Devang Sharma

One thing your manager will never tell you Your promotion depends less on your performance and more on whether your team is actually growing. When I joined Amazon as an SDE-1, my team had 25 people. By the time I became Senior, it had 120+. Looking back, my “fast promotion” wasn’t magic. The org was expanding like crazy and growth creates opportunity. Here is the part people don’t like hearing: ❌ If your team hasn’t grown in years, your career won’t either. ❌ It doesn’t matter how good you are. There is nowhere to go. ❌ The only real path up becomes waiting for someone above you to leave. So if you want to grow faster: Choose teams that are growing. Not teams that are comfortable. Skills matter. Environment matters more.

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Here’s exactly how I would crack a $150K+ SWE job at Microsoft in 6 months. (A real strategy my client used to land interviews at Microsoft, Meta, and Stripe) Too many engineers prepare hard to crack MAANG. But they lack a solid strategy. Here’s the exact roadmap I'll follow if I wanted to land a SWE job at Microsoft. Step 1: Resume + Role Clarity → Reverse-engineer the JD Study at least 10+ Microsoft SWE job listings. Highlight recurring keywords, must-haves, and preferred tools. → Rewrite your resume like a product pitch Show measurable impact: Good: “Improved load time by 43%” Bad: “Worked on performance optimization.” → Make it keyword-optimized for ATS without sounding robotic. Step 2: Master DSA the Microsoft Way → Focus on patterns, not problems Microsoft LOVES: Sliding window Trees (esp. DFS/BFS) Graphs Dynamic programming → Suggested Platforms: Leetcode (Microsoft tag), Neetcode(dot)io roadmap, Grokking series on Educative → 2 problems/day + 1 mock interview/week = compounding prep Step 3: System Design (yes, even for junior roles) → Start with High-Level Design (HLD): Learn how to design APIs, caching, rate limiting, and DB scaling. → Build a project where you actually implement what you learn. Step 4: Microsoft-Specific Behavioral Prep → Microsoft uses structured behavioral interviews Focus on “3As” framework: Action → Approach → Aftermath → Use real projects to show: Collaboration Adaptability Customer focus Engineering rigor → Prep 8–10 STAR stories mapped to their values Step 5: Mock + Real-World Practice → Do 4–5 peer or mentor-led mock interviews (especially for behavioral + design) → Record yourself. Watch for filler words, unstructured answers, lack of metrics. → Apply for 5 roles/week—Microsoft + similar-sized companies (to get into interview flow) Step 6: Apply Strategically + Use Referrals → Connect with 3–5 engineers/recruiters/week on LinkedIn. Don’t ask for a referral right away - engage first. → Reach out using tailored messages like: “Hi [Name], I’ve been preparing for an SWE role at Microsoft. Your journey from [X] to [Microsoft] really stood out. If you're open, I’d love to learn more about your experience.” → Submit applications using referrals whenever possible + 1-click apply where relevant The client who followed this playbook now works at Microsoft Azure and had 3 competing offers before accepting. It’s not about doing everything. It’s about doing the right things in the right order. Give yourself 6 months and follow this roadmap to make it a reality. Share this with someone who dreams of working at Microsoft. P.S. Follow me if you are a tech job seeker in the U.S. I share practical advice that gets you hired. — Additional resources: https://lnkd.in/eKxQmYtP. https://lnkd.in/gwRWpXR9. https://lnkd.in/g94_Cziv

