Pranav Sahu

WHY I DID A PM INTERNSHIP BEFORE STARTING SWE AT GOOGLE 👇🏻 1. LEARNED TO BE USER OBSESSED. Guys, engineering is not just about coding. It’s about building something USEFUL for someone. When I took CS classes at Berkeley, everyone was obsessed with coding and passing test cases, but barely ANYONE talked about the product and if users would even use it. 2. LEARNED CROSS-TEAM COMMUNICATION. Engineers may think PM’s are useless, but they are the ENTIRE REASON engineers have clarity to build. As a PM, I was constantly communicating between cross-functional teams (marketing, eng, customers) to constantly refine feature requests and make it as easy as possible for engineers to build. This taught me to be a more communicative engineer. 3. LEARNED PRIORITIZATION. PM’s ruthlessly prioritize which features to build first. And you cannot possibly build everything in the quarter 😭😭 From this, I learned how to assess the stakeholders of each project and pick which project will have the most impact in a given timeframe. so for all my engineers out there STOP GIVING YOUR PM A HARD TIME and put yourself in their shoes 🙂‍↕️🙂‍↕️

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Lately, been interviewing quite a few candidates for SDE roles — and there’s a trend I can’t ignore. Many are relying on GenAI tools (like ChatGPT) to “help” them in interviews — or, let’s be blunt, to cheat. Now, I’m all in for using these tools for learning, practicing, exploring new ideas. But when you’re facing a problem and you immediately turn to AI for the answer, you’re missing a crucial piece : Your own problem-solving muscle. Here’s the thing, when you actually join a good tech-heavy company, you’ll be working with: internal libraries, custom tools, proprietary systems, unique business constraints. These are things external GenAI tools can’t access ideally and no magic prompt will save you. You’ll need to: Read unfamiliar code, Debug tricky edge cases, Navigate evolving architectures, Work through evolving and fuzzy requirements. That’s where real engineering skill shows up. Not just knowing where to look things up — but being able to think through, break down, and solve problems on your own. So here’s my take: By all means, use GenAI to level up, to practice, to learn. But don’t let it become a crutch that weakens your independent thinking. #SoftwareEngineering #TechInterviews #GenAI #ProblemSolving #CareerGrowth

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🚀 My Interview Experience with Intuit I recently went through the hiring process at Intuit, and it was one of the most unique (and AI-focused!) interview journeys I’ve experienced. Sharing it here in case it helps someone preparing 👇 🧪 Round 1: Online Assessment 3 questions: 1 DSA 1 Shell Scripting 1 SQL A fairly standard start, testing core problem-solving and practical skills. 💬 Round 2: Recruiter Screening (via Uptime Crew) This round was less about coding and more about you: Your interest in tech How you use AI tools Challenges faced while using AI How you verify AI-generated code 💡 Tip: Be honest and practical—this round checks your thinking, not perfection. 🛠️ Round 3: Build Challenge 2 assignments to complete in ~2–4 hours Freedom to use any language + AI tools After submission, there’s a deep-dive interview: Why you chose a specific framework Code optimizations Your overall approach 💡 Tip: Don’t overcomplicate things (learned this the hard way 😅). Keep your solution clean and justified. 🎯 Round 4: Final Technical Round (with Intuit Team) This is where things get serious: Present a project (with PPT) Heavy focus on AI usage in your workflow Deep technical grilling 💡 Tip: Be ready to defend every decision—especially how and why you used AI. 🤝 Round 5: Team Matching The final step—aligning with the right team. 🌟 Key Takeaways AI is not optional here—it’s central to the process Strong fundamentals + practical thinking matter Communication and clarity can make a big difference Hope this helps anyone preparing for Intuit or similar AI-driven hiring processes. Happy to answer questions! 😊 #InterviewExperience #Intuit #SoftwareEngineering #AI #Coding #JobPrep

