Avoiding Overcomplication in Coding Interviews

After taking 75 Software Engineer interviews at Google in < 7 months, I’ve seen a range of mistakes all of us make in coding interviews. Here’s a compiled list to help you (and me) avoid these pitfalls in our future interviews! 1️⃣ Not Clarifying Requirements > Many candidates jump straight into coding. Often without fully understanding the problem. This can waste time and lead to errors. Tip: Always ask clarifying questions. To ensure you get the requirements. Confirm edge cases and input constraints early on. 2️⃣ Overcomplicating Solutions > In the heat of the moment, it is easy to overthink a problem. And this complicates the solution, both for you and your interviewer. Tip: Start with a brute-force approach (just explain it), then iterate towards optimization (code it up). Easy-to-understand solutions get bonus points. 3️⃣ Under-Communication > Interviews are not just about coding. They’re also about conveying your thought process. Silence takes away the only help you have during the interview—your interviewer. Tip: Think out loud! Explain your reasoning and approach as you code. This helps the interviewers understand you and even guide you if needed. 4️⃣ Ignoring Edge Cases > Many candidates create a working solution. But fail to consider edge cases. This can lead to catastrophic failures. Tip: After arriving at a solution, always discuss potential edge cases. Explain how your code handles them. This shows your thoroughness. 5️⃣ Neglecting to Optimize > Even if your solution works, failing to consider optimization can cost you points. Tip: After solving the problem, re-read your solution and discuss ways to improve time and space complexity. No micro-optimizations. Interviewers appreciate candidates who think about efficiency in big-oh notation. 6️⃣ Skipping Dry Runs > 80%+ candidates skip the dry run of their code, leading to overlooked mistakes. Tip: Walk through your code with sample inputs. This helps catch errors early and makes you look proactive. 7️⃣ Getting Flustered > Interviews are stressful. And it is easy to panic if you hit a roadblock. Tip: If you’re stuck, ask for a minute or 2 to gather your thoughts. Ask for hints if necessary—interviewers appreciate candidates who are willing to seek help. Those were my 2 cents on how to tackle coding interviews. But believe it or not, the best way to realize your interview mistakes would be to start taking interviews (even mock ones). After conducting so many interviews at Google, I realized how I often fell into the same traps as everyone. Like going completely silent or forgetting to do a dry run for the interviewer. Taking interviews altered my perspective, and now I advise everyone preparing for interviews to take a couple of them first. Total game changer! #codingInterviews #jobPrep #softwareEngineering #Google #interviewTips

I interview 2 Senior / Staff Engineers at Meta every week for E5 and above roles. If they asked me how to perform better in coding interviews, I would start with these 3 things. These are people with 8, 10, 15 years of experience. 1. Treat the interview like a joint problem-solving session When I ask an algo question, I want to hear your thought process from the first minute. Start wide, then narrow: - First: state the brute force   If I do this in the simplest way, I would:   a) scan all elements,   b) try all pairs or all paths,   c) this gives time O(N²) and space O(N²). - Second: show that you respect constraints   Now, if N is 10⁵, O(N²) will not work. So I will look for something closer to O(N log N) or O(N). - Third: propose concrete options   Option 1: sort and scan with two pointers, complexity X.   Option 2: use a HashMap and one pass, complexity Y. Then ask: Given these options, which path would you prefer I implement first This does a few important things: - It shows you understand trade-offs, not only syntax. - It gives me a chance to correct your direction early. -  It proves you are not guessing. If your first solution is not optimal and I ask for a better one, keep the same structure: offer two ways to improve, sketch pseudocode, confirm the choice, then code. 2. Enunciate while you code One of the hardest interviews to conduct is when the candidate goes silent and types for 20 minutes. As an interviewer, I am sitting there thinking: - Are they stuck - Are they copying a pattern from memory - Do they even know what this line is doing You can fix this just by speaking while you code. Example of what I want to hear: - I am creating this array to store prefix sums. - This loop walks the list once and builds the map from value to index. - This condition picks the earliest valid index for the answer. Now I do not have to reverse engineer your solution. I can follow your logic in real time. I know you understand your code. You also get an extra benefit: if you say something and your code does something else, you will catch that mismatch yourself. Strong communication here is not about fancy English. You can speak in simple language as long as the mental model is clear. 3. Dry run your code Too many candidates write the final line and look up, waiting for a verdict. A much better move is to verify your own work: - Take the example input from the problem. - Feed it through your code step by step. - Say out loud what each variable holds after each key step. For example: - After the first iteration, the stack contains these indices. - Here we update the answer from 3 to 5 because the condition is true. - At the end of the loop, we return 5, which matches the expected output. Two good things happen: - You often find your own typos, off by one error or edge cases. - You show that testing and verification are part of how you think, not an afterthought.