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Here’s exactly how I would crack a $150K+ SWE job at Microsoft in 6 months. (A real strategy my client used to land interviews at Microsoft, Meta, and Stripe) Too many engineers prepare hard to crack MAANG. But they lack a solid strategy. Here’s the exact roadmap I'll follow if I wanted to land a SWE job at Microsoft. Step 1: Resume + Role Clarity → Reverse-engineer the JD Study at least 10+ Microsoft SWE job listings. Highlight recurring keywords, must-haves, and preferred tools. → Rewrite your resume like a product pitch Show measurable impact: Good: “Improved load time by 43%” Bad: “Worked on performance optimization.” → Make it keyword-optimized for ATS without sounding robotic. Step 2: Master DSA the Microsoft Way → Focus on patterns, not problems Microsoft LOVES: Sliding window Trees (esp. DFS/BFS) Graphs Dynamic programming → Suggested Platforms: Leetcode (Microsoft tag), Neetcode(dot)io roadmap, Grokking series on Educative → 2 problems/day + 1 mock interview/week = compounding prep Step 3: System Design (yes, even for junior roles) → Start with High-Level Design (HLD): Learn how to design APIs, caching, rate limiting, and DB scaling. → Build a project where you actually implement what you learn. Step 4: Microsoft-Specific Behavioral Prep → Microsoft uses structured behavioral interviews Focus on “3As” framework: Action → Approach → Aftermath → Use real projects to show: Collaboration Adaptability Customer focus Engineering rigor → Prep 8–10 STAR stories mapped to their values Step 5: Mock + Real-World Practice → Do 4–5 peer or mentor-led mock interviews (especially for behavioral + design) → Record yourself. Watch for filler words, unstructured answers, lack of metrics. → Apply for 5 roles/week—Microsoft + similar-sized companies (to get into interview flow) Step 6: Apply Strategically + Use Referrals → Connect with 3–5 engineers/recruiters/week on LinkedIn. Don’t ask for a referral right away - engage first. → Reach out using tailored messages like: “Hi [Name], I’ve been preparing for an SWE role at Microsoft. Your journey from [X] to [Microsoft] really stood out. If you're open, I’d love to learn more about your experience.” → Submit applications using referrals whenever possible + 1-click apply where relevant The client who followed this playbook now works at Microsoft Azure and had 3 competing offers before accepting. It’s not about doing everything. It’s about doing the right things in the right order. Give yourself 6 months and follow this roadmap to make it a reality. Share this with someone who dreams of working at Microsoft. P.S. Follow me if you are a job seeker in the U.S. I share practical advice that gets you land $150k+ roles in top companies.

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If you interview for an SDE-1 role at Amazon, they will ask you to solve 1 Medium + 1 Hard LC in just 45 minutes. If you interview at Google, Microsoft, they will also ask you to solve 1 Medium + 1 Hard LC in just 45 minutes. At any company you interview today, excluding startups: No matter how many problems you've solved. No matter how good you are, you might be the most talented in that pool of candidates. All that matters to the interviewer in that moment of the first coding round is: → How fast you identify the pattern → How well you optimize → How clearly you explain under pressure That's why strong DSA is the best equalizer. You don’t need system design for SDE-1 roles. You can get in with just awesome DSA skills. But that's where most candidates fail, and honestly, it’s a simple fix. DSA patterns help you: → stop getting stuck and losing hope midway → solve faster because you don’t reinvent the wheel → spot solutions even for unseen problems → build confidence on yourself and in your skills. And that’s exactly why I want to recommend this DSA pattern product, it completely changes the way you prepare. Link: : https://lnkd.in/g94khGEh This DSA product will help you: - help you track and learn the clues and triggers of different patterns - provide AI-based doubt solving + space to add your own notes - solve 250+ good problems with 5 problems each on 50 patterns - train you on every scenario, so you can solve unseen problems. Stop guessing and start preparing for the way these companies hire.

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Enough layoff news. Gear up for upcoming job openings and this can be a big shot for you. In Feb-March you will see a number of openings. I'm listing what to do, how to prepare and list of companies to keep a check on, classification of these companies, their roles and requirements and what their teams are working on. Source: Internal town-hall meetings, VPs and leads, HR discussions, and best of all- info. on upcoming ambitious projects in these companies. Basically... any guy in Bengaluru with few years here and connections with companies can get this out. Let's start with, how to PLAN: - Create a excel sheet of companies, roles and requirements. You will understand later how it magically helps. - Apply minimum in 5 companies each day. And keep on doing this for whole Feb-March time period. - Make 2 resumes. The best hack. Just change phone number and mail id. Resume 1, to apply as soon as you spot the opening. - Resume 2 will be, to get referrals. But since that can be difficult or late at times, Resume-1 got your back. - Keep your Linkedin and Naukri profiles updated. Skip all unnecessary fancy websites sharing farzi job updates. Save your efforts, you need a lot. - For every interview experience, make a folder, journal it in detail. Questions, answers, discussions, time taken. And all interviews, good, bad, rejected, accepted, all. - Build AI and custom LLM projects and deploy them on cloud. Why am I saying this? Because of the teams in which openings are coming. Will describe that too. - Stay in touch with people from companies that I'll be listing. Build good repo with them. Referrals do work, no matter what people say about it. - At that time, coz of so many openings, you'll see people faking a lot in interviews. Don't be fake. If you have not worked on anything, just say you are willing to learn but you have not explored it yet. - Very important, make your resume on Google docs, and not by any AI. You know yourself way better than any any any AI. - This is important, given that new openings can be confusing for some people. Try to apply within first 7 days of opening. HRs will hardly scroll through so many applications. Try and be an early applicany. LISTING companies here: Tier-1: Vm Ware, Google, PayPal, Nvidia, Goldman Sachs, Arcesium, Intuit, Adobe, Linkedin, Philips Tier-2/3: Myntra, Epam, Sapient, Expedia, Bluejeans, FIS, Twilio, Virtusa Yes the companies are less, but there are ample number of openings coming in these for all experience groups. And given the type of companies, I'm pretty sure soon I'll get info. on some more in the similar sector. Sorry, but due to word limitations, I'm stopping here. But I'll also write a detailed segment on which teams and what kind of roles are coming. And what are the right projects to work on for this. And if possible, a breakdown series of few important interview questions. → Keep learning. It's almost the right time. And keep helping others too, good karmas do come back🫶

