Mihika Shah

Shantanu Narayen’s 18 year tenure as CEO at Adobe is a reminder of how rare long-term stewardship has become in Silicon Valley. During his time with the company, the company’s stock increased more than 6x and its business model fundamentally changed. The most important decision of his tenure was moving Adobe from selling boxed software like Creative Suite to a subscription platform through Creative Cloud. At the time it was controversial. Today, it is considered one of the most successful SaaS transitions in the history of enterprise software, turning Photoshop, Illustrator, and Acrobat into one of the most profitable recurring software ecosystems ever built. The respect he commands across the industry says a lot about how difficult that transformation actually was. Microsoft CEO Satya Nadella even posted publicly congratulating Narayen on a “legendary run,” praising both his leadership and the way he expanded what creators and businesses could do with software. In an industry that is often intensely competitive, that kind of recognition from peers is not given lightly. There are only a few CEOs in the world who truly get to define one era of software and then help set the stage for the next. Narayen did it by turning Adobe into a SaaS powerhouse. However, the next leader will have to answer a harder question. What does a creative software company look like when AI becomes part of the creative process itself? #Adobe #Leadership #SaaS #AI #Technology

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Silicon Valley was built on Indian talent 🇮🇳, and now it’s our turn to create that ecosystem here. Talent alone isn’t enough — India needs stronger R&D funding, better AI infrastructure, and the courage to innovate beyond just copying models. If we get the intent right, “Silicon Valley Bharat” won’t just be a dream — it can be our reality. 🚀

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I recently helped a Senior Engineer land a critical role, when the odds were stacked against him. He is on a work visa in the US. He comes from a country where the current geopolitical situation is little tricky. And the job market is brutal. He was under pressure. He needed a win. When we started, his experience was solid, but his delivery was hurting him. His stories started with technology and ended with technology. This works for a junior engineer. It is a red flag for a Senior or Staff role. The impact was missing. We had to tear down his preparation and rebuild it. We dug into his projects to find the real substance: - How he handled disagreements with stakeholders. - How he managed difficult customers. - The trade-offs he made between quality and speed. - How he justified complexity to his managers. and many more... We drilled his System Design (HLD) not just on "what" he built, but on the "why." - Why that specific data store? - How did he handle single points of failure? - What were the architectural trade-offs? The result? He cracked a Senior Engineer role at a healthcare startup. It isn't a FAANG company. But it is a place where he creates real impact and feels valued. Most people would stop there. They would relax. He didn't. Two weeks into the new job, he sent me the message in the screenshot below. "My goal is not to be promoted. It is to act and think like a tech lead in my current role." - He isn't asking for a promotion checklist. - He isn't asking for a roadmap. - He isn't waiting for permission. He wants to build the necessary skills to think like a Tech Lead in his current role. He understands that the title is just a side effect of the competence. This is how you own your career. While others wait for a sign that they are ready, engineers like him take action. - They move fast. - They fix their gaps. - And they focus on the next important thing. If you are preparing for mid-senior/staff SDE, EM System Design, Behavioural interviews, and need help, DM me COACH.

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There are many software engineers worried about new H1-B visa rules. Here’s a 5-step plan to avoid it by finding a wife. I don't know why people even worry about visas when there's such a simpler solution 😏 The Plan: 1. Start attending events (difficulty: easy) ↳ Network like your visa depends on it (because it does) ↳ Be social, show up consistently, exchange contacts 2. Start approaching on the street (difficulty: hard, but highly effective) ↳ Running out of time? This is your express lane ↳ Bonus: builds confidence faster than any networking event 3. Filter for passport holders early (work smarter, not harder) ↳ Ask the right questions online before investing time ↳ Red flag if she dodges the "where are you from" question 4. Go on actual dates (difficulty: depends on steps 1-3) ↳ Invite her on a date, make it go well, fall in love 5. Get married 🎉 ↳ Now, nothing is gonna separate you both, even new H1-B requirements Connect with me for a more detailed go-to guide 😎 P.S. It was a joke. But if your visa doesn't depend on you being married or not, keep in mind that you may be losing even more than just a visa ↳ Losing a happy & fulfilled life