After giving & conducting 100+ coding interviews over the past 12+ years at startups and MAANG+ companies, I’ve realized one thing: —Interviews aren’t about who writes the most code. —they’re about who thinks in the most structured way. Here are 30 key insights I’ve learned from sitting on both sides of the table - as an interviewee striving to prove my skills and as an interviewer evaluating candidates:   - Communicate trade-offs clearly - Test your code with multiple cases - Start with a brute force, then improve - Clarify edge cases & constraints early - Know when to trade-off time vs. space - Explain time & space complexity upfront - Know when to use BFS vs. DFS in graphs - Optimize only after correctness is ensured - Don’t overcomplicate: simple solutions win - Think out loud & show your thought process - Handle errors & unexpected inputs gracefully - Use stack for problems with nested structures - Understand system design even at junior levels - Recognize patterns (many problems are variations) - Cache results for repeated calculations (Memoization) - Understand when to use heaps & priority queues - Confidence matters(believe in your approach) - Master sliding window for subarray questions - Use binary search for optimization problems - Use modular functions for better readability - Know when recursion vs. iteration is better - Use meaningful variable & function names - Write clean, readable, and modular code - Divide & conquer for large problem sets - Refactor before finalizing your solution Understand the problem before coding - Use two pointers for array problems - Use hash maps for quick lookups - Know how to debug efficiently At the end of the day, coding interviews aren’t about memorization, they’re about structured thinking.  Which lesson do you wish you knew earlier?

Today, I witnessed my team lead interviewing a Full-Stack Web Developer with 2 years of experience, and I observed some interesting insights. The interview started with basic technical questions, which the candidate answered well. Then, my team lead gave him a coding task: 👉 "Write a function that removes duplicate values from a nested array while preserving its structure (PHP)." The candidate struggled and couldn’t solve it. So, my lead gave him another task: 👉 "Write a function that groups an array of associative arrays based on a specific key." Again, he couldn’t solve it. At this point, he admitted: "I don’t always have syntax and logic rules memorized, as I usually rely on resources like Stack Overflow and ChatGPT. Could you assign me a real-world task instead?" Here,I decided to step in. Since I was working on WooCommerce project, I gave him this challenge: 💡 "Implement a functionality where a logged-in user gets a 15% discount if they place two orders in a single day." We allowed him to use Google, ChatGPT, or any other resources. To our surprise, within 1.5 hour, he understood WooCommerce functionality, analyzed the existing code, and successfully implemented the feature. ✨ We ended up hiring him! ✨ Key Takeaway Many traditional interview techniques overemphasize logical puzzles and syntax-heavy questions, yet modern developers approach problem-solving differently. Rather than memorizing solutions, they adapt, learn, and implement on the spot using the tools and resources available to them. 💡 Instead of testing how well candidates remember syntax, we should focus on how effectively they apply problem-solving skills to practical challenges. What’s your take on this? Let’s discuss in the comments! 👇 #HiringTechTalent #TechCommunity #WhatDoYouThink