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I’ve interviewed with 3 MAANG companies (Google, Microsoft, Amazon)… And here are 3 things you NEED to know before your next interview 👇 (Esp. if you’re preparing for mid-level SDE roles at top PBCs 🚀) 💡 TIP #1: Give Data Structures & Algorithms (DSA) fundamentals PRIORITY. → Most tech giants, esp. Google, expect you to be strong in Arrays, Strings, Trees, Graphs, and DP. → Don’t just solve random problems. Instead, focus on mastering core patterns, Sliding Window, Binary Search, DFS/BFS, Trie, DP state transitions. 💡 TIP #2: Don’t think Behavioral Rounds are “OPTIONAL” At PBCs like Amazon, your real contributions and leadership will matter. So always quantify your impact → “Led a team of 4 engineers to reduce API latency by 30%” is far better than “Worked on APIs”. 💡 TIP #3: System Design will become UNAVOIDABLE (even mid-level) Interviewers will expect you to design scalable, reliable systems, and explain tradeoffs clearly, especially at Microsoft. Practice structuring your thought process ⬇️ → Start with requirements → High-level architecture → Data modeling → API contracts → Scalability challenges. These actionable tips can help you switch to MAANG-level PBCs, so if you’re working a 9-5 and struggling to prep for your next big role… I highly recommend giving Bosscoder Academy a try. 🔗 Explore their programs here: bcalinks.com/Ce2ut6d They’ve helped 2200+ engineers crack top PBC roles through: 💡 Structured curriculum to help you master DSA, System Design, & AI 💡 Real world, AI-powered projects & 24/7 doubt-solving 💡 1:1 mentorship from industry experts 💡 Resume reviews, mock interviews, & 100% job switch support 📢 P.S. Their REPUBLIC DAY Sale is LIVE with Flat 25% OFF on all programs for a limited time, sounds like the perfect moment to start upskilling! #sdeprep #systemdesign #interviewtips #tech #jobswitch #maang #pbcs #collab

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Let's say you're in an interview for the SDE-II role at Blinkit and you're asked this LLD question: Design a restaurant food ordering system like Zomato, Swiggy, DoorDash How would you answer it? I'm an Engineering Manager with a deep frontend background across the last 12 years of my career. Here's how I would answer it. [1] What a naive design would do Idea: Store everything in memory or simple files, process orders synchronously. Flow: - User browses restaurants from a single database query - Add items to cart stored only in browser localStorage - Submit order as one big transaction - Poll database every few seconds to check order status Why this breaks down? - Cart state lost if user switches devices or clears browser - No real-time updates when restaurant accepts/rejects order - Concurrent order placement causes race conditions (same item sold out) - No way to handle multiple actors (user, restaurant, delivery partner) updating order state - Single database becomes bottleneck during peak hours (lunch/dinner rush) Just localStorage and polling won't scale for a company like Swiggy or DoorDash. --- [2] What real systems do: event-driven architecture with state machines Core Services: Order Management Service - POST /orders, GET /orders/{id}, PATCH /orders/{id}/status - Order state machine: CREATED → CONFIRMED → PREPARING → READY → PICKED_UP → DELIVERED - Each state transition publishes events to message queue (Kafka/RabbitMQ) Cart Service - Separate service with Redis/Memcached for fast, distributed access - Key: user_id + session_id, value: {restaurant_id, items[], subtotal, taxes} - TTL of 30-60 minutes to auto-cleanup abandoned carts - Syncs to backend on every cart modification so it's available across devices Restaurant Service - Menu management with real-time item availability flags - Inventory checks before order confirmation - Restaurant dashboard subscribes to order events for kitchen display system Delivery Service - Assigns delivery partners using matching algorithms (proximity, ratings, current load) - Tracks location via GPS updates every 10-15 seconds - WebSocket connections push location updates to user's app for live tracking Key Data Models: Order {   id, user_id, restaurant_id,    items: [{item_id, quantity, price, customizations}],   status, delivery_address, payment_id,   timestamps, delivery_partner_id } OrderEvent {   order_id, event_type, actor,    previous_state, new_state, timestamp } Real-time Updates: - Client establishes WebSocket connection when order is placed - Backend pushes status changes: "Restaurant confirmed", "Food is ready", "Partner is 2 mins away" - Fallback to Server-Sent Events (SSE) or long polling for older devices Continued ↓

