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How to become a better developer: Top tips from 15 industry leaders

How to become a better developer: Top tips from 15 industry leaders

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Rohit C P
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January 3, 2017
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3 min read
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Last week when I sharedThe top programming languages that will be mostpopular in 2017, the frequent comment was, what does it take to be a better developer?

I’ve met some amazing developers in real life and through React Native Community, and I decided to ask them, “How do I become a better developer?” Thank you to everyone who took the time to answer these questions with passion!

This is a compilation of answers I received from them. Some of these quotes are not limited to answers from that specific question.

Interviewees / Current Position

  • Aravind Kumaraguru (Engineering Director @Pioneers in Engineering)
  • Brent Vatne (Front-end Developer @Exponent)
  • Charlie Cheever (Co-founder @Exponent)
  • Christopher Chedeau (Front-end Engineer @Facebook)
  • Dan Horrigan (Senior Back-end Developer @Futuri Media)
  • Frank W. Zammetti (Lead Architect @BNY Mellon)
  • Janic Duplessis (Co-founder @App & Flow)
  • Jake Murzy (Co-founder @commitocracy)
  • Jun Ho Hwang (Software Engineer @Coupang)
  • Keon Kim (Machine Learning Maniac @NYU)
  • Munseok Oh (Co-founder and CTO @Sketchware)
  • Satyajit Sahoo (UX Lead @ Glucosio & Front-end Engineer @Callstack.io)
  • Sonny Lazuardi Hermawan (Engineer @Sale Stock)
  • Sunggu Hwang (CTO @ScatterLab)
  • Timothy Ko (Software Engineer @Snapchat)


Q&A

Aravind Kumaraguru

Aravind is an undergrad at UC Berkeley pursuing a degree in Electrical Engineering and Computer Science and is Engineering Director for the nonprofit organization Pioneers in Engineering.

Q: How do you think I can become a better developer?

A: Obviously, never stay complacent with what you know – this field changes ridiculously fast, and you need to keep up with it. Follow along with the news in the tech industry, perhaps read up on some source code for a Python module that you recently used.

A friend of mine had some free time over winter break, so he decided to teach himself Django and build a webapp that he could interact with over SMS. It’s sort of a toy project, but he really enjoyed learning the different development paradigms. For context, he specializes in embedded systems and robotics, so this is nowhere near his comfort zone.

But pushing yourself to try different things will make you much stronger as an engineer. I personally wish I had done more web stuff before this year – in my organization (PiE), we’re developing a new iteration of a robotics kit to be used by high school students. While I have a good grasp of the low-level and systems stuff, I’m at a loss when it comes managing our UI design. Never had an interest in doing that type of stuff full-time, but having even a surface-level knowledge can be immensely helpful

Q: Do you have any projects you did to push yourself out of your comfort zone?

A: I built an automated door opener last summer, which operated a mechanical lever to open a door when an RFID card was scanned. The project used a really powerful motor and a mess of sensors to track the state of the arm, which proved to be quite difficult to coordinate. I learned real quick that I would need to do a bunch of offline testing before running my code on the device, which was very different from what I was used to up till then.

In terms of academics, I just finished CS 189, which was a massive crash course in data science, optimization, and probability theory. The programming I did in that class was also very different from what I’m used to, even though it was all in Python.


Brent Vatne

Brent is Front-end web/mobile developer working on Exponent and React Native. He contributes to tons of open-source projects.

Q: I really want to become a better developer; what would you say the first step is?

A: Do stuff you’re excited about and contribute to open source projects:-D

Q: How old are you and how much experience do you have as a programmer?

A: I am 30 years old, and very much 😮

Q: How did you join Exponent? What was the cause?

A: James (ide) and I were the most active contributors to a react-native outside of facebook and so we spoke a lot. He created exponent with Charlie. I ended up doing some consulting work with them and Charlie asked if I’d be interested in working with them full time and year, it was lots of fun so I joined.

Q: I should know objective C and Java thoroughly before I jump into React Native, right?

A: You can learn it as you go if you need to. there’s also tons of pure javascript stuff that need to be done. and documentation. lots of things 🙂


Charlie Cheever

Charlie Cheever is the co-founder of Quora, an online knowledge market. He was formerly an engineer and manager at Facebook, where he oversaw the creation of Facebook Connect and the Facebook Platform. Prior to Facebook, Cheever was employed by Amazon.com in Seattle. He left Facebook to start Quora in June 2009 to work on Exponent.

Q: What’s the motivation of Exponent being free and Open Source?

A: I really want to make something that like a 12-year-old version of me would use. So, someone who doesn’t know tons about programming but can learn new things and doesn’t have a credit card or lots of money, but has time and creativity and a phone and friends. I learned to program making calculator games on TI-85, it’s sad to me that kids can’t make stuff on their phones today.

Q: Why did you leave Quora?

A: I managed the mobile teams there and it was so slow to work on those apps even tho we had good people, I found it so frustrating And after I left I tried to build some mobile stuff and it was so annoying that I decided there needed to be a different way to make stuff. So James and I made something like react Native called Ion. It was strikingly similar actually. But React Native already had android support and 20 people working on it, and we had 2 people. So we decided to make everything else around it that we wanted to make!

Q: What did you do on Facebook?

A: I made the developer platform that all those games like FarmVille were on. Well, not all of it obviously but was one of two main developers. And I worked on the first version of facebook video, then did a lot of random other things. Then was a manager and did log in with Facebook on other sites, and then left to do Quora.

How to monetize your programming skills


Christopher Chedeau

Christopher has been working at Facebook as a Front-end Engineer for about 5 years. Previously, he worked at Curse Network.

Q: What do you do on Facebook?

A: I was on the photos team when I started, then I discovered React and started adopting and promoting it both internally and externally. I was there at the beginning of reacting native and pushed it through until 3 months ago. I just recently switched to the Nuclide team. I’m still #3 contributor on React Native.😛

Q: Do you have any prior work experience?

A: I was working for Curse (doing website for blizzard games) during my college to pay for it. It was fun to see the company go from 5 people in a guild to a 100 people company.

Q: What’s your day to day like on Facebook? The current project you’re working on?

A: I’m currently working on the Nuclide team, Facebook’s IDE built on top of Atom. I would say my time is spent half coding, half cheerleading all the cool stuff people are doing inside of FB.

Q: How do you think one can become a better developer?

A: I think that there are multiple levels.