In my first coding interview, I was so focused on solving the problem that I didn’t care about how my code looked. Messy variables, no indentation, and zero structure. Guess what? I didn’t clear that round. Turns out, clean code matters as much as the solution. Here’s what we should take care of while writing good code during interviews: ✅ Variable names matter Avoid a, b, or temp. Use meaningful names like maxSum or isPalindrome—it makes your logic easier to understand. ✅ Indentation is important Write code that’s neat and properly aligned. It shows you’re organized and professional. ✅ Write scalable solutions Avoid hardcoding values. Use variables and write code that can handle a range of inputs. ✅ Comments If something in your code feels complex, add a quick comment or explain it to the interviewer while coding. ✅ Keep it simple Don’t overcomplicate your logic. A clear and efficient solution always wins. Your code isn’t just a solution—it’s a reflection of your approach. So, the next time you solve a problem, write like you’re being interviewed. Because clean code == confidence. All the best!❤️

During a technical interview, I was asked to: “Build a 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗲𝗿 𝘀𝘆𝘀𝘁𝗲𝗺 that suggests clothing items with images, with a gender filter.” The challenge? I had just 𝟮𝟬–𝟯𝟬 𝗺𝗶𝗻𝘂𝘁𝗲𝘀. Now, in that moment, my head was running through options.  • Backend → Should I go with FastAPI/Flask or keep it plain Python?  • Frontend → React, Tkinter, or Streamlit?  • Algorithm → Something advanced, or something lightweight? Given the time, I chose:  🔹𝗦𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝘁 for the UI — easy to setup and best for quick prototyping  🔹 𝗧𝗙-𝗜𝗗𝗙 + 𝗸-𝗡𝗲𝗮𝗿𝗲𝘀𝘁 𝗡𝗲𝗶𝗴𝗵𝗯𝗼𝗿𝘀 for the recommendation logic — simple but effective.  🔹𝗠𝘆𝗻𝘁𝗿𝗮 𝗙𝗮𝘀𝗵𝗶𝗼𝗻 𝗗𝗮𝘁𝗮𝘀𝗲𝘁 — it already had product images, so integration was smooth. The result → A quick working demo where users could type a query (like “blue denim”), filter by gender, and get relevant clothing recommendations with images. Takeaway? In both interviews and real projects, it’s not about chasing the most advanced solution, it’s about making the 𝗿𝗶𝗴𝗵𝘁 𝘁𝗿𝗮𝗱𝗲-𝗼𝗳𝗳𝘀 under pressure and delivering something that actually works. A simple, working system gives the team something to test, critique, and improve, while an over-engineered non-functional system gives nothing to build on. #MachineLearning #RecommenderSystems #Python #Streamlit #KNN #TFIDF #TechInterviews #CodingInterview #TimeManagement #ProblemSolving 

"Just do more leetcode! Learn the patterns! Do the x 150 list!" This is by far the most common advice I see when people talk about getting better at coding interviews. And honestly? It misses the mark. Yes, knowing sliding windows and backtracking patterns is valuable. But what really moves the needle are what I call "reusable ideas" - small, granular techniques that show up everywhere. Take the is_valid function for checking valid cells in a grid or the directions array for finding grid neighbors: ``` directions = [[-1,0], [1,0], [0,-1], [0,1]] for dr, dc in directions:   new_row, new_col = row + dr, col + dc ``` These tiny snippets shows up in: • Simple grid problems (https://lnkd.in/gBvfGGpF) • DFS problems (https://lnkd.in/gBygf62B) • BFS problems (https://lnkd.in/g9uQy_km)  • Backtracking (https://lnkd.in/gyk8U4pr) • DP (https://lnkd.in/g2R5_2b6) • Simulation (https://lnkd.in/g6_FVyUp) • And more! Most people get stuck writing nested if-statements to check bounds and handle directions. They waste 5-10 minutes in the real interview on something that should take 30 seconds. That amount of time can cost you the job! Here's what I focus on instead of grinding more problems: 1. Identify techniques that cut across multiple problem types 2. Practice implementing them until they're muscle memory 3. Treat them as building blocks and learn to reach for them when appropriate during interviews The goal doesn't have to be to solve 500 problems. It's to build a toolkit of reusable components that make you faster and more confident when it matters. What reusable techniques have saved you time in interviews? There are 42 reusable ideas listed in Beyond Cracking the Coding Interview? Want to see our whole reusable ideas catalog for free? You can with this link: https://lnkd.in/gNrhUSbQ