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I’ve spent 4+ years as a senior level SDE in 4 companies (Cognizant, Ola, Visa, Microsoft) 🚀 And I’ve seen SDEs make these 4 technical errors when switching to tech giants like MAANG-M with a service-based background. MISTAKE #1 is Over-preparing rare algorithms → Spending weeks on advanced DP while ignoring the core 40–50 patterns PBCs actually repeat. MISTAKE #2 is skipping timed practice → It’s not just about working code, do it in 45–50 mins with edge cases & clear explanations. MISTAKE #3 is skipping System Design basics → Jumping to distributed systems buzzwords without mastering database design, caching, API design, & scalability trade-offs. MISTAKE #4 is ignoring debugging and follow-ups → In interviews, you’ll be asked to optimize or debug. Many freeze because they only practice “one-shot” solutions. Plus too many SDEs moving from service-based companies think their client/project work “doesn’t count.” I did too. But in reality, it builds adaptability, ownership, and problem-solving at scale, things PBCs value a LOT, so use it as an advantage. And if you want to learn how to use those skills to your advantage in Senior-level interviews in top PBCs, try the EVOLVE program by Bosscoder Academy. 🔗 Explore EVOLVE for SDEs w/ 6+ YOE here: bcalinks.com/dhMD4Gi They’ve helped 2200+ engineers crack top PBC roles through: 💡 Structured curriculum to help you master DSA, System Design, and AI 💡 Real world, AI-powered projects & 24/7 doubt-solving 💡 Leadership skills for Senior roles with 1:1 mentorship from industry experts 💡 Resume reviews, mock interviews, and 100% job switch support. #java #backend #systemdesign #collab #career #jobswitch #seniors

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How I reverse two-way door decisions as a Software Engineer at Amazon In a previous post, I talked about bias for action and two-way doors. These are decisions you can reverse if they don’t work out. Shout-out to Abhishek Chaurasiya who reached out via DM and asked me a great follow-up question: “What if you realize right after making a decision that it was the wrong one? What do you do then?” Here’s how I think about it: if you notice the mistake right away, you’re lucky. The longer you go down the wrong path, the more costly it will be to reverse. But the decision to reverse doesn't only affect you, so what do you do? 1. Stop and gather data. Don’t just say “I think this is wrong.” What evidence supports the change? For example, if you decided to make a service synchronous, but then realize the workloads are bursty, gather latency and throughput data to demonstrate why an asynchronous design is more resilient. Evidence will make reversal easier to defend. 2. Anticipate pushback. In a team setting, people may want to stick with the decision. Try to understand their motivations for wanting to keep the wrong decision - some are valid, some aren't (e.g. helps with someone's promotion because a system they own gets more usage). Be ready to explain why pivoting now prevents bigger pain later. 3. Reflect on the root cause. What led to the wrong call? Was it missing data? Rushing under pressure? Missing input from key domain experts? Reflection is how you avoid repeating the same mistake. If it’s your own decision, document the lessons. If stakeholders are involved, bring data and reasoning to the table. Two-way doors only help if you’re willing to step back and learn why you took the wrong turn in the first place. Trying to save face will make the problems worse. How do you handle it when you realize a decision you just made wasn’t the right one? --- Hello, I’m Charles, and I am committed to share my two cents on career-related topics for 100 consecutive days. In these uncertain times, I hope to support those facing layoffs or career challenges. Follow me, and let's navigate this together! (49/100) #BiasForAction #Leadership #DecisionMaking #CareerGrowth #SoftwareEngineering

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🚀 My Interview Experience with Intuit - SDE 1 Role I recently had the opportunity to interview for the SDE 1 position at Intuit, and I must say - the entire hiring process was thoughtfully designed and truly impressive. Here’s how it went: 🔹 1️⃣ Resume Screening + Coding Round (90 mins) The first round included: 1 medium-level DSA problem (LeetCode style) 1 SQL problem 1 Git Bash problem It was a well-balanced round testing problem-solving, database knowledge, and practical command-line skills. 🔹 2️⃣ Recruiter 1:1 – AI-Focused Discussion This was a very interesting and modern step. The discussion revolved around my understanding and practical use of AI. In today’s world, where AI is becoming integral to everyday work, this felt extremely relevant and forward-thinking. 🔹 3️⃣ Build Challenge (2–4 hours) A hands-on assessment with two assignments where: All requirements had to be implemented Proper README documentation was required Clear run configurations were expected This round strongly evaluated implementation skills, clarity of thought, and attention to detail. 🔹 4️⃣ Deep Dive Discussion on Build Challenge Another 1:1 where they: Explored my logical thinking and design decisions Discussed scalability considerations Evaluated how I used AI in development Assessed system design awareness This round focused less on “what” I built and more on “why” I built it that way. 🔹 5️⃣ Final Interview (1 hour) A comprehensive round covering: Deep dive into my background and projects System design concepts Data structures Behavioural and situation-based questions ✨ Overall, the experience was structured, practical, and aligned with real-world engineering expectations. It wasn’t just about coding - it was about thinking, building, designing, and adapting with AI in the loop. Grateful for the opportunity to go through this entire process and learn so much along the way. #InterviewExperience #SDE #Intuit #HiringProcess #SoftwareEngineering #AI #Gratitude