The first level is mastering all the concepts. For example yesterday I had to write a function that removes certain keys from a big nested object. Because I’ve done this task so many times in the past, I was able to implement it in one go without even thinking and it worked the first time. For this one, exercises are really good. You want to code the same kind of things many many times to train your muscle memory.

The second level is how do you build things in a way that are not going to break in the future. Ideally, once you build something, you can move to the next thing and it’ll keep working without you there. This is challenging when there’s a ton of developers touching the codebase and product directions changing often.

Finally, the third level is how do you prevent a whole class of problems from even existing in the first place. A good example is with manual dom mutations, it’s very easy to trigger some code that interacts with a dom node that has been removed from the dom. React came in and made this problem go away. You have to go out of your way to do so, and even if you want to do those things, you have the tools to make it work: lifecycle events.

Q: Is there something you wish you’d known or learned earlier as a programmer?

A: Probably the most important thing is: tradeoffs, tradeoffs, tradeoffs. They are everywhere.

If you are working on some random throwaway feature that no one is going to use, who cares if the code is maintainable, you need it to work and now one mistake I see a lot is that people over-engineer the easy things but are not willing to make their architecture less clean from a CS perspective even though it actually provides the user experience you need.

At the end of the day, we write all this code for the users, we should first understand what the user experience should be and then do whatever it takes to get it. If the user just needs to display some content and needs to be able to edit it easily, just install WordPress, pick a good looking theme and call it a day

– Btw, pro-tip, if you want to be successful, always think about the value you are providing. If you are earning $100k a year, this means that the company should be making $200k because you’re here


Dan Horrigan

Dan is a Senior Back-end developer @Futuri Media. He has 20 years of programming experience in many different languages. He’s been contributing to React Native early/mid-2015.

Q: What’s your background as a programmer?

A: I started learning to program (with QBasic) when I was 11 and was hooked. I learned everything I could, as fast as I could. I learned a few languages like Visual Basic and started to dabble with C and C++. Then I found web development and dove in head first. First, learning HTML and CSS, then adding simple CGI scripts written in Perl, and eventually Classic ASP.

My first paying project was when I was 14: A website for the company my dad worked for, with a customer portal to let them see their job progress. This was all in ASP. After that, I started learning PHP, and have been using that as my language of choice ever since. However, I picked up a lot of experience with other languages along the way: JS, Python, Ruby (on Rails), Java, C#, Go, Objective-C.

Q: What are some projects you’re currently working on?

A: I work for Future Media (http://futurimedia.com). We provide SaaS solutions for Broadcast Radio and TV companies. We provide white label mobile applications, social engagement and discovery, audio streaming and podcast solutions, etc. I haven’t had much free time lately to contribute to many OSS projects, but hope to change that soon!

Currently, I am a Senior Back-End Web Developer, but I am transitioning into being the Director of Technical Operations.

Q: Is there something you wish you’d learned or knew earlier as a developer?

A: I wished I would have realized earlier in my career that it is OK to be wrong, and that failure is just a chance to learn.

Q: What’s the first step to becoming a good developer?

A: Come up with a small-ish project that you think would be cool, or would make your life easier, and just jump right in. Too many people try to learn without a goal other than “I want to learn to code.” Without a goal, you are just reading docs or copy/pasting from tutorials…you can’t learn that way.

To become a better developer, you need to do one simple thing: Never. Stop. Learning. Read other people’s code, figure out how that one app does that really cool thing you saw, read blogs, etc. No matter how good you are, or think you are, there is always someone better, and always more to learn.

Q: Is there a certain project you’re currently interested in? Next on your learning list?

A: I have been using, and occasionally contributing to, React Native since early/mid-2015, and continue to be interested in it.

Next, on my learning list is learning Erlang/Elixir. We build heavily distributed systems where I work and think we would really benefit from a language like that.


Frank W. Zammetti

Frank is a lead architect for BNY Mellon by day and the author of eight books on various programming topics for Apress by night

Q: How do I become a better developer?

A: I get asked this question quite a bit both at work from junior developers and from readers of my books. I always give the same answer: make games!

It sounds like a joke answer, but it most definitely is not! Games have a unique ability to touch on so many software engineering topics that you can’t help but learn things from the experience. Whether it’s choosing proper data structures and algorithms, or writing optimized code (without getting lost in micro-optimizations – at least too soon), or various forms of AI, it’s all stuff that is more broadly applicable outside of games. You frequently deal with network coding, obviously audio and visual coding (which tends to open your mind to mathematical concepts you otherwise might not be), efficient I/O and of course overall architecture, which has to be clean and efficient in games (and for many games, extensible). All those topics and more are things that come into play (hehe) when making games.

It also teaches you debugging and defensive programming techniques extremely well because one thing people don’t accept in games is errors. It’s kind of ironic actually: people will deal with some degree of imperfection in their banking website but show a single glitch in a game and they hate it! You have no choice but to write solid code in a game and you figure out what works and what doesn’t, how to recover from unexpected conditions, how to spot edge cases, all of that. It all comes into play and those are skills that developers need generally and which I find are most frequently lacking in many developers.

It doesn’t matter one bit if the game you produce is any good, or whether anyone else ever even plays it. It doesn’t matter if it’s web-based (even if your day job is), or mobile, doesn’t matter what technologies you use. The type of insight and problem-solving skills you build and tune when creating games will serve you well no matter what your day job is, even in ways that are far from obvious.

I’ve been programming games for the better part of 35 years now. No, none of them have been best-sellers or won awards or anything like that. In fact, it’s a safe bet that most people wouldn’t have even heard of my games, even the one’s still available today. None of that matters because the experience of building them is far and away the most rewarding part of it. Perhaps the best thing about programming games is that they are, by their nature, fun! You’re creating something that’s intended to be enjoyable so the process of creating it should absolutely be just as enjoyable. How many things can you do that are really fun while still being challenging and simultaneously help build the skills needed for a long career?

So yeah, make games, that’s my simple two-word answer!

Q: Is there something you wish you’d known or learned earlier as a programmer?

A: Hmm, tough question actually. I guess if there was one thing (and I’ll cheat and combine two things here because they’re related) I would say that early on I didn’t understand two very important phrases: “As simple as possible, but no simpler” and “Don’t let the perfect be the enemy of the good”.