I wish someone had told me this earlier: Coding interviews become much easier when you stop focusing on individual questions and start focusing on patterns. Most candidates spend months solving random problems and still feel unprepared because every new question looks unfamiliar. The reality is that a large percentage of interview questions are built on a relatively small set of patterns: • Arrays • Hashing • Two Pointers • Sliding Window • Binary Search • Linked Lists • Stack & Queue • Trees & BST • Heaps • Graphs • Backtracking • Greedy Algorithms • Dynamic Programming • Intervals • Prefix Sum • Union Find (DSU) Once you start recognizing these patterns, interview preparation becomes far more structured. Instead of thinking, “I haven’t seen this question before,” you start thinking, “I’ve seen this pattern before.” That shift is what separates endless practice from effective preparation. If you’re preparing for coding interviews, spend less time chasing the next question and more time mastering the underlying patterns. Everything starts to connect after that. Save this for your next interview prep. Repost if it helps someone in your network.

The no. 1 reason you're stuck at the SQL interview stage It’s not the tough questions, it’s how you’re tackling the simple ones. Sometimes I know you feel like SQL interview questions that should be a breeze trip you up the most. You know the concepts, but when it’s crunch time, it’s like your brain has other plans. Trust me, you’re not alone. That struggle to explain something basic under pressure? Happens to the best of us. Picture this: you’re in the interview, your interviewer asks, “What’s a JOIN?” You know JOINs backward and forward, but suddenly, your mind goes blank, or worse, you start overthinking it, turning a straightforward question into a tangled explanation. Here’s how to handle four of the most common SQL questions: 1, What is a JOIN? Keep it simple: INNER JOIN gets matching rows from both tables, LEFT JOIN pulls all rows from the left even if they don’t match the right, and so on. Adding a clear example or use case for each type is what sets a good answer apart. 2, Difference between WHERE and HAVING? WHERE filters rows before aggregation, and HAVING filters after. Mention grouping and aggregates to make sure your answer stands out. 3, How do you optimize SQL Queries? Sure, you can talk about indexes, but consider going further—mention things like using fewer subqueries or limiting SELECT to only necessary columns. This shows a more advanced understanding of efficiency. 4, Finding the second-highest salary in a Dataset It’s a classic! A subquery is often the simplest method. But don’t forget to mention handling NULLs or duplicates. Interviewers are listening for how you handle real-world data quirks. The trick isn’t about the “perfect” query; it’s showing you understand why you’re doing what you’re doing, that you know the logic, trade-offs, and how to explain it clearly. 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆 • Practice explaining your answers aloud like you’re teaching a beginner. Clear explanations can be more impressive than complex answers. • Know the basics: joins, WHERE vs. HAVING, and query optimization. • Be concise but thorough. Demonstrate your logic and reasoning, not just the syntax. What’s the toughest SQL interview question you’ve faced? PS: If you think it can be useful for someone else, share this post ♻️

💡 In coding interviews, the expectation is not flawless code. What interviewers really look for is clarity of thought, problem-solving approach, and communication. Think about it — no one expects you to craft a production-ready, fully optimized solution in just 45 minutes. Instead, they want to see: > How do you understand the problem? > How do you break it down into smaller steps? > How do you recover when things don’t go as planned? It’s perfectly fine if you pause to think, take a wrong turn, or even forget syntax. What matters is your ability to adapt, correct yourself, and keep moving with confidence. So, when you prepare, don’t aim for perfection. > Aim for structured thinking. > Aim for communicating your approach. > Aim for calmness under pressure. That’s what separates a good candidate from a great one. And honestly, that’s what real-world engineering is all about. Good luck to everyone on this journey 🚀 #CodingInterviews #InterviewPreparation #ProblemSolving #SoftwareEngineering #CareerGrowth #TechCareers #DSA #SystemDesign