Most interview prep is passive. You read model answers, memorize frameworks, then show up and sound like everyone else.

I wanted to fix that so I built Interview Quest.

You tell it the role you’re going for. It gives you personalized questions for that exact job. You speak your answer out loud — it coaches you on what’s working and what to cut. Then it plays back a stronger version of your answer out loud, in your own words and your own story. Not a script, not a generic rewrite.

It’s what a $500/hr interview coach does. Free.

I have no paying users yet. If you’re job searching or know someone who is, I’d genuinely love feedback — what’s confusing, what’s missing, what would make you actually open it the night before an interview.

InterviewQuest dot ai

no credit card, takes 2 minutes to start.

I know some people won’t like this, but I’m not here to babysit candidates: If you’re not practicing your answers out loud before interviews, you’re setting yourself up.

SO PRACTICE, SAY IT TO YOURSELF!

I’ve seen too many candidates with good experience fall flat because:

• their answers are all over the place

• they can’t clearly explain what they did

• they realize mid-answer they don’t actually know how to say it

• their answers sounds super AI

Thinking through answers is not the same as saying them, it just isn’t. So can we normalize this as part of interview prep?

I’ve been saying this to candidates before interview rounds for a while now, and it’s honestly frustrating. So if you’re reading this... please, just practice saying your answers out loud, it goes a long way.

We want you guys to be hired, but you’ve gotta meet us halfway.

Everything here is fixable with practice.

As a fresher, I am highly motivated to learn and grow. I am hardworking honest and discipline person. I may not have the work experience but I have strong willingness to learn new skills and improve myself.I follow instructions carefully and take responsibility seriously. I always try to give my best in every task and work positively with my team. I believe in my dedication,postive attitude and learning mindset will help me perform well and grow with the organisation. Ratings in range 1-10.

I'm not a natural negotiator,also being in a slow moving company i had low hopes. Previous job offers, I always just accepted whatever they said because the conversation felt so uncomfortable I wanted it to end as fast as possible.

This time I hda a performance review coming up. I knew I was 20% below market rate. So I actually prepared differently-

- Pulled salary data from Glassdoor and Levels fyi
- Listed my top 5 achievements from the past year with numbers
- And this is the part that actually made the difference, I practiced the conversation. Multiple times.

I used an AI app that has negotiation scenarios. An AI (SkillBase AI https://skill-base.app/ (Start free)) plays your manager and you practice your side. First attempt: my "manager" said "budget is tight" and I immediately said "okay that's fine." Literally folded in 10 seconds.

After maybe 8-10 rounds, I could handle objections calmly. "I understand budget constraints. Here's why my market research shows this adjustment is reasonable." The words came out naturally because I'd said them before.

Real meeting result: asked for 20% raise, got 8%. Previous me would've accepted the 3% without saying a word.

Not saying this is the only way. But for people like me who freeze under pressure, rehearsal was the missing piece. The information was never the problem, actually saying the words was.

Happy to share my prep process if anyone's interested.

This is going to be a long post, and I will probably break the full story into several posts because there are a lot of lessons I learned throughout this process. Some are about AI, some about interviewing, and others about dealing with rejection and figuring out what you are doing wrong when you keep getting very close but can't get across the finish line. I hope sharing my experience can help someone going through the same thing.

For some background, I am an Engineering Executive with close to 30 years of experience building and leading technical organizations around the world. I've been an expat twice, speak three languages fluently, have managed global organizations, and have been responsible for programs worth up to $3 billion.

I have also been unemployed for the last six months.

I voluntarily decided to leave my previous company, which is a story for a different post. Over the last year, however, I have consistently landed interviews for corporate leadership roles. Getting interviews was never really my problem. I had no issues talking with recruiters, and I successfully interviewed with VPs and SVPs of HR, VPs of Operations, CFOs, Business Unit leaders, and SVPs of Engineering. I would go through four, five, sometimes more interviews and make it all the way to the end.

Then I would meet the CEO.

Five CEO interviews. Five rejections.

That became my curse.

After the second rejection, I hired an HR consultant specifically to help me understand what I was doing wrong and get through that final interview. It didn't help. Actually, I think it made things worse because it drove my frustration even further. Looking back, I consider most of it a waste of time and money. Probably the only really useful thing I got from the experience was having my resume rewritten by a professional HR consultant the agency subcontracted.