I have a natural perfectionist mentality, so I spend a lot of time pondering architecture, API design, etc. I once spent 33 hours straight working on a Commodore 64 demo because ONE lousy pixel was out of place and my perfectionist brain just couldn’t live with it! Sometimes, I have to force myself to say “okay, it’s good enough, you’ve planned enough, now get to work and actually BUILD stuff and refactor it later if needed”, or I have to force myself to say “okay, it basically does what it’s supposed to, it doesn’t need to be absolutely flawless because nobody but me is even going to notice”. Especially when you’ve got deadlines and people relying on you, you have to make sure you’re working towards concrete goals and not constantly getting stuck trying to achieve perfection because you rarely are going to, at least initially anyway, no matter how hard you plan or try – and the dirty little secret in IT is that perfection rarely matters anyway! Good enough is frequently, err, good enough 🙂

And, your design/development approach should always strive to be as absolutely simple as possible. Of course, what constitutes “simple” is debatable and doesn’t necessarily even always have the same meaning from project to project, but for me some key metrics are how many dependencies I have (web development today is a NIGHTMARE in this regard – less is GENERALLY better) and how many layers of abstraction there are. Developers, especially in the Java world, like to abstract everything and they do so under the assumption that it’s more flexible. But if there’s one thing I’ve learned over the years it’s that the way to write flexible code is to write simple code. It’s better than abstractions and extension points and that sort of stuff because it’s just far easier to understand the consequences of your changes.

As a corollary, a terse code is NOT simpler code! Simple code is code that anyone can quickly understand, even less capable developers, and even yourself years after. Terse and “clever” code tends to be the exact opposite. Often times, the more verbose code is actually simpler because there are fewer assumptions and often less knowledge needed to understand it, less “code hoping” you have to do to follow things. Related to this is that writing less code isn’t AUTOMATICALLY better. No, you shouldn’t re-invent the wheel, but you also shouldn’t be AFRAID to invent a marginally better the wheel when it makes sense. Knowing the difference is hard of course and comes from experience, but if you think it’s ALWAYS better to write less code then you’re going to make your life harder in the long run.

Of course, don’t over-simplify code either. Too simple and suddenly extending it almost MUST mean a refactor. You never want to completely refactor because you HAVE to in order to build an app over time. There’s a balance that’s difficult to strike but it should always be the goal.

Oh yeah, and I wish I knew how to express myself in fewer words… but actually, I’m still obviously working on that one 🙂


Janic Duplessis

Janic is the co-founder of App & Flow, a react-native contributor, and open-source contributor.

Q: Any tips to becoming a better developer?

A: Don’t think there’s anything in particular, you just have keep learning and getting out of your comfort zone. Like trying a new language or framework from time to time. At least that’s what I do but I’m pretty sure there are some other good ways haha 🙂

Q: How can I start contributing to React Native?

A: The best is to start with something small like a bug fix or adding a small feature like an extra prop on a component. Most contributors know either iOS or Android and a bit of JS. There are also some JS devs that work on things like the package and clip. We keep some issues with a Good First Task label that should be a good place to start


Jake Murzy

Jake is an Open-source Archaeologist. He writes buzzword compliant code. Co-founder at @commitocracy.

Q: Hey Jake, any tips to becoming a better programmer? 🙂

A: Number one thing you should do is to learn your tools before you learn the language you work in because it will lead to faster feedback loops and you will get to experience more in less time. So install a linter and it will catch most of your errors as you type. It statically analyzes your code and recommends best practices to follow. You should always follow best practices until you gain enough experience to start questioning them.


Jun Ho Hwang

Jun is a software engineer at Coupang, which is the $5 Billion Startup Filling Amazon’s Void In South Korea. He is a very friendly developer who loves to connect.

Q: How do you become a better developer?

A: The word ‘better’ can be described in various ways–especially in the field of programming. A good developer could be someone who is exceptionally talented in development, someone who is amazing at communicating, or someone who understands Business very well. I personally think a “good” developer is someone who is in the middle–a person who can solve his or her business problem with their development skills, and communicate with others about the issue. Ultimately, to achieve this, it requires a lot of practice, and I recommend you to create your own service. Looking and thinking from the perspective of the user and improving the service to fulfill their needs really helps you grow as a better developer.

Q: Is there something you wish you’d known or learned earlier as a developer?

A: I really wish I started my own service earlier on. The hardest thing to grasp before developing is realizing how you can apply what you learned. Many developers are afraid to start a “service” because it sounds difficult; however, pondering about what to make and where to start, and then connecting those points of thought help you grow as a better developer.

Q: What do you do at Coupang? What are you currently working on?

A: Coupling provides a rocket-delivery-service, and I am working on developing a system called “Coupling Car,” which is related to insurance and monetary management. Furthermore, I’m thinking about adding transportation control system and the ability to analyze data from the log.


Keon Kim

Keon is a student at NYU who is really passionate about Machine Learning. He is a very active GitHub member who tries to contribute to open source projects related to machine learning.

Q: What are your interests? What kind of projects have you worked on?

A: I’ve been working on machine learning projects these days. I am one of the project members of DeepCoding Project, a project with a goal of translating written English to the source code. I’ve been contributing to a C++ machine learning framework called my pack(https://github.com/mlpack/mlpack), which is equivalent to skit-learn in Python.

I’ve also done some fun side projects: DeepStock (https://github.com/keonkim/deepstock) project is an attempt to predict the stock market trends by analyzing daily news headlines. CodeGAN (https://github.com/keonkim/CodeGAN) is a source code generator that uses one of the new deep learning methods called SeqGAN.

Q: How do you become a better developer?

A: I think it is really important to understand the basics. By basics, I mean math, data structures, and algorithms. Deep learning is really hot right now, and I see people jumping into learning it without basic knowledge in computer science and mathematics. And of course, most of them give up as soon as mathematical notations appear in the tutorial. I know this because I was one of them and it took me really long time to understand some concepts that students with a strong fundamentals could understand in a fraction of the time I spent. New languages, libraries, and frameworks are introduced literally every day these days, and you need the fundamentals in order to keep up with them.


Munseok Oh

Munseok is a Full-stack developer and CTO at Sketchware. He previously worked at System Integration for ~7 years.

Q: How do I become a better developer?

A: When I was very young and cocky, I evaluated other developers based on their coding style. There were certain criteria they had to pass in order for me to judge them as a good developer. But now, I really don’t think that way. Now, I believe that every developer is progressive, which means he or she is becoming a better developer every day. It doesn’t really matter if the style is bad or code is good–as long as the program runs, I think it’s great! Whether the program has room for growth or has bugs, I think the motivation to develop is what really matters. Developers usually are never satisfied with their skills. They are always eager to become better–probably why you’re doing this. It’s really hard to justify “good developer”. People like you will become better than me in no time. I still don’t think I am a good developer.