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LeetCode has 3374 problems But Most PBCs repeat these 20 🔻 1. 𝐀𝐫𝐫𝐚𝐲𝐬 & 𝐇𝐚𝐬𝐡𝐢𝐧𝐠 (Google, Amazon, Meta, Microsoft) → Two Sum, Longest Consecutive Sequence, Subarray Sum Equals K 2. 𝐒𝐥𝐢𝐝𝐢𝐧𝐠 𝐖𝐢𝐧𝐝𝐨𝐰 & 𝐓𝐰𝐨 𝐏𝐨𝐢𝐧𝐭𝐞𝐫𝐬 (Google, Meta, Amazon) → Longest Substring Without Repeating Characters, Container With Most Water, Minimum Window Substring 3. 𝐒𝐭𝐚𝐜𝐤 & 𝐌𝐨𝐧𝐨𝐭𝐨𝐧𝐢𝐜 𝐒𝐭𝐚𝐜𝐤 (Google, Amazon, Facebook) → Valid Parentheses, Largest Rectangle in Histogram 4. 𝐁𝐢𝐧𝐚𝐫𝐲 𝐒𝐞𝐚𝐫𝐜𝐡 (Google, Amazon, Meta) → Search in Rotated Sorted Array, Median of Two Sorted Arrays 5. 𝐋𝐢𝐧𝐤𝐞𝐝 𝐋𝐢𝐬𝐭 (Google, Amazon, Meta) → Merge Two Sorted Lists, Detect Cycle in Linked List 6. 𝐓𝐫𝐞𝐞𝐬 & 𝐆𝐫𝐚𝐩𝐡𝐬 (Google, Meta, Amazon) → Lowest Common Ancestor, Word Ladder, Number of Islands 7. 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 (Google, Amazon) → Climbing Stairs, Longest Palindromic Substring, Coin Change 8. 𝐇𝐞𝐚𝐩𝐬 & 𝐏𝐫𝐢𝐨𝐫𝐢𝐭𝐲 𝐐𝐮𝐞𝐮𝐞𝐬 (Amazon, Google, Meta) → Kth Largest Element, Merge K Sorted Lists Remember, you don’t need to solve thousands of problems to crack your target company. A focused, strategic approach on key topics works best. And you can get exactly this by connecting with senior SDEs from top PBCs. 🔥 Just connect with them for FREE here: https://lnkd.in/gqfsRHDS They’ll guide you through in-depth DSA concepts, help you recognize common patterns, and teach company-specific coding practices. With mock interviews and real-time feedback, you'll be ready to crack DSA interviews and land your dream job. 💪 PS: Sometimes, stepping back and asking for help is the smartest move. #dsaquestions #dsatopics #collab #preplacedcollab #interviewprep #techinterviews #interviewtips