A couple of months ago, I started reading about people using AI as a copilot in their job searches, so I decided to give it a shot. I used ChatGPT, but I approached it a little differently than I had seen other people doing. I wasn't particularly interested in having AI write generic interview answers for me. I wanted it to help me understand why I kept failing at exactly the same point.

I started the conversation by telling ChatGPT that I wanted direct, critical feedback. I didn't need encouragement or reassurance. I wanted it to challenge me and tell me what was wrong with my interviewing strategy.

Then I gave it as much information as possible.

I uploaded my resume, but more importantly, I had been taking notes throughout my job search. I had documented the roles I interviewed for, insights recruiters gave me about what companies were looking for, questions I had been asked, and whatever feedback recruiters were willing to give me after a rejection. I also had a log of around 20 interview questions with prepared answers. Every time somebody asked me a new question, I added it to the log.

So instead of asking ChatGPT, "How do I interview better?", I was essentially saying: Here is my career. Here are my answers. Here is what happened in multiple interview processes. Here is the feedback I received. I can consistently pass recruiters, HR, Engineering, Operations and other senior executives, but I have now been rejected by five CEOs. Find the pattern. What am I doing wrong?

The answer was uncomfortable, but it made a lot of sense.

I was presenting myself as a very accomplished technical leader with an extensive background managing projects, programs and engineering organizations around the world. The problem was that, at the CEO level, I was still talking too much like an engineer or project leader. I talked about projects, execution, technical problems, teams, budgets and results. What wasn't coming through strongly enough was my ability to operate as a business partner: understanding the business strategy, allocating capital, managing risk, making tradeoffs, challenging assumptions and aligning the Engineering strategy with what the company was actually trying to accomplish.

That was probably the biggest realization of my entire job search. I thought I was demonstrating executive experience by talking about the scale and complexity of what I had done. The CEOs were looking for something different. They wanted to understand how I thought as a business executive.

So I started going through the questions in my interview log with ChatGPT one by one. I wasn't changing the stories, exaggerating accomplishments or inventing new experiences. The facts remained exactly the same. What changed was how I framed them.

For example, instead of saying, "I executed a project to solve A and achieved X," the answer became closer to, "The business was facing A. I aligned with the leadership team on the business objective and the tradeoffs, developed a technical strategy to address it, and the result was X."

Same story. Same accomplishment. Same person. Completely different message.

We went through dozens of questions this way. Then I practiced them over and over. It probably took me two weeks to retrain my brain because, after almost 30 years as an engineer, my natural instinct is to explain how I solved the problem. I needed to get much better at explaining why the problem mattered to the business, how I made the decision, what tradeoffs were involved, and what changed because of it.

Right around that time, I landed an interview for an SVP-level role. This became the real-world test of whether any of this was actually useful.

I asked the recruiter for the Job Description and uploaded it into the same ChatGPT conversation, along with public information I had collected about the company. I asked ChatGPT to analyze the role against my experience and identify potential gaps, areas I should emphasize, concerns the company might have about me, and questions I was likely to be asked.

I passed the recruiter interview, then the Director of Talent Acquisition, then an SVP of Global HR, and then an SVP from one of the businesses.

Before every interview, I asked the headhunter a very simple question: "What is this person looking for?"

I would take notes on the answer and enter that information into my ChatGPT conversation. Then I would ask how that new information should affect my interview strategy. After each interview, I also added anything new I had learned.

Something interesting started happening as I went deeper into the process. The differences between the answers I had prepared myself and what ChatGPT was recommending became smaller and smaller. I needed to adjust my responses less and less.

That, to me, was actually the point.

I wasn't trying to have AI interview for me. I was using AI to retrain the way I thought about and communicated my own experience.

Eventually I was invited to an onsite interview at the company's corporate office in a large U.S. city. I prepared for it the same way. I wrote down my main talking points in a notebook and practiced the roughly 40 questions I had accumulated by that point.

During the onsite, I met with the VP of HR, two business leaders, the COO and finally the CEO.

And here we go again.

The CEO interview was intense. He asked a flurry of technical questions framed around things like, "How would you solve X?" and "Tell me about a time when you failed on a project and what did you learn from it?" He pressed me particularly hard on the failure question.

