u/Neil_at_HackerEarth

I’ve been thinking about this a lot lately.

Two candidates can have almost the same skills.

One gets nervous, takes a little longer to solve the problem and struggles to explain their thinking.

The other is confident, talks well and gets through the questions quickly.

Guess who usually gets the offer?

And that’s where technical hiring gets interesting.

A 45-minute interview can tell you a lot about someone but it can also miss a lot.

Someone might be an excellent engineer but terrible at interviews.

Someone else might be great at interviews but only average at the actual work.

So what should hiring teams really be measuring?

Technical knowledge?

Problem-solving?

Communication?

Actual work samples?

Or a mix of everything?

I’d genuinely like to hear from both sides:

Hiring managers - what makes you say “yes”?

Candidates - what do you think interviews fail to measure?

I’ve been thinking about this a lot lately.

Two candidates can have almost the same skills.

One gets nervous, takes a little longer to solve the problem and struggles to explain their thinking.

The other is confident, talks well and gets through the questions quickly.

Guess who usually gets the offer?

And that’s where technical hiring gets interesting.

A 45-minute interview can tell you a lot about someone but it can also miss a lot.

Someone might be an excellent engineer but terrible at interviews.

Someone else might be great at interviews but only average at the actual work.

So what should hiring teams really be measuring?

Technical knowledge?

Problem-solving?

Communication?

Actual work samples?

Or a mix of everything?

I’d genuinely like to hear from both sides:

Hiring managers - what makes you say “yes”?

Candidates - what do you think interviews fail to measure?

I’ve been seeing more recruiters use AI interview tools for the first round of technical hiring.

On paper, it sounds pretty useful. You have 100+ candidates, limited interviewer time, and nobody wants to spend 30 minutes on every candidate.

But I’m curious about what happens in real hiring.

For recruiters, HR teams, or recruitment agencies who have actually used one:

- Did it really reduce the time spent on first-round interviews?

- Were the questions relevant to the actual role?

- Could it properly follow up when a candidate gave an interesting answer?

- Did you end up shortlisting better candidates, or just faster?

- How did candidates react to being interviewed by AI?

- Did you still need a recruiter or engineer to review most of the interviews manually?

- And was the cost actually worth it?

Would be especially useful to hear some real numbers.

Something like:

“We had 200 candidates -- AI screened 120 -- 30 moved ahead -- saved X hours of interviewer time.”

Even examples from different hiring volumes or technical roles would be useful.

I’m particularly interested in how recruiters are using these tools in their actual workflow - what they use them for, which parts of the process they automate, and where they still involve a human interviewer.

Anyone here using an AI interview assessment tool for technical hiring?

What does your process look like?

I've been thinking about this lately.

A normal coding test can tell you if you got the answer right or wrong.

But in an actual interview, you also have to explain why you did something.

Like why you picked that approach, what you'd change if the requirements changed, or what you'd do if your code starts failing.

And honestly, thats the part I struggle with more than the coding itself.

So I kinda get why AI interviews are becoming a thing.

If an AI interviewer can ask follow-up questions based on what you said, it could be pretty useful for practice. You get to practice explaining your thinking instead of just solving questions.

But then again... does it actually feel like a real interview?

Or is it just another way of practising questions?

Curious what developers/students here think.

Would you use something like this before an actual technical interview?

I’ve been thinking about this a lot lately.

Two candidates can have almost the same skills.

One gets nervous, takes a little longer to solve the problem and struggles to explain their thinking.

The other is confident, talks well and gets through the questions quickly.

Guess who usually gets the offer?

And that’s where technical hiring gets interesting.

A 45-minute interview can tell you a lot about someone but it can also miss a lot.

Someone might be an excellent engineer but terrible at interviews.

Someone else might be great at interviews but only average at the actual work.

So what should hiring teams really be measuring?

Technical knowledge?

Problem-solving?

Communication?

Actual work samples?

Or a mix of everything?

I’d genuinely like to hear from both sides:

Hiring managers - what makes you say “yes”?

Candidates - what do you think interviews fail to measure?

I have been thinking about this lately, especially around the assessment quality checklist for campus Hiring.

A lot of discussion about this topic jumps straight to tools or processes, but i think the practical details matter more.

For example, I'd look at:

- Whether the process actually matches the role.

- Whether candidates get a fair chance to show they know

- weather the hiring team gets useful signal

- how much time does the process really save?

There probably isn't one approach that works for every company or role.

Would be interested in hiring what people have actually seen work in practice.

I’ve been thinking about this a lot lately.

Two candidates can have almost the same skills.

One gets nervous, takes a little longer to solve the problem and struggles to explain their thinking.

The other is confident, talks well and gets through the questions quickly.

Guess who usually gets the offer?

And that’s where technical hiring gets interesting.

A 45-minute interview can tell you a lot about someone but it can also miss a lot.

Someone might be an excellent engineer but terrible at interviews.

Someone else might be great at interviews but only average at the actual work.

So what should hiring teams really be measuring?

Technical knowledge?

Problem-solving?

Communication?

