other professional writers?

Deep knowledge and understanding of technology. These skills are crucial to delivering solid technical documentation. Technical writers usually write for CTOs, developers, and even non-technical customers. Having such a varied audience means technical writers have to constantly tune their tone, information depth, and jargon usage as per the audience.

Also read: 5-Step Guide To Gender-Fluid Tech Job Descriptions (+Free Checklist)

Key responsibilities of a technical writer

Ensure your technical writer candidate can do the following:

Research the product and grasp concepts of the underlying technology used to make the product
Understand and follow technical content guidelines defined by the brand to draft technical documentation
Work with team members across Product and Marketing to draft appropriate technical content
Work with the Design team to create relevant diagrams, charts, code snippets, etc.
Take feedback from team members, customers, and beta testers to align the content with their requirements.

Write great job descriptions to hire talented technical writers - Free Checklist

Key performance indicators (KPIs) for a technical writer

Use the following KPIs in the job description:

1. Technical accuracy: How well does your technical writer know your product? Are they adding correct code snippets to the content when needed? Define KPIs to measure how accurately the writer is presenting your product – a useful way is to design a technology or product onboarding for new joiners. Managers can also conduct regular tests or workshops about the product to align technical accuracy.

2. Readability: Technical content tends to get higher grades in online editors like the Hemingway app. This can be very misleading. Define an acceptable readability score for the hired technical writer or check how their published content performs. A great way to check the usability of written content is by asking for feedback. For example, Google takes feedback on its product support content by asking the reader ‘Was this article helpful’ with Yes/No options. This helps the support team understand the usefulness of the content published.

3. Adherence to content guidelines: Define non-negotiable key content guidelines that the technical writers should follow

4. Collaboration: Define KPIs that include getting feedback from customers, other teams, and/or testers as part of the review process.

Average expected pay for technical writers:

According to Salary.com, the typical salary for a full-time technical writer ranges from USD 54,945 to USD 68,512 in the USA. For a freelance writer, the compensation for a technical blog post ranges between USD 350 to USD 1000+ depending on the content format and expertise.

When should a technology brand hire a technical writer?

A technology business requires a technical writer to cover the following content formats:

User manuals: Step-by-step instructions about using the product
Whitepapers: Authoritative reports to educate potential customers about your product use case or industry
Developer documentation: Create guides and help tutorials for developers to build using your product’s ecosystem
Newsletters: Email periodicals about your product, new features, and other information critical for engaging potential customers
Technical blogs: Search Engine Optimized technical blog posts as per the company’s content marketing strategy.

Hiring a freelance technical writer v/s an in-house technical writer

Choosing between freelance and in-house technical writers depends on the number of content projects and expertise required.

For example, if your company plans to publish only three to five whitepapers a year, it doesn’t make sense to hire a full-time employee. On the other hand, if your publishing strategy includes multiple technical content formats, a freelancer may prove to be expensive.

What makes a good technical writer?

Apart from the non-negotiable exceptional writing skills, check for these top 3 must-have hard skills in your technical writer:

Technical research skills: A good writer must thoroughly study your product, technology, and user experience to craft well-researched content.
Writing skills: Technical content can be very dry and hard to understand. A good writer, usingspeech to text technology, not only writes grammatically correct content but also knows how to make really hard concepts easy to grasp for laymen, without sounding condescending.
Visual communication: A technical writer may have to present instructions using diagrams, charts, or infographics. For this, they may have to work with a designer or need adequate visual communication skills to showcase technical diagrams. It is important to know how and when to use visual communication in your content to create impact, as well as resonate with the audience.

Check for these top 3 must-have soft skills in your technical writer:

Empathy: A technical writer simplifies technology for common users. Empathy is key to ensuring they write what the reader can easily understand and implement.
Attention to detail: Without attention to detail, a writer may publish wrong instructions or help instructions that hurt the brand’s credibility.
Adaptability: Technology is constantly changing and a technical writer should know how to adapt and learn to keep up.