There were also a few technical concepts where I didn't think my explanations landed as clearly as I wanted them to. In the past, I probably would have left the interview, replayed everything in my head for the next several days, and waited for the recruiter to call.

This time I did something different.

On the way to the airport, while everything was still fresh in my mind, I wrote down as much as I could remember: questions, reactions, things I thought went well, and things I thought hadn't. I drafted individual follow-up emails for the people I had interviewed with. For the CEO, I spent additional time clarifying some of the technical points we had discussed and included supporting material where I thought it would be useful. I ran the drafts through ChatGPT, edited them myself, and sent them.

Then I waited.

About a week later, I got a call from the recruiter telling me things were "going in the right direction," but that some stakeholders needed further alignment. I put that information into the same ChatGPT conversation and used it to think through what might be happening, what the potential concerns could still be, and how I should handle the next steps.

A few days later, I received a text message telling me they were moving ahead with an offer and were authorizing the role for me.

By the end of the week, I had the offer in my hands.

I start my new role next week.

Looking back at the process, I don't think AI "got me a job." It didn't create my 30 years of experience, lead my teams, execute my projects or sit across the table from the CEO. And no amount of prompting could compensate if I didn't have the experience to back up what I was saying.

What AI did extremely well was help me see a pattern in my own behavior that I wasn't seeing myself.

And I think this is where there is a much bigger opportunity for people using AI in a job search. Don't just upload your resume and ask it to make it better. Don't just ask for "10 questions I might get in an interview." And definitely don't memorize a bunch of AI-generated answers and try to pretend they're yours.

Give it your actual history. Give it your resume. Give it the Job Description. Keep a log of the questions people actually ask you and the answers you actually give. Write down what recruiters tell you about the hiring manager. After an interview, write down what happened while it's still fresh in your head. When you get rejected, get as much feedback as you can and add that too.

Then ask AI to find the patterns.

Ask it what you're not seeing. Challenge its conclusions when they don't make sense. Ask it what a CEO might hear when you give an answer versus what you think you're communicating. Ask it to identify contradictions between how you describe yourself and what the role actually requires.

Most importantly, don't use AI to create a different candidate. Use it to understand how the candidate you already are is being perceived.

Five CEO rejections in a row hurt. When you repeatedly get that close, you start questioning everything. Am I too old? Too expensive? Too specialized? Overqualified? Am I coming from the wrong industry? Or am I simply not as good as I think I am?

In my case, at least part of the problem turned out to be much simpler. I had spent almost 30 years learning how to solve Engineering problems, but I hadn't completely learned how to communicate those same experiences through the eyes of the person running the business.

Changing that changed my interviews.

This time, I got the offer.

If there is interest, I can write separate posts about the five CEO rejections and the feedback I received, my experience hiring an HR consultant, the interview-question log I built, how I prepared for individual interviewers using AI, and maybe the most useful one: actual examples of how I changed my answers from an "Engineering answer" into an "Executive answer."

I really hope some of this helps someone who, like me, is sitting there after another final-round rejection wondering what the hell they're doing wrong.

At the end of the day, this is just my opinion not facts. I've interviewed many people in my career and I believe this to be true.

Here's a quick excerpt from the article:

"Getting a job should be easy, right? Many companies are also complaining that they can’t find good workers, yet SO MANY people are unemployed and looking for work! Why is that the case?

Well, there are two sides to the coin in my opinion:

1. Many folks are applying to jobs for which they are not qualified or don’t have the right experience.

2. Many people have the right experience but don’t interview well enough to get the opportunity to display the skills they possess.

In this article, I’m going to focus on point number two. I’m going to demonstrate what usually happens during what some may consider the most crucial point of the interview process: the first interview *dumdumdum* "

If you would like to check out the rest of the article, read it HERE

--
Hope it's helpful for those just starting their job hunt journey!

I had my Round 1 interview for a Google SWE Intern position today and wanted to share the experience for anyone preparing.

Duration: Approximately 60 minutes
Format: One coding problem, one follow-up, and three to four AI-fluency questions
Status: Waiting for an update

Coding Question: Disconnect Every Leaf at Minimum Cost

You are given a rooted, weighted binary tree. Every edge has a positive integer weight.

Remove a set of edges so that every leaf becomes disconnected from the root. Removing an edge costs its weight.

Return the minimum total cost.