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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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Right before my teammate landed her SDE 2 role at a MAANG company, one thought kept replaying in her mind 👇 “What if this setback is actually setting me up for something better?” And that offer didn’t come easily either. There were months filled with second-guessing, interviews that didn’t convert, and rounds where things simply fell apart. She could have told herself, “Maybe I’m just not cut out for this.” But she chose not to! Instead of quitting, she reset her strategy and changed how she prepared 👇 → She went back to every rejection and analyzed the exact gaps in her performance. → She made DSA a daily habit, solving at least two problems a day, prioritizing pattern recognition over volume. → She doubled down on mock interviews until explaining her approach felt structured, calm, and confident. And the biggest SHIFT? She stopped preparing in isolation. She built connections on LinkedIn & found guidance from senior engineers at her target product companies. And having someone experienced review her preparation and thinking process completely elevated her game. So, if you're balancing a full-time job, intense prep, and constant uncertainty, remember this: → The right roadmap and mentorship can accelerate what your own effort sometimes can’t. And that’s exactly why I recommend getting this guidance from industry experts at Bosscoder Academy, esp. if you’re a working dev and want to save months of trial and error. 🔗 Explore their programs here: bcalinks.com/ygKkAgF They’ve helped 2,200+ engineers crack top PBC roles through: 💡 Structured curriculum to 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 Holi Sale is LIVE, so you can get 25% OFF on all courses for a limited time! #collab #pbc #career #sdeprep #tech #jobswitch #rejection

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I'm curious why big companies still use H1b visas while there is L visa. Advantages for a company: - No quotas, i.e. it's possible to move anyone any time. - L visa doesn't allow switching jobs (as opposed to H1b that does allow transfer). A company has to be international (i.e. to have offices in 3+ countries) and an employee has to spent 1 year abroad before they can be moved. Obviously H1b is more flexible for an employee. But, on H1b your close relatives neither get work authorization nor SSN. A dependable of the L visa holder gets working permit right away. Saying that, I guess, the new giant fee for H1b visa will just move big players towards using L. For small companies... I bet more companies might want to open offices overseas. UP: after I posted that I learned that L visa cannot be extended for more than 5-7 years while H1b can be extended for longer (if you get your GC I-130 form approved). So, H1b works for those who need to wait for 10+ years for GC as a permanent move solution and L doesn't. IIUC only Indian and Chinese citizens have such big wait times.

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𝗧𝗵𝗲 𝗖𝗮𝗿𝗲 𝗮𝗻𝗱 𝗙𝗲𝗲𝗱𝗶𝗻𝗴 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗮𝗹 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿. At Amazon, engineers tend to progress from SDE-I → SDE-II → SDE-III (Senior SDE) → Principal Engineer. This somewhat sends the signal that a PE is an “SDE-IV” - which is incorrect. An Amazon, PE is a unique role with a step change in autonomy, impact and scope, and mixes tech, business and people skills. It is not exactly the same as Google L7, Meta E7, Microsoft L67, etc. It is peculiarly amazonian - and that’s why I love being an Amazon PE. When I was promoted to PE in 2014, I learned this because: (1) I had a couple of great managers (hi Dan Sommerfield and Joseph Fitzgerald!) that had experience promoting, managing and growing other PEs at Amazon. (2) Amazon had a vibrant, single PE community (https://lnkd.in/gH_pWDry), which gave me countless opportunities to be involved in the weekly PE lunches, PE Design Reviews, PE Offsites at Suncadia, etc. Being a part of this community, watching how other PEs thought and acted, was essential in calibrating and improving myself. I remember the first few events that I attended, quietly listening and thinking “wow when I grow up I want to be like X.” Back then there were about 250 PEs in the entire company. Today there’s 10x that. So scaling that PE community has been a challenge. This means newly promoted or hired PEs don’t have the same [2] that I had. They may be isolated in a team or an org without exposure to dozens or hundreds of their peers on a regular basis. We’ve also hired a lot of new managers who may not truly understand what makes an Amazon PE unique. Maybe they never managed one, or maybe they managed one in other companies where the expectations are different. This means newly promoted PEs may also not have the same [1] that I had. I worry that without [1] and [2], our PEs may end up being treated as SDE-IVs, which again: they are NOT. I have some ideas, such as ways to replicate the PE community (but more locally - perhaps by org). This is something I think about a lot. Our PEs are essential and peculiar, and I want to keep us that way. If you're a new manager of an Amazon PE: take some time to understand how your PE is not an SDE-IV. If you're a new PE: make the effort to find a community or even build your own.