Q: What was the most difficult thing when you were developing Sketchware?

A: Developing Sketchware wasn’t too difficult because we had a good blueprint for the item. The direction was very clear for us to follow, so developing it was a breeze. However, there was a line we had to maintain for Sketchware–this line had two conditions:

  1. Sketchware must be an easy tool for anyone to create applications.
  2. Whatever the user takes away from Sketchware can be applied in their future career

Since we wanted Sketchware to be an efficient tool that can help users learn programming concepts, I am very considerate and think a lot when it comes to adding new features in the application.

Q: As a developer, is there something you wish you knew or fixed earlier?

A: I really wish I jumped into the Start-up world earlier. When it comes to developing, you need to be passionate and really enjoy what you do. Even if you pull 3 all-nighters, ponder all day long about a new algorithm, or stress about a new bug, everything will be okay if you’re enjoying it. It really goes back to the question #1–I get my energy from the joy I have when I develop, and that joy eventually makes you a better developer. When life hits you, most developers lose the passion for developing if you think of it as work. I used to be like that. But now, I’m really not worried–since developing brings joy to me now. Even if we run out of funds or our company burns down, it’s really okay since I am making the most out of what I am doing.


Satyajit Sahoo

Satyajit is the UX Lead at Glucosio, and Front-end Engineer at Callstack.io. He is an amazing open-source contributor; he is one of the top 5 contributors in React Native

Q: What is your background as a programmer?

A: I don’t really come from a programming background. I did my graduation in Forestry. I left post-graduation after getting a job offer and never looked back.

Q: What’s your day like on day to day basis?

A: It’s pretty boring. I wake up, order some breakfast online or go out, then start office work. In evening I go out to a bar or take a long walk if there’s enough time left. At night I mostly watch TV series or hack on side-projects.

Q: Motivation behind contributing to open source projects?

A: I’ve been involved in Open Source for a long time. When I was doing my graduation I got into Linux and got introduced to the world of Open Source. I loved it how we could learn so much from other projects. It fascinated me that developers were selfless to let us see and use the there code for free (mostly). I did a lot of Open Source projects in form of themes and apps during my college days, and it always made me happy when people forked them and changed to meet their needs, and send pull requests to fix things.

As a developer, I contribute to Open Source projects most of the time because I need a feature, or it improves something on a project I love. I think it’s better if we work together to fix stuff that is important to us rather than just filing issues.

Q: How do I become a better developer?

A: I think it’s important that we are open to new things. There’s a lot to learn, and we cannot learn if we stay in our bubble. Try new things, even if you think you can’t do it, even it looks complex on the surface. I have failed to do things so many times, but eventually succeed. In the process, I understand the problem and the solution, and then it becomes really simple.


Sonny Lazuardi Hermawan

Sonny is a JavaScript Full Stack Engineer, a React & React Native player, and an Open source enthusiast. He currently works as an Engineer at Sale Stock.

Q: How do you become a better developer?

A: I think always eager to learn is the key. Try everything, make mistakes, and learn from that mistakes. I agree that code review from partners and senior engineers will make our code better. Try publishing your own open source projects, meet other great developers and learn from them.

Q: What’s your motivation behind creating open source projects?

A: I just want the people to know about our idea, and try implementing it so that others can use our project. I’m really inspired by people that work on open source projects that used by many devs such as Dan Abramov that created redux.


Sunggu Hwang

Sunggu worked at Daum Communications for 4 years. Then, he left Daum to work at Scatter Lab as the CTO. This is his 5th year at Scatter Lab.

Q: How do you become a better developer?

A: Hmm… Becoming a good developer… Every developer has his or her own personality when it comes to programming. As an analogy, think about blacksmiths! Not all blacksmiths are alike–some enjoy crafting the best sword, while some might enjoy testing out the sword more than crafting it. I am a thinker–who plans and organizes thoughts before I carry out an action. I think a good developer knows how to write concise and clean code; you should practice this habit. Even though the trend for programming is always changing, and many people use different languages, write a piece of code that anyone can understand without comments.

Q: What do you think is the next BIG thing?

A: I’ve observed the evolution of programming languages, and I think it’s becoming more abstract every generation–procedural programming, imperative programming, functional programming… I think in the future, maybe in about 20 to 30 years, we will live in the time where the computer writes the code for us, and we just put them together like legos.

Q: What should I focus on studying?

A: I think deep learning is a must. Try different tutorials and learn it with passion. Math, algorithms–anything will help you in the long run.


Timothy Ko

Timothy is a software engineer at Snapchat. He previously worked at many places such as Riot Games, Square, etc.

Q: What do you do at Snapchat?

A: I’m a software engineer on the monetization team, so I work on anything related to making money. Some example projects are Snapchat Discover, a news platform within the iOS and Android apps; Ad Manager, a control panel used by sales and ad operations to flight ads; Ads API, which allows third-party partners to integrate their own ad platforms into Snapchat. Also, I was a past intern at Snapchat so I occasionally give talks and Q&As to upcoming interns. I’m also heavily invested in hiring and conduct a lot of interviews there.

Q: What do you do on a day-to-day basis?

A: What I’ve mentioned previously. Also, even after I pass on the work to other people, sometimes I have to go back and help support it or be part of the technical discussions on future changes. When new people join the team, usually I’m the one to ramp people up on how the code base looks like the kinds of frameworks we use, how a typical engineer workflow looks like, etc.

Q: What languages/framework do you guys mostly use?

A: For server code, it’s usually Java and for UI we use React Redux. Most teams work in google app engine, which is why we use Java, but some teams switch it up a little bit due to some app engine limitations. And of course, the product teams work in objective C for iOS and Java for Android.

Q: How do you think I can become a better developer?

A: I think the best thing to do is to do as many things as possible. I did seven internships while in school so I already had two years of work experience before I graduated. Work experience is super important because coding in a hackathon, doing personal projects, and doing school assignments are totally different than working with enterprise software and apps with real users. But you have to start somewhere, so that’s where going to school, doing personal projects, and competing in hackathons comes in. And while at work, I think the best way to succeed is to ask lots of questions and learn by doing. You can read and study all you want, but you might not understand what’s going on until you actually do it. Another thing is code reviews — you can do so much knowledge transfer by having a more senior engineer tear your code apart and tell you how to make it better. Also, if you ever come up with a proposal on how to solve a problem, getting a tech lead to bombard you with hard questions forces you to make sure you have every little detail covered.