How to hire a technical writer? – the 5-step hiring process

At Merrative, we are a publishing talent marketplace that helps brands and publishers with thought leadership content. Here’s how we designed a process to hire a technical writer to save recruitment costs:

Step 1: Set the right expectations

Paid trials are expensive in the technical writing field. Hence, setting budgets and processes is key to ensuring you do not waste money in doing paid trials with unqualified technical writers.

1. Write technical documentation and create content guidelines

Creating content guidelines specifically for your technical content acts like a checklist for gauging how well the writer fits your requirements.

2. Create content brief templates for various content formats and topic segments that need to be covered

Having templates handy for the required content formats helps quickly assign paid trial tasks to selected writers. Save topic clusters for paid trials to test writers based on their experience.

3. Prepare agreements and fix a budget

Ensure that you sign agreements to protect your company data, product designs, and other key internal information as writing assignments may require sharing them. Have a budget in place to test technical writers accordingly. In our experience at Merrative, it is better to hire experienced writers who may charge more but produce quality output.

Step 2: Set up a ‘Write For Us’ program

‘Write for Us’ is one of the key ways in which writers and agencies approach companies they would like to work with for at least guest posting opportunities. This is a great way to collaborate with writers who are genuinely interested in contributing to your content library. It also reduces your recruitment efforts. Epilogue’s (Merrative’s in-house publication) ‘Write for Us’ page generated 100+ applications within 3 weeks of its launch.

Step 3: Create a technical writer interview checklist

Create a checklist of questions to ask potential technical writer candidates. Questions about company culture fit, professional experience, and technical expertise is a great mix.

Also read: 8 Unconsciously Sexist Interview Questions You’re Asking Your Female Candidates

Step 4: Set up a technical writer paid assessment workflow

At Merrative, a writer is selected based on our internal selection guidelines of educational qualification, industry experience, and professional writing experience. Then, we gauge the writing style and technical depth of the relevant samples shared by the writer as per our content guidelines.

We approach writers who meet our qualification guidelines for a paid trial assessment post negotiating budgets. On submission of the writing sample, we check how much they have adhered to our content guidelines and then proceed with more projects.

Good execution of Step–1 is crucial to ensure smooth trials in Step–3.

Step–5: Onboard the hired technical writer into your content production system

Like any new recruit, the newly hired writer, too, has to adjust to your company’s workplace culture. Having a good onboarding process ensures they are trained in using the product and tools used in your organization. Set up a meet and greet with the existing team for smooth collaboration.

Hiring rubric used by Merrative to filter the top 5% of technical writers

Here’s a hiring rubric used by Merrative to hire technical writers:

How to hire a technical writer - A Rubric

If you would like to understand more about our technical writer hiring process, feel free to email hello@merrative.com to schedule a chat. You can also download this hiring rubric and more resources from our free writing resources section.

5 tips for hiring the best technical writer

Here are 5 best practices used at Merrative that might help you streamline your technical writing hiring process:

Stress on experience: At Merrative, we have experienced how writers who had graduated with a software degree, have worked in the software industry, or wrote about software as a hobby produced the best content compared to other candidates.
Don’t take unprofessional behavior lightly: One of our writers in the talent pool submitted content with 3% plagiarism and defended it by saying how ‘3% is alright’. Eventually, we observed how the writer indeed slacked off multiple times in terms of adhering to defined content quality standards. Seemingly small but unprofessional behavior can add up as you work together and eventually become a problem.
Review writing samples or portfolio: it is possible to understand a writer’s skill by gauging how they have structured their portfolio. For example, a diverse portfolio suggests a lack of subject matter expertise. Ask for relevant samples on topics your brand aims to cover and check the depth of writing. Carefully analyzing portfolios helps avoid unnecessary paid writing tests.
Do not use job templates: using job description templates may dilute your branding and may not be enough to attract the right applicants due to being ‘general’. Carefully research what you require in your candidate and state that in your job description, or consider leveraging a writing assistant for personalized and effective job postings.
Use screening tools: it is common to receive thousands of technical writer applications. There are many dedicated hiring tools like LinkedIn, Upwork, Workello, etc that help with test assignments and recruitment.

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.

A Practical Guide To Hire A Technical Writer For Your Tech Team

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