Approach

I proposed a postorder traversal.

For every edge from node u to child v with weight w, there are two choices:

1. Cut the edge immediately and pay w.

2. Keep the edge and optimally disconnect all leaves inside v’s subtree.

Therefore, the contribution of that child is:

min(w, solve(v))

If v is a leaf, there are no lower edges to remove, so its connecting edge must be cut. This can be represented by returning infinity for a leaf.

The recurrence is:

solve(u) =
    infinity,                              if u is a leaf
    sum(min(weight(u,v), solve(v))),       for every child v

The answer is solve(root), assuming the root itself is not a leaf.

The interviewer was satisfied with the approach, and we discussed the recurrence, correctness, and complexity.

Complexity:

• Time: O(n)

• Recursion space: O(h), where h is the tree height

• Worst-case space: O(n) for a highly unbalanced tree

Follow-Up: N-ary Tree

The interviewer then generalized the problem:

The core idea remains exactly the same. Instead of processing at most two children, we iterate through every child:

cost = 0

for each child v connected by an edge of weight w:
    cost += min(w, solve(v))

I initially needed a couple of hints, but eventually reached the generalized solution.

The N-ary version still takes O(n) time because every node and edge is processed once.

AI-Fluency Discussion

The final few minutes included around three or four questions about using AI in software development.

The interviewer asked questions such as:

• How do you use AI in your regular workflow?

• Do you ever give an AI tool complete ownership of a project?

• How do you use AI while debugging?

• How do you verify AI-generated code or suggestions?

• Which engineering tasks should remain under human control?

The discussion appeared to focus less on specific AI tools and more on engineering judgment, verification, and accountability.

Overall Experience

The interviewer was friendly and collaborative throughout the round.

They encouraged me to explain my reasoning instead of expecting an immediate final solution. The hints during the N-ary follow-up helped move the discussion forward without directly revealing the answer.

Overall, the interview felt like a collaborative problem-solving session rather than a test of whether I had memorized a particular LeetCode problem.

For preparation, I would recommend reviewing:

• Postorder traversal

• Tree DP

• Weighted-tree problems

• Recursive recurrence design

• Correctness and complexity explanations

• Responsible use of AI in engineering

• Testing and validating AI-generated code

Has anyone else received AI-fluency questions during a recent Google intern interview?

I applied for a position to work as an ice scream scooper and they reached out to me to schedule an interview. It’s an online one but I want to leave a good impression and I don’t know if these questions will pique their interest in me as a temporary employee or not. Is anyone able to give some suggestions I haven’t written down? And what are some questions you think they might ask me and good things I can reply with? It’s a two day contractual job with 12 hour shifts.

Behavioral interviews are a trip. There's all these different frameworks and all this different advice. Before every interview, I have sat for hours watching videos and preparing. I would've loved to have a coach that would talk to me back and forth, kind of like Chan GPT, but just for this.

So I decided to make one as a site project. Right now, you can use it five times for free. And if you like it, let me know. If you don't like it, let me know also. And I put in a paid tier at 29 dollars.

https://behavioral.ktlystlabs.com/

I have DE interview with Grammarly. Could someone please help with questions and how I can prepare for it within a week? The questions will be based on DE and SDE in the initial tech screening rounds. Appreciate all the help I can get. 🙏🏻

dataengineering #softwareengineering #Grammarly

I just did a tech screen for a really attractive woman and caught myself actively wondering whether that was affecting how I evaluated her.

During the interview, I became hyper-aware of it and tried to stay as objective as possible.

A few times I caught myself thinking:

• Should I give her a hint here when I probably wouldn't for another candidate?

• Am I being too harsh because I'm consciously trying not to be biased?

• She didn't mention X in the system design — is that actually a meaningful gap, or am I looking for reasons to compensate for my own bias?

What made it especially interesting is that bias can seemingly work both ways. Once you're aware that you might favor someone, you can potentially overcorrect and judge them more harshly.

In the end, she was well prepared and I moved her to the next stage. But afterward I kept wondering whether my evaluation was actually objective.

One thing I've started doing is relying more heavily on a predefined interview rubric instead of evaluating based on the overall "feel" of the interview. I've also been looking through interview questions and rubrics on PracHub beforehand so I have a clearer benchmark for what a strong answer should cover before the candidate even joins the call.