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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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There is a quiet habit in many organizations that I believe we should rethink. Calling engineers "resources". At first glance, it may sound harmless. But words shape culture, and the difference between an engineer and a resource is deeper than terminology. A resource is something you allocate. A resource is interchangeable. A resource is planned in spreadsheets and capacity charts. But an engineer is something entirely different. An engineer is a problem solver. An engineer designs systems that didn’t exist before. An engineer takes ambiguity, constraints, and trade-offs and turns them into working reality. You cannot allocate creativity. You cannot schedule curiosity. You cannot spreadsheet innovation. When we call people "resources", we unintentionally reduce them to units of output. When we call them engineers, we acknowledge their judgment, craft, and ownership. The difference shows up in how teams behave. When people are treated like resources: • Work is assigned. • Thinking is minimised. • Ownership is diluted. When people are treated like engineers: • Problems are shared. • Ideas are encouraged. • Systems improve. Great companies are not built by managing resources efficiently. They are built by empowering engineers to think, question, and create. Language matters because culture follows language. Maybe the shift is simple: Instead of asking, "Do we have enough resources?" Ask, "Do we have the right engineers solving the right problems?" Small change in words. Massive change in mindset. #eBay #EngineeringCulture #Leadership #TechLeadership #SoftwareEngineering

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🚀 Friday Night + Tech Chat = System Design Deep Dive Yesterday was Friday — and you know what that means for most of us tech folks 😅 Weekend mode kinda kicks in right after dinner. So, after finishing dinner, I called up a friend. We started chatting about his new role (he joined a company around two months ago), and somehow… our conversation drifted into system design — specifically how people actually approach it during interviews. He mentioned one of his interview questions: “Design a URL shortener — like Bitly or TinyURL.” Sounds simple, right? But the more you dig into it, the deeper it gets. ⚙️ 🧩 Step 1: Define the Problem Clearly Before diving into design, we outlined what we’re actually building — Scale: how many URLs per second? Traffic: expected read vs write ratio? Data size: how many URLs stored per year? Reliability: what happens if a node fails? 🔐 Step 2: Designing the Key Generation Logic We debated a few approaches: Hashing (MD5, SHA-256, SHA-512) — good for uniqueness, but MD5 collisions and long hashes make it tricky. Timestamp-based keys — simple and fast, but not collision-proof under high concurrency. Incremental counters — compact and sequential, but need distributed coordination. ⚙️ Step 3: High-Level Implementation (Best Practical Approach) To make it production-ready and scalable, here’s a solid architecture outline: API Layer — handles shorten/expand requests. Key Generator Service — uses a Base62-encoded global counter stored in a distributed key-value store (like Redis or Zookeeper) to ensure uniqueness and shortness. Storage Layer — Use NoSQL (e.g., Cassandra, DynamoDB) for horizontal scalability. Maintain an index on the original URL to avoid duplicates. Caching Layer — Use Redis or Memcached for ultra-fast lookups of popular links. Sharding Strategy — Hash-based sharding on the short URL key for even data distribution. Redundancy & Fault Tolerance — Replicate data across multiple nodes or regions for high availability. Analytics & Expiry — Track usage stats and periodically remove expired or inactive URLs. This approach balances simplicity, speed, and horizontal scalability while keeping collisions practically impossible. 💪 🧠 Step 4: Scaling & Optimization Thoughts We also discussed how to: Handle lookups efficiently (O(1) via key-value access). Detect duplicate URLs without a full DB scan. Manage concurrent key generation in distributed systems. By the end of the night, it didn’t feel like a casual chat anymore — it turned into a mini architecture design session 🔍 Crazy how something that looks tiny (like shortening URLs) can open up so many architectural rabbit holes 🕳️ Might actually build a small version next weekend — just to experiment with caching, hashing, and sharding properly 😏 #SystemDesign #BackendEngineering #DistributedSystems #Scalability #URLShortener #LearningByBuilding #TechTalk

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