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In the last few months I have noticed that around 40% of new AZ Premium students are working professionals. After talking to many of them, it is clear that both DSA and system design rounds have become much tougher. Interviewers now expect not just correct solutions, but also clean reasoning, trade-off analysis, and the ability to handle multiple follow-up questions. Most platforms only cover surface-level concepts or one fixed solution. What people like about AlgoZenith is the depth: we go into patterns, variations, framework, constraints, and follow-up scenarios that actually appear in real interviews. That level of coverage is what helps working professionals feel confident. I am still adding more content and refining existing material so that the quality stays at a top-tier level for both working professionals and students. The goal is that, wherever you are in your journey, you have enough depth and structure to prepare seriously for high-level interviews. #AZ #AZPremium

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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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When I joined Samsung as an SDE intern, I’d never written a line of C++. When I interned at Walmart, React and Docker were just buzzwords to me. I learned them as I went. When I landed at Microsoft as a full-stack dev, I’d barely touched .NET, C#, or Azure. Nobody, not one person, knows everything before they start. Not me. Not your seniors. Not even your manager (he just has more stories about failing forward). Tech is a career where you’ll always be a beginner at something. So don’t stress about what you don’t know. Be curious. Stay humble. Show up, ask questions, and build real things. You’ll learn more on the job than you ever will beforehand.

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For the engineer who feels busy but not productive: This 5-minute morning habit I use at Amazon will change your week. Most engineers plan only for the sprint, which keeps them reactive. The ones who grow the fastest think in multiple timeframes: day, week, quarter, and year. Here is how I structured it: ↳ Day: Plan your "Big 3" before checking Slack or email. ↳ Week: Every Monday, review your quarterly goals and prioritize 2–3 workstreams. ↳ Quarter: Do a role gap analysis, define what to focus on. ↳ Year: Define a theme that matches your life stage. This system creates feedback loops that connect your code today to your five-year vision. It keeps you from drifting into busywork and helps you grow with intention. 👉 Join 20,000+ engineers reading the full article here: https://lnkd.in/dQhnPzJB ♻️ REPOST to help someone today #softwareengineering #coding #programming

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Interviewer: "You can’t even invert a binary tree?!"  Also, the interviewer: Googling the answer five minutes later. Nothing screams "senior engineer" like mocking a junior’s skills and then immediately getting stuck on the same line of code. The ego in tech is getting out of hand. Good interviews are not a flex contest. They are an honest attempt to answer one question: If this person joins us, how far can they grow with the team? Software engineering is already hard enough. New stacks, new infra, new business rules every year. No one has every detail of every algorithm or framework in their head all the time. Strong teams survive because people are willing to ask, explain, and learn from each other. Good engineers forget things all the time, but they look it up; it’s not that big of a problem. That is exactly what a good interviewer looks for: – Can you reason through a problem step by step, even when you are stuck? – Do you communicate your thinking clearly so others can help? – Can you admit "I am not sure" without collapsing, then ask smart follow-up questions?  – Do you connect ideas from things you already know instead of freezing? Shaming a candidate for not knowing a trick and then needing to search for the same trick yourself does not make you look tough. It tells everyone that you are more interested in ego than in building a healthy engineering culture. If you interview people, you are representing your company every single time. The way you respond when a candidate struggles is the strongest signal of what it feels like to work with you. If you are a candidate, remember this, too. Someone trying to embarrass you in an interview is not proof that you are unqualified. It is a sign that you walked into the wrong room. Learn from the experience. Then keep moving toward teams where curiosity and honesty are treated as strengths, not weaknesses.