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You are in a system design interview at Amazon for an SDE-3 role and the interviewer has given you the question to Design Netflix. He then asks a follow up to you: How does Netflix knows when to show: Are you still watching? Is it just time-based? If it were time-based, you would see it every time. So what is actually going on under the hood? Both look like a simple pop-up. Underneath, it is a mix of product thinking, client logic, and backend events. Btw, if you’re preparing for system design/coding interviews, check out our mock interview tool. You can use it for free here: https://lnkd.in/gpCn7t2T [1] Start from the product goals The feature is not only about nagging people. - Save bandwidth and CDN cost if the viewer has slept or walked away - Avoid autoplaying potentially sensitive content in an empty room - Protect kids if parents start a show and leave the TV on - Do all this without annoying active binge watchers So the design must answer one question: "When is the user probably not here any more" [2] Naive design - pure timer Simplest idea: - If playback has been running for 2 hours, show Are you still watching - If user clicks "Yes", reset the timer Why this is weak: - Someone can binge 5 episodes in a row and gets interrupted in the middle of an intense scene - Someone can start a show, walk away after 5 minutes, and the platform will keep streaming for the next 2 hours - It ignores how many episodes were auto played, device type, time of day, user habits  [3] Realistic design - session and engagement signals Think in terms of a "watch session" and "engagement events". Signals the client can track: - Play, pause, seek, volume change - Episode finished and next episode auto started - Remote or keyboard input, UI navigation - Screen on or off events from the device - For mobiles: app background or locked state A common heuristic could be: - Count how many episodes have auto played without any user interaction - Track how long it has been since the last button press or navigation - Only trigger the prompt when both are high enough Example rule: - If 3 episodes in a row have auto played - And there has been no interaction for 45 minutes - Then, before starting episode 4, show Are you still watching This feels much smarter: - Active viewers who pause, skip intro, change volume keep resetting the "engagement clock" - Sleeping viewers do not touch anything, so the next episode is blocked by the prompt  [4] Client heavy vs server heavy design You can talk about two design choices. Client first: - All logic runs inside the app on TV, mobile, or web - Client keeps an in memory session model and decides when to show the popup - It still sends telemetry events to backend for analytics and future tuning Pros: - Works even with flaky network - Highly responsive, no extra server round trip Cons: - Logic must be implemented and updated across many platforms - Harder to quickly roll out rule changes Continued ↓

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If I had a system design interview tomorrow at Google, this is exactly how I’d approach it. (This framework helped me crack 3 FAANG+ companies in the past, including Amazon.) Most engineers fail system design interviews not because they lack knowledge but because they lack structure. You don’t need to memorize 100 architectures. You need a structured and easy-to-apply approach that works every time. Here’s how I break it down: 1/ Clarify the Problem Before Writing Anything - System design interviews aren’t about throwing buzzwords—they’re about trade-offs. - Start with scoping → Are we designing just one feature or the entire system? - Ask constraints upfront → How many users? Read/write ratio? Latency requirements? - Define success criteria → What matters most? Scalability? Cost? Low-latency? Most candidates assume things and jump into solutions. I make sure I know what we’re solving before I even start. 2/ Define Functional & Non-Functional Requirements Clearly - Functional: What features does the system need? - Non-functional: What are the performance expectations? - What’s the biggest technical challenge? (This helps guide the discussion.) Example: If we’re designing YouTube, is the focus on video uploads, recommendations, or live streaming? Each has a different set of constraints. 3/ Estimate the Scale & Plan Capacity Like an Engineer - Users per second? Requests per second? - Storage needs? If we store 10MB per user and have 100M users, what does that mean? - Throughput? Can a single database handle the load, or do we need sharding? Most candidates throw random numbers. I do quick, back-of-the-envelope calculations to validate my assumptions. 4/ Break the System into Core Components (High-Level Design) - Define the major building blocks → API Gateway, Load Balancer, Service Layers, Databases. - Don’t overcomplicate. Simple and scalable always wins. - Clearly define the interactions between services. If I’m designing a messaging app, I break it down into: — User Service (auth, profiles) — Messaging Service (storing chats) — Notification Service (real-time updates) — Media Storage (for images, videos) Each has different constraints, so I build around what’s most important. Continued Here: https://lnkd.in/eJ2T966N

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When you join a new org or switch teams in the same, it is quite an unsettling and borderline anxious experience. Here are a few things that I did to ramp up faster. 1. I consciously made an effort to remain unblocked 2. I read a ton of code and its history, sometimes even unrelated 3. I asked questions about the past, the present, and the future 4. I took up relatively mundane tasks - cross-team work, tests, and docs 5. I extended a helping hand in whatever capacity I could 6. I proactively met skip-level leaders and managers to understand the vision Some companies do have a culture of pairing up with someone existing in the team, but even if you do not get a mentor, it is important that you still navigate the situation and ramp up as quickly as you can. The above list is not exhaustive, by any means, and hence you can always add things that you find helpful in your context. but the lowest common denominator is to show extreme intent and interest to get output and drive outcomes. Hope this helps.

