I'm not really a huge fan of LeetCode style interviews. But, most of the big tech companies operate this way so I don't have much of a choice when interviewing candidates. I notice awhile ago my coding problems became seemingly less challenging all of a sudden. So, I plugged the question into ChatGPT and it sure enough it nailed it! Perfect answer. Remember to always talk through the problems in your interviews. It's more about your thought process then the actually problem. In this new AI era, problem solving skills and asking the right questions are more valuable then ever. #AI #interviewing #coding
How ChatGPT helped me ace LeetCode interview
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🌞 Happy Sunday! AI isn't just shaking up code—it's rewriting the rules of tech interviews! 🚀 From real-time coding suggestions to smarter preparation, candidates now have powerful copilots by their side. 💻 AI tools like GitHub Copilot & CodeWhisperer are being used to sharpen coding chops 🧠 Interview prep platforms now embed AI to simulate real interview environments 🔍 Recruiters are reevaluating assessments to focus more on logic and less on syntax 📈 Candidates using AI responsibly are leveling up faster than ever What’s your take on AI in coding interviews? Drop a comment or share your insights below! 💬 #AIAssistedCoding #TechInterviews #FutureOfWork
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🌞 Happy Sunday! AI isn't just shaking up code—it's rewriting the rules of tech interviews! 🚀 From real-time coding suggestions to smarter preparation, candidates now have powerful copilots by their side. 💻 AI tools like GitHub Copilot & CodeWhisperer are being used to sharpen coding chops 🧠 Interview prep platforms now embed AI to simulate real interview environments 🔍 Recruiters are reevaluating assessments to focus more on logic and less on syntax 📈 Candidates using AI responsibly are leveling up faster than ever What’s your take on AI in coding interviews? Drop a comment or share your insights below! 💬 #AIAssistedCoding #TechInterviews #FutureOfWork
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Follow-up: The “Code Debug Round” That Truly Opened My Eyes -> https://lnkd.in/gWwvGrDJ I believed I did well. Then the comments happened. And wow — many of you spotted issues I completely missed. 👏 It again made me reflect deeply on how should I approach code reviews. Here’s the complete issue list I uncovered — along with several important ones I initially missed but were caught by others. Bringing them all together here: 🔒 Concurrency, Transactions & Data Integrity Race condition Missing transaction management around debit/credit Credit limit check not actually enforced Incorrect comparison operator during balance validation 🔐 Authorization & Security isAdminAgent controlled by client — major security flaw Incorrect exception type thrown for authorization failures No audit trail for financial movements No rate limiting on sensitive operations ❌ Validation & Input Handling Using != instead of .equals() for String comparison No null-check for destinationAccount No validation when source and destination accounts are identical No input sanitization on request parameters 🧱 Architecture & Design Smells Business logic implemented directly inside controller Tight coupling between controller and service calls REST API semantic issues in the endpoint Weak random number generation for loan IDs - increases the chance of collision Missing static final when initializing the service objects Inconsistent null handling strategy Logger defined but never used 💬 Comments & Code Quality No proper logging message and error handling Exception message for null account is not helpful From now on, I’ll review every PR as if it were an interview question. Because good developers fix issues. But great developers spot them before they break. If this made you think differently about interviews — Share this post with your peers and challenge them to spot these issues too. #CodeReview #SystemDesign #SoftwareEngineering #CleanCode #CareerGrowth #Java #Interviews #DesignPatterns #BackendEngineering
The interview game just got tougher. 🚀 Some companies are replacing DSA rounds with Code Debug Rounds — and it’s catching everyone off guard. Here’s what happened in my recent interview with #Confidential Round 1 → Telephonic Call ✅ Standard culture fit, resume review, hybrid work discussion. Round 2 → Code Debug Round (Plot twist! 🎯) Instead of writing code, I had to review someone else’s. The goal? Find issues in: • Design Patterns • Performance bottlenecks • Runtime errors • Code improvements I caught around ~12... but missed a few critical ones. Result → Rejected. And here’s the kicker — At first glance, the code looked perfectly fine. After the interview, I even asked ChatGPT to analyze it — but it couldn’t catch all the issues either. 😅 Find the exact question they gave me 👇 Can you spot the issues or improvements in this code? Let’s see how many you can find. Drop your answers in the comments — I’ll share my detailed breakdown this weekend. PS: I have posted the solution of the code review here - https://shorturl.at/oJyNP #CodeReview #SystemDesign #SoftwareEngineering #Interviews #DesignPatterns #Java #CareerGrowth #LearnToCode
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Trying to decide if biggest problem for SWE Interviews is - they're mostly luck - they don't mirror reality On the side of luck: - Same algo question two days in a row - I got it right the second time. - For my "No AI Take Home", I used AI On the side of reality mismatch: - Algo questions optimize for infrastructure spend, but dev time is almost always more costly - On LeetCode there are pages of explanation for the "top" answers. But is your startups documentation up to date? - A software engineer's tools include AI, Logs, Slack, etc. yet I've never had to send a Slack in an interview Let me know your greatest interview luck, and the worst mismatch you see
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The interview game just got tougher. 🚀 Some companies are replacing DSA rounds with Code Debug Rounds — and it’s catching everyone off guard. Here’s what happened in my recent interview with #Confidential Round 1 → Telephonic Call ✅ Standard culture fit, resume review, hybrid work discussion. Round 2 → Code Debug Round (Plot twist! 🎯) Instead of writing code, I had to review someone else’s. The goal? Find issues in: • Design Patterns • Performance bottlenecks • Runtime errors • Code improvements I caught around ~12... but missed a few critical ones. Result → Rejected. And here’s the kicker — At first glance, the code looked perfectly fine. After the interview, I even asked ChatGPT to analyze it — but it couldn’t catch all the issues either. 😅 Find the exact question they gave me 👇 Can you spot the issues or improvements in this code? Let’s see how many you can find. Drop your answers in the comments — I’ll share my detailed breakdown this weekend. PS: I have posted the solution of the code review here - https://shorturl.at/oJyNP #CodeReview #SystemDesign #SoftwareEngineering #Interviews #DesignPatterns #Java #CareerGrowth #LearnToCode
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Recently, I watched a candidate's cursor move while his hands were in the air as they "solved" a fairly straightforward python problem. "I'm not using AI," he insisted. We both knew he was lying. This was one of the most bizarre interview sessions I've had and frankly, and I'm seeing more of it. It wasn't a deepfake or some wild story. I even told candidates during the interview process they could use ChatGPT to look things up. Just not to solve the problem directly. I wanted to explore how they thought and worked through problems. How many folks interviewing are seeing this - are we going back to in person interviews?