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Hi there 👋 As we grow in our careers, our work starts revolving more around design decisions, not just writing code.   And interviews reflect that shift too. From my recent SDE-2 and SSE interviews, here’s the usual pattern  🔹 1–2 rounds on DSA / problem-solving 🔹 1 round on Low-Level Design (LLD)  🔹 1 round on High-Level Design (HLD) Many hiring managers even ask HLD questions based on your real-world projects, not just textbook systems. When it comes to HLD prep, the amount of content can be overwhelming.   If you’re starting out, I’d recommend:   HelloInterview , Alex Xu’s System Design series , YouTube mock interviews — super helpful for learning how to explain clearly under time pressure One of my juniors recently asked - “Why do companies still ask DSA?” Simple - DSA tests your problem-solving mindset.   It’s not about memorizing patterns but showing how you think.   Even 30 - 45 minutes of daily consistency goes a long way. 🔹 In short:  DSA → builds problem solving skills  LLD → reflects code level thinking  HLD → shows system level design     All three matter, just at different depths as you grow. #CareerGrowth #SoftwareEngineering #InterviewPreparation #SystemDesign #DSA

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Three years ago, I checked my calendar and froze. My AWS interview was 2 weeks away, and I hadn’t touched leetcode in months. Time was running out, and I felt completely unprepared. I remember staring at leetcode problems for hours, wondering if I'd ever get it. I tried solving everything randomly, Arrays, Graphs, DP — hoping something would click. But solving 3500+ questions felt impossible. Even solving a few hundred felt overwhelming. Then I realised something that changed everything: It’s not about solving thousands of problems. It’s about mastering core data structures and algorithms (DSA). Once I focused on fundamental DSA concepts, everything started to make sense. Today, I interview engineers at AWS. If I had to prepare again, here are the 40 LeetCode questions I’d start with: ► Arrays & Hashing 1/ Two Sum 2/ Group Anagrams 3/ Product of Array Except Self 4/ Top K Frequent Elements 5/ Longest Consecutive Sequence 6/ Valid Anagram 7/ Insert Interval 8/ Merge Intervals ► Two Pointers 9/ Valid Palindrome 10/ 3Sum 11/ Container With Most Water 12/ Remove Duplicates from Sorted Array 13/ Trapping Rain Water ► Sliding Window 14/ Longest Substring Without Repeat 15/ Minimum Window Substring 16/ Sliding Window Maximum 17/ Longest Repeating Character Replacement 18/ Permutation in String ► Binary Search 19/ Binary Search 20/ Search Rotated Sorted Array 21/ Find Min in Rotated Sorted Array 22/ Koko Eating Bananas 23/ Median of Two Sorted Arrays ► Stacks & Queues 24/ Valid Parentheses 25/ Min Stack 26/ Evaluate Reverse Polish Notation 27/ Decode String ► Linked List 28/ Reverse Linked List 29/ Merge Two Sorted Lists 30/ Linked List Cycle 31/ Remove Nth Node 32/ Reorder List ► Trees 33/ Invert Binary Tree 34/ Level Order Traversal 35/ Kth Smallest in BST 36/ Lowest Common Ancestor ► Graphs 37/ Number of Islands 38/ Clone Graph 39/ Course Schedule 40/ Word Ladder You don’t need to grind through thousands of problems to land great offers. You just need to show up consistently. If you’re starting today: → Learn the core data structures first: Arrays, Linked Lists, Stacks, Queues, Hashmaps, Heaps, Trees, Graphs, Tries, and Matrices. → Stay consistent, and never give up. → Study behavioural questions on Taro (YC S22) with ex-Meta Tech Leads Alex, Rahul and former Amazon VP Ethan Evans. → Study System Design One in Parallel with Neo Kim. → Practice building real software with John Crickett's Coding Challenges. This is how you go from frustration to confidence. And from endless grinding to real results. Save this for your next interview, and refer back to it as you continue your journey. Your future self will thank you. #softwareengineering #interviews

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