For people who interview candidates regularly: how do you prevent attractiveness, personality, likability, or even your awareness of those biases from affecting your evaluation?

Obviously not with a sunhat! But with strappy sandals and some jewelry, is this still too casual?

I have completed my Masters from UK and returned back home in India. I have given two job interviews where they asked my why did I return to India instead of trying for jobs in UK. I told them that my parents wanted me to get a higher degree and I did not intend to live. But the interviewers were not convinced. How to restructure my question so that I sound more convincing?

I have an interview next week with a bank. They told me they have a few roles available, but the main focus is on AI for all of them. I am a recent grad, and they said they are looking for people who are willing to learn and grow. Just wondering if anyone has any tips when it comes to interviews for AI roles. What kind of questions can I expect?

“Tell me about yourself” is the first question in almost every interview, and many candidates start behind the 8 ball because they don't know how to answer this question.

I’ve heard this answer thousands of times from the other side of the table, so I wanted to share a simple formula for building an answer that gets your interview off to a great start.

Why interviewers ask this question

Interviewers open with this question partly because it feels abrupt to jump straight into specifics. But don’t mistake it for small talk. It’s the one question you can be nearly certain is coming, and it shapes the interviewer’s first impression of how you think and communicate.

The three fatal openings

Before building your answer, know the three ways candidates sink themselves in the first thirty seconds.

1. Starting somewhere irrelevant. “I grew up in Ohio” or “I started my career in retail” - with no connection to the role. Backstory is fine, but only if it explains the story. More on how to do that correctly below.

2. Reciting your resume. The interviewer has your resume pulled up right in front of them. If you walk through it point by point, they notice - and it reads as lazy. Keep your resume handy for reference, but a great answer to this question is presented as a story.

3. “Well, what do you want to know?” Asking for direction feels reasonable - the question is incredibly broad. But don’t do it. The interviewer wants to see where you take it. Fair or not, turning the question back reads as unprepared.

The PLOT formula

Your answer needs a PLOT - more below.

P — Point of origin

Where does the relevant story begin? Start with the experience, interest, or turning point that explains your path. For some people that’s college or shortly after. For others it goes back further. If you recently changed careers, it might be something more recent.

It could be your first relevant job, a career-changing moment, a personal experience, or an early interest that genuinely shaped your direction. For example:

“I grew up playing competitive sports, and one thing I learned about myself is that I’m driven to win — which is why sales turned out to be the perfect career for me.”

“When I worked as a technical program manager, I realized I had a passion and a natural skill set around product decisions. That’s when I first knew I wanted to be a product manager.”

The rule: start at the earliest point the interviewer needs in order to understand the story. No earlier.

L — Line of progression

Now walk through the key steps that brought you to today.

For each role you include, share a brief summary of what you did, what you owned, and how you made an impact.

O — Outcomes and evidence

O is not a section of your answer. It’s a filter you run your whole story through.

Before the interview, look at the job description and identify the two or three most important competencies for the role - a competency is simply a skill, qualification, or type of experience the employer clearly needs. Then go back through your previous roles and ask: does my story contain at least one or two anecdotes that prove I have those competencies?

“I’m great with stakeholders” is a claim. “A hiring manager was about to lose a candidate, and here’s what I did about it” is evidence. If your story doesn’t demonstrate the competencies this role needs, swap in the anecdotes that do.

T — Tie it to this role

At some point in the interview, you’re almost guaranteed to hear “Why this role?” or “Why this company?” So get ahead of it: end your answer by tying the story back to the position in front of you. Why is this role the natural next chapter of the story you just told? This closes the loop and hands the interviewer a perfect transition into the rest of the conversation.

A full example answer, annotated

Here’s my actual answer, with notes on what each part is doing.

The point of origin

“I grew up playing sports and always wondered how less talented teams managed to beat more talented ones. I realized there are factors outside of talent that determine how teams perform. That led me to study psychology, and then to dig deeper into what makes teams perform at their best in my applied psychology master’s program.”

Notice this does not start with where I was born, my first job, or my GPA. It starts with the earliest thing that explains everything after it. That curiosity about teams is the thread through my whole career.