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🚨 If you’re prepping for big tech interviews… prep like it’s 2026. Meta just changed their entire strategy They’re piloting a new AI-assisted coding interview, where you’re expected to code with GPT-4o, Claude 3.5, or Llama 4 by your side. Here’s what you need to know: → It’s a 60-minute session where you extend, debug & build on a real multi-file codebase → You’re not solving LeetCode-style puzzles, you’re guiding AI, reviewing output, and making judgment calls → They want to see how you collaborate with AI, not how fast you can write binary search from scratch 🧠 The game has changed: You don’t just need to write code. You need to critique AI’s code, catch bugs, and reason through complexity. So if you’re prepping for big tech interviews… prep like it’s 2026. The AI isn’t replacing you, it’s your co-pilot. But you’re still the driver. #Tech #Career #AI
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🚨 The Interview Process Seriously Needs to Change Back in 2020, I was happily building projects — until some YouTube bhaiya said: “DSA is mandatory if you want to get into MNCs.” So yeah, I joined the grind. Solved 800+ problems across LeetCode, GFG, InterviewBit — what not. Fast forward five years later, interviewers still ask: “Number of islands?”, “Rotten oranges?”, “2-sum?”, “3-sum?” 💭 Solving 1000+ DSA problems doesn’t make any sense if we don’t know how real product building works. Built a lot of projects — and I never even got a chance to use a Number of Islands-type problem anywhere. Then comes the legendary one — “Find the non-repeating integer using only Java 8.” Bro, who wakes up thinking “Let me find this number but only with streams”? I mean seriously — who even cares whether you solve it using streams or not? And then the classics — “What is a functional interface?” or “How does HashMap work internally?” Are they taking an interview or hosting a quiz? 😭 In an AI-first world, where we’re building with Copilot, ChatGPT, and real-world tools — why are we still testing people like it’s 2015? Let’s flip it. How about this 👇 Call candidates to the office 9:30 AM – 6:30 PM, give them a real problem from your product. Let them use AI tools, talk to the team, ask doubts, and build something end-to-end. You’ll instantly see — how they collaborate, how they think, their patience, ownership, curiosity, and their actual passion for building. And for the candidate — they’ll understand the company culture, see how the team builds and interacts, and get real insight into how products are actually made. Even if they don’t get selected, they’ll walk away learning something real No regrets. No rejections for “not knowing Java 8 features.” Just a productive, learning-driven day. Let’s stop judging talent by quiz. Let’s start hiring by how people build, how they think, and how they grow. Let’s hire people who are upskilling themselves every day. Let’s hire engineers — not just developers. What’s your take on this kind of interview process? #interviews #techhiring #developers #career #growthmindset
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It’s been interesting to watch how the approach to technical interviews has been shifting. Back when ChatGPT first appeared, a lot of tech leads and engineering managers were busy redesigning interview processes to catch candidates who relied on LLMs for answers or coding. And sometimes it wasn’t easy — strong candidates had their tricks as well. But now the situation is different. A developer who knows how to use AI coding assistants properly can build things noticeably faster. So the real challenge has become: how do you identify these people during interviews? Everyone will say they “use Cursor” or “work with Copilot,” but only a fraction actually use them effectively. Curious to hear how your companies approach this today. How do you evaluate it in your hiring process?
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Excited to share my project — PrepBot: Smart Interview Simulator! Link: https://lnkd.in/gPpHfuRQ PrepBot is an AI-powered platform designed to help users practice and prepare for interviews in a realistic, chat-based environment. It simulates both technical and HR interviews, evaluates responses, and provides instant feedback with improvement tips. This project aims to make interview preparation smarter, interactive, and more personalized — helping candidates boost their confidence and communication skills before facing real interviews. #AI #ArtificialIntelligence #InterviewPreparation #TechInnovation #Project #PrepBot #MachineLearning #SoftwareDevelopment #WebDevelopment #ReactJS #NextJS #OpenAI #Coding #Developer #Innovation #Technology #CareerGrowth #Learning #TechProject
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Principal Engineer @ Boltive | Technical Vision, Technical Leadership
5dLately I have been having the candidate use ai to solve a mid complexity problem in a real framework in real time. Do they know how to prompt for the right outcome? Do they select the right model, and reprompt when the answer is sub optimal? Do they understand enough context to plug in the results and make it run? We then pivot to cicd and deployment questions and database scaling questions based on the initial work. This seems to work well, be hard to cheat, and reflect real world skills.