*The article was originally posted by Sung Park on Github*

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Why traditional resumes no longer predict strong hires

Resumes measure presentation more reliably than capability. Recruiters have long used job titles, company names, degrees, and years of experience as proxies for performance, but generative AI tools — ChatGPT, Teal, Rezi, and Kickresume among them — have collapsed the cost of producing a polished application. The World Economic Forum's Future of Jobs Report 2023 found that 44% of workers' core skills are expected to change by 2027, which means a resume snapshot ages faster than the role it describes.

For recruiters, the operational impact is direct: pipelines fill, screen rates rise, and yet QoH stays flat. As AI becomes more deeply embedded in hiring, HR leaders are being forced to rethink a single question:

What if resumes are no longer the best predictor of performance?

That question is reshaping recruitment faster than many organizations expected — though, as discussed later, the shift away from resumes carries its own trade-offs.

Share of Workers' Core Skills Expected to Change by 2027
Source: World Economic Forum Future of Jobs Report 2023

The resume was built for a different era

Modern work no longer fits the resume's static format. Skills evolve in months rather than years, roles overlap across functions, and professionals build expertise through online communities, freelance projects, bootcamps, and self-directed learning. According to SHRM's 2024 Talent Trends research, nearly half of HR leaders report that candidates from non-traditional backgrounds are increasingly competitive on assessments.

Resumes still reduce people to standardized timelines, and many capable candidates are filtered out by ATS rules simply because they lack the "right" employer logos. At the same time, candidates skilled in resume optimization can outperform genuinely capable professionals at the screen stage — a pattern that pre-dates AI but has been amplified by it.

It has become far easier for candidates to generate polished resumes, cover letters, and interview responses in minutes. For recruiters, the takeaway is practical: formatting and phrasing are no longer reliable proxies for capability.

AI did not break hiring — it exposed existing problems

AI did not create the resume problem; it surfaced one already present in most hiring funnels. Surveys of recruiters, including Gartner's 2024 HR research, have consistently shown three pre-AI pressures: recruiters overwhelmed by application volume, candidates optimizing resumes to pass ATS filters, and hiring managers reporting weak outcomes despite reviewing seemingly strong resumes.

AI accelerated these problems to a point where they can no longer be ignored. Many candidates can now generate a highly optimized application in seconds, and recruiters increasingly struggle to distinguish between candidates skilled at self-presentation and those who can actually do the work.

The operational shift is moving from:

"What does your resume say?"

Toward:

"Can you actually do the job?"

The rise of skills-based hiring

Skills-based hiring outperforms resume screening because it measures demonstrated capability rather than credential proximity. A growing number of organizations — including IBM, Accenture, and Delta, profiled in LinkedIn's Skills Path program — are moving toward skills-first models that prioritize practical assessments, simulations, project work, and role-specific problem-solving over employer brand or degree.

This trend is most visible in technology hiring, where coding assessments and real-world technical evaluations generally provide stronger signals than resumes alone, particularly when compared against resume-only screens for time-to-productivity. HackerEarth has run over 100 million developer assessments across enterprise hiring programs, and the consistent pattern in that dataset is that demonstrated coding performance correlates more closely with on-the-job output than degree or prior employer.

Beyond tech, a growing number of organizations are extending the model: marketing teams using campaign-brief exercises, sales teams using recorded customer-handling scenarios, and operations teams using situational judgment tests. For a deeper view of how this maps to specific roles, see our skills-based hiring guide and developer assessment platform.

Where skills-based hiring breaks down

Skills-based hiring is not without trade-offs, and recruiters evaluating it should plan for known failure modes:

  • Assessment bias. Poorly designed assessments can disadvantage career returners, caregivers, and candidates with limited test-taking time as severely as resume screens disadvantage non-traditional backgrounds.
  • Gaming of take-home tests. Unproctored coding or case exercises are increasingly solvable with generative AI, which means assessment design has to evolve in step with candidate tooling.
  • Candidate experience at scale. Long assessment batteries lower completion rates and damage employer brand, particularly for senior candidates who have multiple offers in play.
  • Legal exposure. In jurisdictions including New York City (Local Law 144) and under the EU AI Act, automated employment decision tools are subject to bias audits and disclosure requirements. Recruiters should confirm vendor compliance before deploying AI-driven scoring.

The honest read: most organizations announcing a "shift" to skills-based hiring still filter by degree at the ATS layer. The shift is real, but it is uneven.

Skills-Based Hiring Priority vs. ATS Screening Reality
Source: LinkedIn Future of Recruiting 2024; ATS screening figure illustrative based on article claims

Why HR leaders are rethinking potential

Potential is becoming more measurable in ways resumes never allowed. Traditional hiring often prioritized pedigree — familiar universities, recognizable employers, conventional career paths — but AI-powered assessment platforms (HackerEarth, HireVue, Pymetrics, Codility, and Workday Skills Cloud among them) score candidates on demonstrated performance against role-specific tasks, calibrated to a benchmark population.

These tools typically combine task-based evaluations, behavioral simulations, and structured scoring rubrics. Their limits matter too: they score what they are trained to score, they can encode bias from the training population, and they do not measure long-arc traits like cultural contribution or leadership trajectory. Recruiters should treat them as one signal in a structured interview loop, not a single decision point.

Research suggests that candidates without elite degrees frequently match or outperform credentialed peers on standardized technical assessments. In many cases, career switchers and self-taught professionals demonstrate strong adaptability and practical skill. Organizations that shift toward capability-based evaluation may gain access to broader and more diverse talent pools — though, as noted above, only if assessment design itself is audited for fairness.

The recruiter's role is changing

AI is not replacing recruiters; it is shifting where recruiters spend their time. Traditional recruitment rewarded screening volume and speed. Modern hiring increasingly rewards judgment, stakeholder alignment, and structured decision-making.

As automation handles sourcing, scheduling, resume parsing, and initial outreach, recruiters are spending more time on work AI cannot do well:

  • Probing candidate motivation through structured behavioral interviews
  • Evaluating adaptability against specific role demands using scorecards
  • Building hiring-manager alignment on the req and intake brief
  • Designing candidate-experience touchpoints that protect offer-accept rates
  • Calibrating assessment results against on-the-job performance data

The recruiter who succeeds in an AI-heavy pipeline is the one who can interpret signal, not the one who can scan resumes faster.