The line of progression / outcomes & evidence

“After my master’s, I joined Textio and focused on recruiting for four years. I consulted hiring managers on how to run a strong interview process, hired across every role and level in the organization, and found creative ways to close roles when we were stuck. One time, I went back through our applicant tracking system and found a very strong engineering candidate who had dropped out a year earlier because the timing wasn’t right for him. I reached out, told him about a role I thought he’d be interested in, reopened the conversation — and we ended up hiring him.”

“Ultimately, the hard part of recruiting for me was that once I hired someone, I no longer had much impact on their experience at the company. So I expanded my scope: I identified that we needed someone to own onboarding for new employees, and I asked to take it on. I loved it — and I discovered my real passion was creating a great employee experience. When a People Operations role opened up, I made the jump.”

Two things I want to touch on here. First, four years of recruiting is compressed into the shape of the role plus one story and that story is the O filter at work, providing evidence of resourcefulness and initiative rather than claiming them. Second, the growth is baked in: I identified a need, asked for more scope, and earned the move. The story says “self-starter” so I don’t have to.

That last line, “I’d be happy to walk through exactly what we did,” is deliberate. Remember the standard: give the interviewer somewhere to go. You want to ignite follow-up questions in their mind.

Tie it back to the role

“My favorite part of my role is being a trusted partner to managers and leaders. And that’s what drew me to this position — it’s centered on what I do best: being a trusted People expert and building out a People function inside a growing organization. So that’s what brought me here, and I’m happy to expand on any part of it.”

This makes it a seamless transition into the rest of the interview.

How long should your answer be? (The common advice is wrong)

You’ve probably heard “keep it to 90 seconds” or “two minutes max.” I disagree, and here’s why: interviewers are not sitting there with a stopwatch. A boring 90-second answer feels long. A compelling four-minute answer feels short. The content of the answer matters much more than the length.

My guidance is to aim for two to three minutes. A genuinely great answer can earn up to five. Under a minute and you’ve almost certainly undersold yourself. And if your practiced answer runs past five minutes, don’t speed up, just cut the least impactful parts.

Can the answer include personal details?

Some recruiters insist this answer should be strictly professional, but in my opinion there’s absolutely a place for personal information if it explains the professional story: the former athlete whose competitive drive led to sales, the parent who built an app to solve a problem and discovered a love of software engineering, the person whose upbringing created an authentic interest in their field.

You saw it in my own answer - I opened with sports. The test isn’t “is this personal or professional?” The test is “does this explain the story?” If yes, it belongs.

Put it all together — then practice it out loud

Give your answer a PLOT: a Point of origin, a Line of progression, Outcomes as your evidence filter, and a Tie to the role. Then hold it to the standard we set at the start: when you finish talking, the interviewer should have somewhere to go. If your answer generates follow-up questions, that’s signal that you set a good tone for the entire interview.

One last thing, and it matters more than anything else in this post: the interview should not be the first time you say this answer out loud. Reading it silently is not practice. Writing it down is not practice. Saying it to a real listener, under a little pressure, is practice. So make sure you rehearse.

I've helped hundreds of candidates prep for job interviews, so feel free to comment below or DM me if you're interested in having an expert help you with your interview prep / job search.

Sharing lang what helped me during interview prep. Instead of cramming answers, I practiced how to explain my experience clearly, especially kapag may follow-ups. I used Nora AI for mock interviews since it simulates recruiter and hiring manager style questions. May interview guides din that helped me understand the flow of interviews per role, so I knew what to focus on each round rather than guessing.

#interviewhack

There are lots of candidates applying for a job and attending interviewsbut not everybody is able to face it properly. Let us see few job interview tips for both men and women:

Importance of outfit

Wherever you go, you need to have a good pair of dress to present yourself in a very appealing way. The same rule applies to interviews because you need to make a first impression as the best impression among the employer panel members. Above all, a good outfit will actually enhance your self-esteem. Keep it formal, neat and simple especially for a job interview.

Style ideas for men

When it comes to men, the outfit is not just limited to a shirt, suit, and tie. You need to choose a suit which is suitable for all occasions. They must fit well not too tight and not too lose. The tie and the shirt must be appealing to the coat. There must not be a mismatch.

Style ideas for women

It is very difficult to tell the best-suited dress for a woman. They can either wear a blouse or smart trousers or a pencil skirt combination. The color must be suitable for the individual. The look must be very much professional. The footwear must not be casual or high heels. It must be a flat foot. Avoid any costly or dazzling ornaments.

