Home
/
Blog
/
Hiring Strategies
/
4 Images That Show What Developers Think Of Layoffs In Tech

4 Images That Show What Developers Think Of Layoffs In Tech

Author
Kumari Trishya
Calendar Icon
November 16, 2022
Timer Icon
3 min read
Share

Some days ago, we polled our Twitter and LinkedIn community and asked them if they would ever take another job at the company that laid them off. This was the result.

Layoffs in tech - Poll

The two years of the pandemic (2020-2022) saw 1100+ companies globally laying off employees. In the first 8 months of 2022, we reached half that number with 500+ companies announcing layoffs in tech in August. The number of employees who had lost their jobs globally stood at 72,900+ at the end of the month.

The massive wave of downsizing has hit every tech sector in the world. Credit Suisse and Goldman Sachs have reduced their employee size, with BofA and JPMorgan saying they are being cautious. Meta, Twitter, Netflix, Noom, Wipro, and Oracle are just some of the tech names that have had to let go of their workforce. Nordstrom, Wells Fargo, Beyond Meat, Peloton – almost everyone has had to take these measures to preserve capital.

The question everyone is asking is – didn’t we learn anything during the pandemic?

COVID was a bonafide ‘black swan’ event that defied predictions. However, many economists have been talking about an impending recession for a while now. Despite the warning signals, most of the corporate world ended up repeating the hiring-and-firing pattern that has become the norm after macroeconomic events.

This is what normally happens during every downturn:

  1. Companies go into ‘freeze’ mode. Hiring stops, budgets are cut, and perks are canceled.
  2. If the company has not planned ahead, the hiring freeze very soon turns into a layoff.
  3. When the market starts to rebuild, companies hire overzealously to make up for lost time and effort.
  4. This overzealous hiring usually pays off in a V-shaped recession where the markets rebound sharply after a dip. Most recessions aren’t this forgiving, and companies that have hired in a rush may end up having to find ways to cut extra baggage.

Our post-COVID normal followed the same pattern as well. There is no denying that the use of technology boomed during the pandemic, causing every industry sector to adopt and focus on new tech tools.

The overwhelming consensus that ‘every company is now a tech company’ caused a sudden demand for developers. Even as we were all still coming to terms with the ‘new normal’, tech hiring (and hiring in general) burgeoned so much that top-tier talent was able to demand a 100% salary hike in an unprecedented candidate’s market.

All of which led us to this.

Tech hiring has undergone a sea change in the last two years. We have replaced outdated modes of assessment and interviews with new AI-based tools for efficiency. Remote work is the mantra we all live by. While the overall ‘work culture’ in many tech companies has become more empathetic and people-focused, this empathy has still not trickled into the way we handle layoffs in tech.

Also, read: Greeks to Geeks: What Plato Says About Bettering Your Team Culture

Airbnb garnered a lot of ‘awwws’ when CEO Brian Chesky wrote a heartfelt email to employees announcing, and apologizing, for the COVID-induced downsizing. The company even offered outplacement support, and its post-employment care strategy was among the most detailed and comprehensive that American companies were offering at that time.

Airbnb was an outlier. Most layoffs in tech that happened during COVID happened unexpectedly, without warning, and over a Zoom call or two. Reiterating what we stated in the beginning, trust issues are an undeniable outcome of such processes.

In the past decade, Nokia received a lot of praise among the developer community for its outplacement program ‘Bridge’, which was created in 2011 when the company was faced with the harsh choice of laying off employees. The program’s objective — and the metric that Nokia used to gauge success — was the percentage of employees who knew what their next step would be the day they left the company.

Nokia’s program showed the tech world that changes needn’t always be brutal and that employers have a responsibility to their employees and the communities they engage with. Using this philosophy of accountability to create processes for layoffs requires companies to be more transparent than they have ever been before, engage in constant communication with employees and local communities, and build a robust outplacement support system that does not just end with a severance package.

This need for outplacement support was called out loudly by our developer community, too.

Layoffs in tech - Poll 2

So, what’s a better way for handling layoffs in tech?

Let’s begin by accepting that layoffs in tech are hard – for the employee who is losing their job, the recruiter or HR professional who is tasked with breaking the sad news to the team, and the company itself.

Layoffs hurt a company’s bottom line. Facts below:

  • A 2012 University of Austin Texas review of 20 companies that had engaged in layoffs found that layoffs had a neutral to negative effect on stock prices in the days following the announcement.
  • A related study says that the majority of companies that conducted layoffs were less profitable for up to three years after the layoff.
  • A third study conducted by researchers from Auburn University, Baylor University, and the University of Texas shows that companies that conduct layoffs are twice as likely to file for bankruptcy in the next five years than companies that had found other ways to bolster profitability.