Candidates are changing faster than hiring systems

Modern career paths now move faster than most ATS configurations. Today's workforce values flexibility, creativity, continuous learning, and project-based growth, and many professionals build experience through freelance work, startups, creator platforms, and side projects. Their resumes often look unconventional, but unconventional no longer equates to unqualified.

Organizations that shift toward capability-based evaluation may access talent pools that rigid resume filters would otherwise miss. For practical guidance on adjusting screening criteria, see our guide to evaluating an ATS for skills-based hiring.

The future of hiring will feel more human

There is an irony in the AI shift: as resumes become easier to automate, organizations are being pushed to evaluate creativity, adaptability, collaboration, and real-world problem-solving more directly. The likely structure of mature AI-enabled hiring is AI handling repetitive tasks — sourcing, scheduling, parsing, initial scoring — while recruiters and hiring managers focus on nuance, context, and long-term fit.

FAQ

Is skills-based hiring more effective than resume screening? Skills-based hiring tends to predict on-the-job performance more reliably than resume screening for roles where the work can be assessed directly, such as engineering, data, sales, and marketing execution. According to LinkedIn's Future of Recruiting report, 73% of recruiters now prioritize skills-based approaches. Effectiveness depends heavily on assessment design and on whether downstream ATS filters still gate candidates by degree.

What HR processes is AI changing first? AI is changing sourcing, resume parsing, candidate matching, and initial assessment scoring first, because these are high-volume, rules-based tasks. Structured interviewing, offer negotiation, and onboarding remain primarily human-led, though AI-assisted note-taking and scorecard analysis are growing.

Will AI replace recruiters? AI is unlikely to replace recruiters, but it is changing the skill profile. Recruiters who can interpret assessment data, align hiring managers, and design candidate experience will be more valuable; recruiters whose role is primarily resume scanning are most exposed.

How do I evaluate an AI hiring tool for bias? Ask the vendor for a bias audit report (required under NYC Local Law 144 for automated employment decision tools), the demographic composition of the training data, the validation methodology against job performance, and the appeal process for candidates. Avoid tools that cannot answer all four.

Is resume-based hiring going away? Resume-based hiring is under pressure but not disappearing. Most organizations are moving toward hybrid models where resumes provide context and assessments provide the capability signal. A full move away from resumes is unlikely in the next hiring cycle for most enterprises.

What is the biggest risk of switching to skills-based hiring? The biggest risk is poorly designed assessments that introduce new forms of bias or damage candidate experience. A skills-based process built on a long, unproctored, untested assessment battery will perform worse than a structured resume screen.

Next steps: See it in action

If you are a recruiter or talent leader evaluating how to move from resume-led to skills-led screening, book a demo of HackerEarth Assessments to see how role-specific evaluations, proctoring, and benchmarked scoring fit into an existing ATS pipeline. For background reading, see our developer assessment platform overview and the HackerEarth recruiter blog.

Recruiters who pair structured assessment data with strong human judgment build better pipelines than either resumes or AI alone can produce.

Must-Know Recruitment Questions for HR and Talent Acquisition Teams (2026)

Recruitment questions every HR professional should know in 2025

Estimated read time: 7 minutes

Most "tell me about yourself" answers are now written by ChatGPT the night before the interview. That single shift — candidates arriving with rehearsed, AI-polished narratives — has broken the standard interview script and forced recruiters to redesign their question sets from the ground up. This guide outlines the categories of recruitment questions every HR professional should know in 2025, why each matters, and example questions you can adapt to your hiring rubric or scorecard today.

LinkedIn's 2024 Global Talent Trends report notes that skills-based hiring and behavioral assessment have moved from optional to expected in most talent acquisition workflows. Yet many hiring conversations still rely on outdated prompts that produce polished answers and unclear signals. The recruiter persona — the one running req intake, pipeline reviews, and screen calls — needs a tighter toolkit.

Who this is for: This article is written for recruiters and talent acquisition partners running structured interviews. Hiring managers building a scorecard alongside the recruiter will also find the question categories useful.

Adoption of Structured Hiring Practices Among HR Teams (2020–2025)
Source: LinkedIn Global Talent Trends claims cited in article

Why modern recruitment questions fail when they stay outdated

Industry observers at SHRM have noted that candidates are better prepared, interviews are more structured, and expectations on both sides have risen (SHRM research). With generative AI tools widely available, many candidates now enter screens with refined, rehearsed narratives.

The result is predictable — polished answers, unclear signals, and decisions made on incomplete understanding. The quality of the recruitment questions you bring into the room directly defines the quality of the signal you capture on the scorecard.

A contestable position worth stating plainly: behavioral interview frameworks like STAR are now overused to the point where candidates have memorized the structure, which reduces signal quality unless interviewers probe past the rehearsed answer with follow-ups.

What this article won't claim

Structured behavioral interviewing is not a silver bullet. Over-indexing on adaptability can screen out deep specialists whose value is stability and depth. Ownership-mindset framing, if applied rigidly, can disadvantage neurodivergent candidates or those from cultures where collective credit is the norm. Use the questions below as part of a balanced rubric — not as a single filter.

From "tell me about yourself" to understanding real intent

Traditional opening questions rarely reveal a candidate's intent or direction. A stronger opening probes why a candidate is moving at this specific point and what kind of work keeps them engaged beyond compensation.

Evidence from Gallup's 2023 State of the Global Workplace report suggests today's workforce is increasingly motivated by alignment, learning, and perceived growth — not stability alone. If this layer is missed early in the interview, the rest of the evaluation becomes less reliable.

Example intent and motivation questions

  • "Walk me through the last time you decided to leave a role. What specifically triggered the decision?"
  • "What kind of work has made you lose track of time in the last 12 months?"
  • "If this role didn't exist, what would your second-choice next move be — and why?"
  • "What would need to be true 18 months from now for you to consider this move a success?"

What to listen for

  • Specific triggers and trade-offs, not generic phrases like "growth" or "new challenges."
  • Consistency between the stated motivation and the candidate's actual career pattern.

Red flags

  • Answers that match the job description back to you almost verbatim.
  • Vague language about "culture" or "growth" with no concrete example.

Behavioral and competency-based recruitment questions: getting past scripted answers

One of the biggest challenges recruiters face today is not lack of talent, but over-prepared talent. Hiring practitioners increasingly find that well-structured, confident answers do not always reflect real capability, especially when responses are influenced by preparation tools or rehearsed narratives.

