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Building Future-Ready Tech Teams

Building Future-Ready Tech Teams

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Ruehie Jaiya Karri
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June 9, 2021
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8 min read
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For the third year in a row, there is a massive increase in the skills gap across industries, with nearly 80% of organizations saying that their teams lack the necessary skills; as stated by the Global Knowledge IT Skills and Salary report. The ever-increasing skills gap is the bane of IT leaders who aim to build future-ready tech teams. The age of digital disruption dictates the requirements of the current and future workforce and the existing workforce is unprepared to address the emerging trends and developments of the future.

Hiring their way out of this problem is not an option, say recruiters. There is a dire need for upskilled personnel and every organization needs to identify and provide ample opportunities for its employees to grow and upskill themselves.

Flexible, scalable, and innovative teams are the future of tech. The sooner companies throw traditional practices out of the window the better. Future-proofing teams dictates the success of any organization and ensures it stays relevant, in 2021.

Digital transformation and innovation are happening at such a rapid pace. Companies are feeling the pressure too, which is why they must be building future-proofed teams and ever-ready workforces. Ensuring your team can scale with the changing times, will ensure your teams are agile, scalable, and ready for any market or industry demands. The onus is on business leaders to give their teams the skills they need to keep up and stay ahead. Future-proofing is a team-sport, meaning everyone can, and should, play an active role in learning, growing, and innovating. From taking online courses to attending virtual events like hackathons and conferences, there is an abundance of opportunities available to ensure companies always continue to stay ahead of the curve.
– Brian H. Hough, Founder of Airblock Technologies

Traits of a future-ready workforce

  • A finely balanced workforce consisting of both people and technology.
  • Tech teams that are characterized by continual learning integrated with their flow of work.
  • Future-ready tech teams have a repertoire of skills that will come into use 5-10 years from now.

The ability of organizations to address the skills-gap challenge by assessing the current lack of skills, and predicting skills needed for the future will help them in future-proofing their tech teams. Although it’s hard to accurately predict future demands; due to the fast-paced advancements in technology, there is a set of skills that will never go out of style.

Soft skills. They are overwhelmingly hard to find and the pressing need for these soft skills is tied to employees’ abilities to learn and adapt to change. This agility is becoming increasingly important – perhaps even more than functional or technical skills.

“Communication is the key in every company. It is even more important in the remote company of the future. Remote companies need 10x the process early on, and it pays out later though. A very underrated skill is communicating your progress and status with the rest of your teammates and keeping your project management system tight.”
– Radoslav Stankov, Head of Engineering at Product Hunt

Characteristics of a future-ready tech team

Building the future requires more than just technology; It requires a combination of agility, insight and flexibility. Such teams are open to new ideas, willing to abandon outdated practices, and adapt to emerging technologies.

From AI specialists to full-stack developers, having a diverse talent pool ensures the team can tackle a variety of challenges.

With an emphasis on upskilling and reskilling, these teams are always on the lookout for the next big thing in tech.

Siloed methods are a thing of the past. Future-ready teams prioritize collaboration. Rather than react, these teams anticipate challenges and work on solutions before issues escalate.

The importance of soft skills in building a future-ready tech team

Soft skills are personal attributes that enable someone to interact effectively and harmoniously with other people. They are often referred to as interpersonal skills or people skills. Soft skills are just as important as hard skills, or technical skills, in the workplace. In fact, many employers believe that soft skills are even more important than hard skills, especially for tech teams.

There are many reasons why soft skills are so important for tech teams. First, tech teams need to be able to collaborate effectively to solve complex problems. This requires strong communication, teamwork, and problem-solving skills. Second, tech teams need to be able to adapt to change quickly. The technology landscape is constantly evolving, so tech teams need to be able to learn new things and adapt to new situations. This requires strong adaptability, resilience, and creativity skills.

Here are some specific examples of soft skills that are important for tech teams:

  • Communication: Tech teams need to be able to communicate effectively with each other, as well as with other stakeholders, such as product managers, designers, and customers. This includes being able to clearly articulate ideas. That could be verbally and in writing, or utilizing relevant technology like call center software as appropriate.
  • Teamwork: Tech teams need to be able to work together effectively to achieve common goals. This requires being able to collaborate, share ideas, and give and receive feedback.
  • Problem-solving: Tech teams need to be able to identify and solve problems effectively. This requires being able to think critically, creatively, and methodically.
  • Adaptability: Tech teams need to be able to adapt to change quickly. This requires being able to learn new things, unlearn old things, and adapt to new situations.
  • Resilience: Tech teams need to be able to bounce back from setbacks and failures. This requires being able to persevere, learn from mistakes, and stay motivated.
  • Creativity: Tech teams need to be able to think creatively to solve problems and develop new solutions. This requires being able to come up with new ideas and think outside the box.

Employers are increasingly looking for tech candidates with strong soft skills. In fact, a study by LinkedIn found that 92% of recruiters believe that soft skills are just as important as hard skills, if not more important.

Here are some tips for building a future-ready tech team with strong soft skills:

  • Hire for soft skills as well as hard skills. When interviewing candidates, be sure to assess their soft skills as well as their hard skills. Look for candidates who are good communicators, team players, and problem solvers.
  • Provide training and development opportunities for soft skills. Just like hard skills, soft skills can be learned and developed. Offer your team members training and development opportunities in areas such as communication, teamwork, and problem-solving.
  • Create a culture that values soft skills. Make sure that your team members know that soft skills are valued in your organization. This could involve recognizing and rewarding team members for demonstrating strong soft skills, or incorporating soft skills development into your performance review process.

By investing in soft skills, you can build a future-ready tech team that is well-equipped to succeed in the rapidly changing technology landscape.

How can you identify and address the challenges of building future-ready tech teams?