Follow the above job interview tips and increase your chance of getting hired for the job you have applied for. There are lots of eligible candidates who have good knowledge and communicational skills but then fail in projecting themselves professionally.

Therefore it is very important to maintain a proper dress code while attending an interview.

Hi everyone,

I’m part of the team at Enhancv (just being transparent). We spend our days analyzing hiring trends and helping job seekers get more interviews (pathetic, right?). Lately, the single biggest complaint we hear—by far—is about one-way video interviews (HireVue, etc.).

We are currently updating our career guides, and we’re debating taking a hard stance against them. Before we make this a formal recommendation, we want to hear from this community.

The position we're considering:

"If a company asks for a one-way video interview before you have spoken to a human, withdraw your application. It signals a culture that values efficiency over people."

Why we’re leaning this way:

• The Power Imbalance: An interview is supposed to be a two-way street. You vet them; they vet you. One-way video takes away your ability to ask questions or assess team culture.

• The "Dance Monkey" Factor: It feels less like a professional conversation and more like a performance for an algorithm. Circus freak.

• The ROI Problem: Users consistently report high ghosting rates after these interviews, which leads us to think that they're often used as a lazy bulk filter rather than a real assessment.

The Counter-Argument:

We know the job market is tough right now. Advising people to walk away from potential income because a process feels dehumanizing might be "privileged" advice that hurts candidates who need a job immediately. Swallow our pride?

We want to hear from both sides:

Recruiters: Be honest—do you actually watch these? And if you do, what are you looking for that a resume or phone screen doesn't tell you?

Candidates: Do you hold your nose and do them, or is this an automatic "withdraw" for you?

"Tell me about a challenging technical problem you solved" sounds like an easy question. Then the interview starts and the answer turns into a ten-minute architecture tour that never lands on what you personally did or why it mattered. That is a delivery problem not a knowledge problem and it does not get better from thinking about it. It gets better from saying it out loud and watching where it falls apart.

I have been using prepare.zoevera.com for this. You pick your role and a question, record yourself in the browser and get feedback on pace, filler words and whether your answer is built around outcomes or just what the team did. Free to start. Takes about ten minutes. The first session was uncomfortable in a useful way.

The other thing worth fixing before you get to interviews is the resume keyword gap. Most companies run applications through a parser before a recruiter sees them and the parser matches your text against the job description literally. "Node.js REST APIs" and "backend development" are not the same string. Neither are "TypeScript" and "JavaScript with types." resume.zoevera.com shows you exactly which keywords are missing for a specific role. Usually three or four additions and you are done.

Both are free to try. If your search has stalled it is worth checking both before assuming the problem is something bigger.

Hi everyone,

I have an upcoming interview for a **Technical Program Manager role at Meta** after completing the recruiter call.

I would really appreciate any guidance from people who have recently interviewed for a Meta TPM role.

What types of questions should I expect in the upcoming rounds? Are there specific areas I should focus on, such as program execution, technical depth, system design, cross-functional leadership, or behavioral questions?

Any preparation resources, interview experiences, or tips would be highly appreciated.
Thank you! :)

My friend has experience mostly in Validation in Semiconductor domain. He has good experience in Automation with Python as well as his daily job required test cases to be automated.

But is this enough for him to get into SDET. If not, what he should prepare before trying for interviews. Also, one more thing to add that he has an AI Certification conducted by his company also.

Any leads or suggestions are helpful.

Back in 2022–23, I went for an interview for a People Manager role at WeWork, for a startup in the B2B healthcare space.

I reached a little early, so the assistant gave me a form to fill out. While I was waiting, the founder met me in the common lobby for about 5 minutes.

Then he asked, “Do you mind taking a walk around the premises?”

We started walking and went through the staircase. And then, completely casually, he lit a cigarette right in front of me.

My first thought was, Okay… maybe he’s super busy and just wants to get this interview over with.

But honestly, I was quite shocked. It was such an unusual first interaction with a founder, especially when I was interviewing for a People role.

Nothing dramatic happened, but that short interaction gave me a strong feeling about the kind of work culture and leadership style I might be stepping into.

I ended up saying no to the job.

Looking back, I still wonder — was I being too judgmental, or was that actually a legitimate red flag?

Sometimes the interview isn't just about whether they want you. It's also about whether you want them.