This is why competency-based questions — which explore decision-making logic, trade-offs, and real-time reasoning — produce higher signal than story-based prompts alone. For technical roles, pairing these with a practical assessment helps confirm what the interview surfaces. HackerEarth's skill assessments use role-specific question libraries and rubric-based scoring so the recruiter can compare candidate outputs against a defined standard, rather than relying on the candidate's own narrative of their capability.

Example behavioral and competency-based questions

  1. "Tell me about a decision you made in the last six months that you would make differently today. What changed your thinking?"
  2. "Describe a time you disagreed with your manager on a priority. How did you handle it?"
  3. "Walk me through a project where the scope changed mid-execution. What did you cut, and why?"
  4. "Give me an example of feedback you initially rejected but later acted on."

How to probe past the rehearsed answer

If a candidate delivers a clean STAR-format response, follow up with: "What's one detail you usually leave out of that story?" or "Who would tell that story differently?" These prompts disrupt the rehearsed structure and surface the actual reasoning.

Situational judgment and adaptability questions

Workplaces are shaped by continuous change — shifting priorities, evolving tools, and hybrid collaboration. Many hiring teams now treat adaptability as a core hiring parameter rather than a soft skill, particularly for roles where ambiguity is the default state.

Situational judgment questions present a realistic scenario and ask the candidate how they would navigate it. They are harder to rehearse than story-based prompts because the scenario is novel.

Example situational judgment questions

  • "You join the team and discover the project you were hired to lead has already slipped two months. What are your first three actions in week one?"
  • "Two stakeholders give you conflicting priorities on the same Friday. Both are senior to you. How do you handle it?"
  • "A teammate is consistently delivering work that is technically correct but late. You are not their manager. What do you do?"
  • "You realize halfway through a quarter that the metric you committed to is no longer the right one. How do you raise it?"
  • "Your top-performing team member tells you in a 1:1 they're considering leaving. They haven't told their manager. What do you do in the next 24 hours?"
  • "A vendor misses a critical deadline that puts your launch at risk. Walk me through how you decide whether to escalate, switch vendors, or absorb the delay."

What to listen for

  • Sequencing — do they ask clarifying questions before acting?
  • Trade-off awareness — do they acknowledge what they would not do?
  • Stakeholder reasoning — who do they involve, and when?

Culture and values-alignment questions

Cultural fit is often misunderstood as shared interests or personality alignment. A more useful frame is behavioral consistency with the team's working norms.

A second contestable position: generic "culture fit" questions should be retired in favor of values-alignment scenarios that name a specific behavior the company expects. "Culture fit" as a phrase invites bias; a scenario tied to a stated company value forces a more concrete answer.

Example values-alignment questions

  • "Our team gives feedback in writing before live discussion. Describe the last time you gave hard feedback. What did you write down first?"
  • "We prioritize shipping over perfection. Tell me about a time you shipped something you weren't fully proud of. What happened next?"
  • "Describe the last time you changed your mind because of data, not opinion."

For a deeper look at how culture signals show up in technical interviews, see our guide on how to design a structured technical interview.

Identifying ownership mindset over task execution

Task completion alone is no longer a strong hiring indicator for most knowledge roles. What recruiters and hiring managers increasingly screen for is the ownership mindset — how a candidate behaves when outcomes are unclear, accountability is shared, or success metrics evolve mid-execution.

A concrete scenario

Consider a Series B SaaS company hiring its first sales operations manager. The pipeline is messy, the CRM is half-implemented, and the founder is the de-facto rev-ops owner. Standard task-execution questions ("walk me through how you'd clean a pipeline") produce textbook answers. Ownership-mindset questions — "What would you stop doing in your first 30 days, and how would you tell the founder?" — surface whether the candidate can hold the seat. A strong answer names a specific thing they'd stop (e.g., "weekly pipeline reviews in their current form"), the trade-off they're willing to accept, and how they'd frame the conversation with the founder. A weak answer lists everything they'd add — new dashboards, new processes, new tooling — without naming a single thing they'd remove or a single conversation they'd own.

Example ownership questions

  • "Tell me about something you fixed that wasn't your job to fix."
  • "Describe a time the goalposts moved on you. What did you do in the first 48 hours?"
  • "What's a process you killed, and what replaced it?"

Red flags

  • Answers that always credit "the team" with no individual decision named.
  • Stories where the candidate is consistently the rescuer or always the victim.

Questions to avoid: legal and compliance boundaries

A structured question set is only as strong as its weakest prompt. In most jurisdictions, certain questions are either illegal or carry significant legal risk because they touch protected characteristics or regulated information.

Common categories to avoid in initial screens:

  • Age, date of birth, or graduation year as a proxy for age.
  • Marital status, family planning, or childcare arrangements ("Do you plan to have kids?" "Who watches your children?").
  • Citizenship or national origin beyond the legally permitted "Are you authorized to work in [country]?"
  • Religion, religious holidays, or observance schedules.
  • Disability or medical history, including questions about prior workers' compensation claims.
  • Salary history — now restricted or banned in many US states and several other jurisdictions. Ask about salary expectations instead.

For a deeper treatment of pre-employment screening practices and compliance, see our overview of pre-employment assessment design. Always confirm specifics with your legal or HR compliance partner — local law varies.

Rethinking what "good answers" actually mean

In traditional interviews, clarity and confidence were often equated with strong performance. Modern hiring increasingly challenges this assumption.

The signal you want is depth, consistency, and reasoning quality — even when responses are less polished. A candidate who says "I don't know, but here's how I'd find out" is often a stronger hire than one who delivers a fluent answer with no underlying logic.

To codify this on the scorecard, score reasoning and presentation as separate rubric lines. A candidate can score 4/5 on reasoning and 2/5 on presentation and still be a strong hire — but you will only see that if the rubric separates them.

FAQ: structured hiring questions

Which recruitment question category is most often skipped — and why does it matter?

In practice, ownership-mindset questions are the category recruiters most often skip, because they're the hardest to score consistently and the answers don't fit neatly into STAR. The cost of skipping them is high: ownership signal is what separates strong individual contributors from people who execute well only when the path is clear. If you only have time to add one new category to your interview guide, this is the one with the largest marginal lift.

What is the STAR method, and is it still useful?

STAR stands for Situation, Task, Action, Result. It is a candidate-response framework that helps structure answers to behavioral questions. It remains useful as a default structure, but because most candidates now prepare STAR-formatted stories, interviewers should probe past the rehearsed answer with follow-up questions about trade-offs, omitted details, and alternative perspectives.