Also, read: Fear and Layoffs: How to Cope with Tech’s Uncertain Times

When we polled the recruiters in our community, they unequivocally said that hiring post a layoff is harder, as it affects the company’s branding and sourcing efforts.

Layoffs in tech - Poll 3

So, if you are looking for alternative ways to handle layoffs in tech, or avoid getting to the point where you have to cut down your workforce, then we have some tips for you:

  • Avoid reflex hiring: Most companies speed up hiring as soon as they see signs of market recovery. The term ‘hiring frenzy’ is real. Instead of going with the trend, make realistic projections for the team you want to build, and approach your hiring meticulously.
  • Hire slightly below your projection: At any given time, the HackerEarth staff portfolio operates at about 90% of what we consider ‘full capacity’ or ‘ideal’. This isn’t understaffing. We have consciously decided to not hire a full house to give ourselves some breathing space and avoid a domino effect when the market changes rapidly, causing internal “accidents”.
  • Invest in your team culture: If you’re not hiring specialists for every single role, then you need to staff your team with people who are willing to wear multiple hats and adapt quickly. Note, there is a thin line between hiring talent that is willing to diversify and handle multiple projects, versus overworking your team. If you tread this line carefully though, you can build a robust, multiskilled, and adaptive team that can weather market changes without breaking down.
  • Invest in your team culture 2.0: Companies often refer to their workforce as a ‘valuable asset’ when things are going well. It’s ironic that you would let go of your most valuable possession in a heartbeat! Stay people-focused first and forever, so when you have to ask your teammates to step up during a crisis, they do not feel like they are being taken for granted.
  • Explore all possible avenues: Job sharing (in which two people fill a single role and take home a 50% pay), furloughs, temporary pay cuts, salary rollbacks – there are many ways to budget and save money that do not involve mass layoffs.
  • Plan for crisis: We all love the Google model of workplaces that offer every single amenity one can dream of (and maybe more), handsome bonuses, and whatnot. These are lovely add-ons to our work life, but they shouldn’t become addictions. When Better.com had to lay off about 900 people in 2021, the CEO admitted in an open call that the company could have done a better job of managing funds, which could have delayed – possibly prevented – the mass downsizing. The bottom line: manage your money Better.

It’s time to lay off the layoff!

My sorry attempt at wordplay aside, the way a company handles a moment of crisis says a lot about its overall culture. About 90% of the developers from HackerEarth’s community say that they would look at layoff measures as a reflection of the brand’s EQ. On the other hand, about 21% of the recruiters polled on our LinkedIn handle said that they think there’s ‘not much’ that can be done about layoffs. They are part and parcel of the job and should be treated as such.

Layoffs in tech - Poll 4

Layoffs in tech - Poll 5

When Gartner surveyed more than 3,500 employees around the world in October 2021, about 65% said the pandemic had made them rethink the place that work should have in their life, and look for personal value and purpose at work. It stands to reason then that employees who think their bosses do not value them would want to look for opportunities elsewhere.

This is precisely the message you send to your employees – and the larger developer community – when you announce a mass layoff willy-nilly, and sans any support systems in place. That you don’t care. And that’s got to hurt your employer brand for sure.

Research shows that job cuts rarely help leaders achieve their goals. More often than not, layoffs are good only for short-term gain, and the cost savings are generally overshadowed by negative employer branding, loss of knowledge, reduced employee engagement, higher voluntary attrition, and reduced innovation. You might save in the short term, but most probably you will see a dip in profits, and your employee engagement, in the long run.

Here’s your chance to be a better employer and prove that the values of empathy and compassion we all talked about so much during COVID were not a ‘black swan’ event unto themselves. Here’s hoping you handle the storm differently than how everyone else is.

Subscribe to The HackerEarth Blog

Get expert tips, hacks, and how-tos from the world of tech recruiting to stay on top of your hiring!

Author
Kumari Trishya
Calendar Icon
November 16, 2022
Timer Icon
3 min read
Share

Hire top tech talent with our recruitment platform

Access Free Demo
Related reads

Discover more articles

Gain insights to optimize your developer recruitment process.

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 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 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 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.
Top Products

Explore HackerEarth’s top products for Hiring & Innovation

Discover powerful tools designed to streamline hiring, assess talent efficiently, and run seamless hackathons. Explore HackerEarth’s top products that help businesses innovate and grow.
Frame
Hackathons
Engage global developers through innovation
Arrow
Frame 2
Assessments
AI-driven advanced coding assessments
Arrow
Frame 3
FaceCode
Real-time code editor for effective coding interviews
Arrow
Frame 4
L & D
Tailored learning paths for continuous assessments
Arrow
Get A Free Demo