Actual work samples?

Or a mix of everything?

I’d genuinely like to hear from both sides:

Hiring managers - what makes you say “yes”?

Candidates - what do you think interviews fail to measure?

I was looking at some developer job openings recently and decided to check 10 of them properly.

Different companies, different job titles, different tech stacks.

But I kept seeing the same things:

1. DSA: Still comes up a lot, especially for fresher and entry-level roles.

2. Being good at one language: Most jobs weren't asking for 5–6 languages. They wanted people who were comfortable with at least one.

3. Git/GitHub: Pretty common requirement. Makes sense too, since most college projects involve working with others now.

4. Projects: Almost every role wanted some kind of practical experience. And I think having 2 good projects is better than putting 10 half-finished ones on your resume.

5. Communication: This one surprised me a little. A lot of job posts mentioned communication or working with a team.

The thing I realised while going through these:

I spent a lot of time trying to learn every new technology I came across.

But maybe that's not the best way to prepare for a job.Get good at the basics. Build a few things. Know your projects properly.

And be comfortable explaining what you did.

That's probably a better starting point.

For people applying right now - are you seeing the same requirements in the jobs you're applying to?

I used to think personal projects were always better for getting a job.

You have more time, you can build things properly, and you can add whatever you want.

Then I did a hackathon and changed my mind a bit.

In a hackathon, you have a deadline. Things break. You have to decide what’s actually worth building and what you should just leave out. If you’re working with a team, you also have to figure out who does what without wasting half the time.

My personal projects helped me learn coding and build things at my own pace.

Hackathons taught me how to actually get something working when you don't have much time.

Both have helped me in different ways when applying for jobs.

I’d probably recommend doing both if you get the chance.

I would be interested to hear what others found more useful for their job search.

I’ve been seeing a lot of discussions about candidates disappearing after interviews.

But I’m curious about the other side.

A candidate spends time applying, preparing, doing an assessment, taking interviews… and sometimes they just never hear back.

No rejection.

No update.

Nothing.

Then when a candidate stops replying, it’s called “ghosting.”

So where do you draw the line?

Is ghosting ever okay from either side?

Recruiters/hiring managers - what usually causes candidates to get dropped without an update?

Candidates - what’s the worst experience you’ve had with a company going completely silent?

Genuinely curious to hear both sides.

I still remember how seriously I took my first technical interview. I spent most of my time revising DSA going through questions, and trying to prepare for every possible thing they could ask.

Looking back, I probably spent too much time worrying about the questions and not enough time thinking about the actual interview.

So I am curious about everyone else's experience.

What's one thing you wish someone had told you before your first technical interview?

Could be something small - how to approach a question, what to do when you're stuck ?

It would be interesting to hear what you learned the hard way.

Trying to understand this from the recruiter/engineering manager side

Is it finding good candidates, screening hundreds of resumes, figuring out if someone actually has the skills they claim, or dealing with AI in interviews/takehomes?

I’ve been talking to a few people in tech hiring and everyone seems to have a different pain point.

For those actually hiring engineers, what part of the process is the biggest headache for u rn?

I'm just trying to understand where hiring gets messy

Been curious about what people here are actually building during challenges lately.

Did u try some new API? Use an AI tool for something? Build around a random service just to see what u could do with it?

Drop what u built and the tool/API you used. Doesn’t have to be some huge project either, even a small experiment counts.

Always interesting to see how differently ppl solve the same kind of problem.

What’s the most interesting thing u’ve built recently?

Been curious about what people here are actually building during challenges lately.

Did u try some new API? Use an AI tool for something? Build around a random service just to see what u could do with it?

Drop what u built and the tool/API you used. Doesn’t have to be some huge project either, even a small experiment counts.

Always interesting to see how differently ppl solve the same kind of problem.

What’s the most interesting thing u’ve built recently?

Been seeing more discussion around tech placements lately, and the prep seems to be changing quite a bit.

DSA is still important, but just grinding hundreds of questions doesn't really tell u how someone will perform on the job. Projects, debugging, problem solving and even how they use AI are becoming part of the picture too.

For hiring teams, this also makes the evaluation harder. A candidate can prepare for common questions, but it's much harder to fake how they approach an unfamiliar problem or explain a decision.

Do u think placements need to test more of that now?

One thing I’ve noticed is candidates can usually tell pretty early if a hiring process is well thought out.

Clear JD, knowing what the rounds look like, actually sticking to the timeline, even just replying when u said u would. Small stuff, but it matters.

And the opposite is true too. Vague role, surprise assessment, 2 weeks of silence... trust goes down pretty fast.

For recruiters here, what’s something your team started doing that made the process better for candidates?

Been noticing more teams using AI for parts of their technical interviews and tbh, I can see why.

Scheduling is easier, candidates dont have to wait days for the next round, and u can get through a lot more interviews without making recruiters spend their whole week on calls.

But I think the interesting part is getting the candidate experience right. The tech can work perfectly, but if the process feels confusing, ppl are gonna hate it.

For anyone who's been through one recently, what was it like?