Future-proofing activities have led companies to ideate newer strategies and morph their team structures to meet real-time disruptions and demands. Three important areas that need attention are:

The organizational skills gap

The skills gap refers to the mismatch between the skills that employers are looking for in employees, and the skills those employees possess. Persistent skills shortage affects the business objectives of a company, and a stop-gap solution is not the answer. It is difficult to pinpoint any one reason for this. However, a few well-informed guesses would include a lack of qualified applicants and a lack of learning investment in existing employees. Acknowledging that tech teams are falling behind, and identifying the wide skills gap across the organization is the first step.

Learning and development programs

Nearly 39% of decision-makers attributed skills gaps to a lack of training investment two years ago. In 2021, 74% of organizations say reskilling their workforce is crucial to their success over the next 12–18 months. Organizations need to step up and provide suitable learning and development opportunities for their employees, which have the potential to transform market volatility into growth. Forward-thinking companies also encourage and enable employees to apply their skills and interests in different ways.

L&D programs are the need of the hour when it comes to closing the skills chasm. Internal upskilling of teams is an effective way to future-proof your workforce and provide an improved employee experience and higher employee retention.

Check out HackerEarth’s Learning and Development platform here.

Leveraging technology

This one is a no-brainer. Technology, being one of the major reasons for the skills gap challenge, is also key to bridging it, and enabling rapid up- and re-skilling. Equipping employees with the right digital tools to work with today, and encouraging the use of the newest technologies and tools to keep up with the trends of tomorrow must be a part of any project plan to build future-ready tech teams. For example, using the best QR code generator allows teams to easily share information, track progress, and distribute training materials, making it easier for teams to access resources and stay aligned with project goals.

No crystal ball can predict what the future of work is going to look like. What should we do?
1. Join the community – Facebook Groups, conferences, webinars, etc. – Don’t just watch/read, contribute! It’ll force you to branch out and learn new things to create the content.
2. Demo 2 products every month – this will keep you on the front end of the technology evolution. Even if you have no budget and don’t need anything, always be exploring what’s out there.
3. A/B test and iterate – if things are going “well” – give yourself a pat on the back, and then iterate to find an even better way to do it – and continue doing this, forever. You will NEVER find “the right” way to do things, only better ways. And there are ALWAYS better ways.”
– Mike Cohen, Founder of Wayne Technologies

Future trends: Implementing remote and hybrid work models

The COVID pandemic has left us with some truths. We know that with remote work becoming the norm, decentralized teams spread across time zones will become even more common.

With location no longer a barrier, companies will tap into global talent, bringing diverse perspectives and skills.

Such teams will need certain processes in place to ensure business continuity. For instance:

  • Tools like Slack or Microsoft Teams can keep everyone connected, ensuring seamless communication.
  • Virtual stand-ups or weekly meetings can help teams stay aligned with company goals.
  • Instead of micromanaging, leaders should trust their team, focusing on output rather than hours spent.
  • Ensuring that remote team members don’t feel left out should be a priority for HR managers. Virtual team-building activities can foster camaraderie.
  • Understand that everyone has different peak productivity times and home situations can also go a long way in bettering the work-life balance.

Future tech teams might also regularly collaborate with AI tools or even AI “team members” to enhance productivity. Instead of rigid roles, team members might switch hats based on the project’s demands, promoting holistic skill development.

There is no doubt that companies will need to shift their current hiring practices and adopt remote and virtual-friendly processes to hire for this scenario. The right set of assessment and interviewing tools will help tech leaders identify talent fit from the early stages. Developers, too, will also need to be adaptable and willing to learn new skills in order to succeed in this new environment.

If you chase all the trends not only will you not keep up but you’ll likely lose sight of your core priorities. Technology should equip and enable you to serve your customers more effectively and expand the value you create for them. Technology isn’t self-justifying and you shouldn’t follow just any new trend. “Future-proofing” requires a deep understanding of your potential futures! What is your market, where do you have product/market fit, and what are your core competencies as a company? Focusing on the core drivers for your business will enable you to select a set of innovative technologies to keep an eye on and through that focus do a much better job avoiding change fatigue and avoid getting distracted with the latest shiny “innovation.”
– Steve O’Brien, President of Staffing at Job.com

Organizations that invest in their current and future workforces invest in themselves. The key to truly succeed is to constantly experiment, fail, learn, grow—and not be afraid to start the process anew when the world invariably changes again.

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Author
Ruehie Jaiya Karri
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June 9, 2021
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8 min read
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Vibe Coding: Shaping the Future of Software

A New Era of CodeVibe 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,...

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 code.

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 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.

Guide to Conducting Successful System Design Interviews in 2025

What is Systems Design?Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.Systems Design, in its...

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

  • Develop an understanding of basics of system design and architecture
  • Familiarize yourself with commonly asked systems design interview questions
  • Read about system design case studies for popular applications
  • Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

  • Plan the extent of the topics and scope of discussion in advance
  • Clearly define the evaluation criteria and communicate expectations
  • Quantify constraints, inputs, boundaries and assumptions
  • Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

  • Ask follow-up questions to challenge a solution
  • Probe candidates to gauge real-time logical reasoning skills
  • Make it a conversation and take notes of important pointers and outcomes
  • Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

  • Encourage candidates to explore and consider alternative solutions
  • Work with the candidate to drill the problem into smaller tasks
  • Provide context and supporting details to help candidates stay on track
  • Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.

How Candidates Use Technology to Cheat in Online Technical Assessments

Impact of Online Assessments in Technical Hiring In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers. The ease and...

Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.
  • Secure, sealed-off testing environment
  • AI-enabled live test monitoring
  • Enterprise-grade, industry leading compliance
  • Built-in features to track, detect and flag cheating attempts
Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.
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