How many interview question frameworks should a structured interview include?

Practitioners commonly recommend 5–8 core questions per 45-minute round, with planned follow-up probes. This is a rule of thumb rather than a sourced standard. Fewer questions with deeper probes typically produce more signal than many surface-level questions.

What is the difference between behavioral and situational judgment questions?

Behavioral questions ask about past actions ("Tell me about a time you…"). Situational judgment questions ask about hypothetical scenarios ("What would you do if…"). Behavioral questions test verified history; situational questions test reasoning on novel problems. Strong interview loops use both.

How do you reduce bias in recruitment questions?

Use a structured interview where every candidate is asked the same core questions, score answers on a defined rubric, and have at least two interviewers calibrate independently before discussing. Avoid "culture fit" as a freeform judgment; replace it with values-alignment scenarios tied to documented company behaviors.

Can skill assessments replace interview questions?

No. Assessments and interview questions answer different things. Assessments produce structured skill evaluation against a defined rubric; interview questions surface reasoning, motivation, and judgment. The strongest hiring loops pair both — skill assessments for verified capability, structured behavioral interviews for everything assessments can't measure.

Final thoughts and next steps

The recruitment questions every HR professional should know in 2025 are not a fixed list — they are a working toolkit you adapt to the role, the level, and the rubric. The categories above (intent, behavioral, situational, values-alignment, ownership) give you a structure; the example questions give you a starting point.

Next steps

  • Audit your current interview guide. Map every question to one of the five categories above. If a category is empty, add two questions.
  • Separate reasoning from presentation on your scorecard. Score them as distinct rubric lines.
  • Pair interviews with skill verification. Schedule a demo of HackerEarth Assessments to see how rubric-based skill scores integrate with your interview scorecard, so your hiring decision isn't relying on candidate self-report alone.

Sources referenced: LinkedIn Global Talent Trends, SHRM Research, Gallup State of the Global Workplace.

Why Empathy Could Be Your Biggest Hiring Advantage

Why Empathy Could Be Your Biggest Hiring Advantage

Why Human-Centered Hiring Matters More Than Ever

Hiring has never been more optimized than it is today.

From AI-powered recruitment tools to automated screening systems and structured interview workflows, HR and talent acquisition teams now have more ways than ever to improve hiring speed, consistency, and scalability.

But in the middle of this efficiency-driven approach, one critical element is slowly disappearing: employee empathy.

Empathy in hiring is not about slowing down recruitment or making decisions less objective. It is about ensuring candidates are treated like people navigating important career decisions, not just profiles moving through a hiring pipeline.

As recruitment becomes increasingly system-driven, preserving the human side of hiring is becoming both more difficult and more important.

For HR leaders and talent acquisition professionals, this is no longer just a workplace culture discussion. It directly impacts candidate experience, employer branding, hiring quality, and long-term employee retention.

When Hiring Feels Like a Process Instead of an Experience

Most modern recruitment systems are designed around efficiency.

Applications are filtered automatically, interviews are scheduled faster, and candidates move through hiring stages with minimal manual effort. Operationally, this creates speed and structure.

But from a candidate’s perspective, the experience can often feel distant and impersonal.

Many candidates go through multiple interview rounds without clear communication, feedback, or transparency about timelines and expectations. Even when the hiring process is fair, it may still feel mechanical.

This creates a growing challenge for HR and TA teams:

How do you maintain hiring efficiency without removing the human connection from recruitment?

That is where empathy becomes essential.

The Hidden Cost of Low-Empathy Hiring

The impact of low-empathy hiring is not always immediate, but it compounds over time.

Candidates remember how organizations made them feel during the recruitment process, especially during rejection or delayed communication. Those experiences shape employer perception long before someone becomes an employee.

Over time, this directly affects employer brand and candidate trust.

There is also another hidden cost.

When hiring becomes too rigid or overly process-driven, recruiters may overlook candidates with strong long-term potential simply because they do not perfectly match predefined criteria.

Without empathy, context disappears.

And when context disappears, opportunities are often missed.

For HR leaders, empathy is no longer just a soft skill. It is becoming a competitive hiring advantage.

Why Empathy Is Becoming a Competitive Hiring Skill

Today’s workforce is far more dynamic than it was a decade ago.

Professionals switch industries, build careers through unconventional paths, and learn skills outside traditional education systems. As a result, resumes and structured evaluations only tell part of the story.

Empathy helps recruiters understand what exists beyond the surface.

It allows hiring teams to better understand:

  • Career transitions
  • Employment gaps
  • Nontraditional experience
  • Personal growth journeys

This shift changes the entire hiring mindset.

Instead of asking:

“Does this candidate perfectly match the role?”

Recruiters are increasingly asking:

“What could this candidate become in the right environment?”

That perspective creates stronger and more future-focused hiring decisions.

Where Empathy Fits in Modern Recruitment

Empathy does not replace structured hiring systems.

In fact, it becomes most effective when built into them.

Simple improvements in communication can significantly improve candidate experience. Clear updates, transparent timelines, respectful rejection emails, and honest feedback all contribute to a more human-centered recruitment process.

These small changes often have a lasting impact on how candidates perceive an organization.

For HR teams, the goal is not to remove structure from hiring.

The goal is to ensure structure does not remove humanity.

Better Hiring Decisions Start With Better Human Understanding

Empathy also improves the quality of hiring decisions themselves.

When recruiters take time to understand a candidate’s context, they often uncover strengths that are not immediately visible on resumes or scorecards.

A candidate who appears average on paper may demonstrate exceptional adaptability, resilience, or problem-solving ability in real-world situations.

Without empathy, those signals are easy to miss.

For talent acquisition leaders, this means recognizing that hiring is not just about selecting the strongest profile.

It is about identifying the strongest long-term fit within a real human context.

Final Thoughts

As recruitment continues evolving through automation, AI hiring tools, and structured decision-making, the biggest risk is not losing efficiency.

It is losing humanity.

Employee empathy ensures hiring remains people-focused, even as processes become more technology-driven.

It does not slow recruitment down. Instead, it helps organizations create better candidate experiences, stronger employer brands, and more thoughtful hiring decisions.

Because candidates may forget interview questions or assessment scores.

But they will always remember how they were treated during the hiring process.

And in today’s competitive talent market, that experience often determines whether top talent chooses to join or walk away.

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