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After conducting ~200 interviews at #Amazon, I’ve seen clear patterns in what sets successful candidates apart. If you’re aiming for an SDE role, here’s how to focus your prep: 1. Sharpen Your Problem-Solving Skills: Strong fundamentals in data structures and algorithms are non-negotiable. Practice medium to hard problems on LeetCode—focus on arrays, trees, graphs, heaps, and DP. 2. Be Ready for System Design Even at L4/L5, expect a system design round. Think high-level architecture, scalability, trade-offs, and be familiar with AWS basics. 3. Master Behavioral Interviews Amazon takes Leadership Principles seriously. Use the STAR format to craft strong stories—highlight ownership, customer obsession, and problem-solving. 4. Think Aloud Interviewers care about your approach, not just the solution. Talk through your thought process, assumptions, and edge cases clearly. 5. Do Mock Interviews Practice with peers or mentors. Real-time feedback improves communication, pacing, and confidence. Consistency beats cramming. Prepare with intention, and you’ll be ready. Let me know how this helped you! #Amazon #SDEInterview #SoftwareEngineering #TechCareers #LeadershipPrinciples

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From 9+ yrs in mid-size PBCs → SDE @ British Petroleum at 50+ LPA 🥳 “After almost 10 years in product companies, I knew I needed bigger responsibilities, leading teams, handling systems at scale, but my prep had no structure.” That is how Niranjan Bagade described his phase before joining Bosscoder Academy. He had already spent 1.5 years preparing on his own, LeetCode, random materials, YouTube, but with no roadmap, no feedback, no direction. Months went by, and there was no measurable progress. But then he decided to upskill through Bosscoder Academy and: ✅ He learned to identify the core patterns and do pattern-wise DSA prep ✅ Got a structured & personalised roadmap instead of scattered prep and yt videos ✅ Learned how to think for interviews, not just for practice ✅ Cleared his blockers through real-time mentorship from industry experts  ✅ Rebuilt confidence through mock interviews & peer learning Soon after completing the program, he cracked a 50+ LPA SDE role at British Petroleum with the help of Bosscoder’s placement team & transitioned into a role with higher scope and ownership. So, for anyone aiming to switch to top PBCs for SDE-2/3 roles, working full-time & losing direction, his advice was simple: → Put in honest effort, stick to the process, be patient, & don’t give up when it gets slow. And if you’re an SDE juggling prep with a full-time job, I’d strongly recommend getting help from industry experts at Bosscoder Academy. 🔗 Explore their programs here: bcalinks.com/VbU062Z They’ve helped 2200+ engineers crack top PBC roles through: 💡 Structured curriculum to help you master DSA, System Design, & AI 💡 Real world, AI-powered projects & 24/7 doubt-solving 💡 1:1 mentorship from industry experts 💡 Resume reviews, mock interviews, & 100% job switch support 📢 P.S. Their FESTIVE Sale is LIVE, and all their courses are 25% OFF for a limited time offer! #softwareengineer #collab #interview #successstory

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I thought 3+ YOE as an SDE would make interviews easy. But I’ve failed enough interviews to know this → experience alone WON’T save you. Here are 7 mistakes I made (and often see other SDEs make) when interviewing for top product companies 👇 ❌ I wasted time guessing LC problems instead of solving what was asked. Interviewers rarely use exact LC questions, focus on the problem in front of you. ❌ Rushing into code made me rewrite half of it later. Explaining the approach and confirming assumptions first saves time and shows clarity. ❌ Skipping test cases early backfired. Writing them upfront gives structure and prevents missing critical scenarios. ❌ Hoping interviewers won’t notice bugs NEVER works. Acknowledge them and suggest fixes, it reflects ownership. ❌ Finishing the solution isn’t enough. If you can’t explain complexity, you’re out, so be ready every time. ❌ Expecting the code to speak for itself. Interviewers can’t read your mind. Explain your thought process as you code to show reasoning. ❌ I once added flashy claims I couldn’t defend. If you can’t explain it, don’t list it, because credibility matters more. Have you ever seen yourself making similar mistakes? If yes, it might be because your prep can be scattered and inconsistent without proper guidance. So if you’re preparing for SDE-2/3 interviews with top PBCs while juggling a 9-5, I highly recommend getting guidance from industry experts at Bosscoder Academy. Explore their programs here 👉 https://shorturl.at/8mW0H They’ve already helped 2200+ engineers switch to top product-based roles with a well-structured curriculum for DSA, SD, and full-stack development, 1:1 mentorship from industry experts, and 100% job switch support. Abhay Singh

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