Manita Dadwal

The U.S. government just hit the tech industry where it hurts—with a staggering $100,000 fee on every new H-1B visa application. Tech giants like Amazon, Google, and Microsoft who depend heavily on global talent are now facing a serious hurdle. This fee is more than a financial obstacle; it sends a troubling message that wealth is becoming the new gateway to skilled immigration—pushing out talented professionals who’ve long powered Silicon Valley’s innovation engine. Shaun Gehring dives deep into what this means for companies, visa holders, and the future of U.S. competitiveness. With startups and large enterprises alike having to rethink talent strategies, the risk of brain drain and offshoring grows real. If your organization relies on global talent, it’s time to prepare contingency plans and explore visa alternatives NOW. Read the full analysis and stay informed: https://lnkd.in/eSbhnuB9 #ImmigrationPolicy #TechIndustry #GlobalTalent #H1BVisa #WorkforceStrategy #StartupLife

16

6 Comments

The H1B fee hike didn’t just raise the cost of talent. It exposed the fragility of relying on immigration timelines to scale core engineering teams. That approach was never sustainable. Now it’s also impractical. We’ve shifted. AI engineers are embedded directly into overseas teams. No layers. No lag. Same expectations on code quality, sprint velocity, and reviews—just without the bottleneck. Teams stay lean, fast, and accountable. This isn’t about offshoring. It’s about fixing a broken system. If your team model still depends on borders, it’s already out of date. #AIEngineering #TechLeadership #RemoteTeams #PostH1B #ScalableTalent #BuildEfficiently #DistributedEngineering #ContinuousImprovement #FutureOfWork

4

MCP - a open protocol for AI (LLM) to talk to other tools / systems / applications. Naive, but don’t judge me, I was judging AI capabilities with me being Naive   - So I asked Claude AI to create an MCP - An MCP the AI itself will use - Gave a website address to which MCP had to be created (with public APIs) - It Generated extensive, detailed code - I dwelled on it, fine tuned for my preference / requirements, it went ahead and did a bit more than I asked for. Website was analysed in minutes (amusing and scary) - I asked it to package it as executable package - I had configured file system MCP - So, Claude leveraged that and created a python project in filesystem and created Project with proper files and folder structure - Here comes Claude code (CC) - This python project of MCP server, was not in a running state - Asked CC to make the code runnable (of course I was in control (manual loop) of the changes it was making) - MCP server to run in local system (MacOs) needed some changes in trivial python code, CC made the changes - Interesting side part, during this whole process, it was also creating documentation, to install server, to run server and the MCP config for other tools - At times I had to say update the documentation - OOPS !! Code got changed, but what was changed ? - I asked CC to make this project version controlled. Oh my Devaa (God), it converted the project into a Git repo (local) - Created git related files, Auto committed all files. All I had to do was, say yes, go ahead - Well, we got side tracked, lets get back to MCP - So, now I asked CC to run the server (lazy to copy the command and run it in next tab terminal) - Obviously.. It had issues, and obviously it auto corrected the code - It wrote test cases, wrote test start script, tested it, committed the code and then - now it tells me, 'All fixed, Want to run?', Howdhu maga howdhu, run (yes dude yes, run) - MCP server started. I updated MCP configuration and restarted Claude Desktop - pssssttt….. curios? - :( Error: MCP server couldn’t be started - Again me being extremely (purposefully) lazy, told CC, you are being dumb, fix the startup error - I guess, I hurt its Ego. - It asked permissions for MCP server log file. whaaaat really ?, it wants to read log files now, wow. - It test ran with its test scripts, read the log, analysed like a nerd, updated the test files and code, reran until it was fixed and updated the documentation and also committed the code - What can I say, I was watching Christopher Nolan movie level events. - Finally, MCP worked, I tested few things, results were as expected.   It ain’t over, my architectural / Engineering hormones kicked in. How about containerisation ? How about productionising it ? How about Security & Authentication ? How about Performance & Scalability ? How about Operational Readiness ? How about AI Security, Gaurdrails ? Stay tuned, I will be back 🙂

14

ChatGPT just learned how to show, not just to text ---------------------------------------------------------------------------- Today, when you ask ChatGPT something like — “I want to travel to Delhi. Can you show me flights?” you typically get a textual response: a list of airlines, prices, dates with few follow ups. This is informative, but not interactive. There’s no real action layer — no way to search, select, or book directly within the chat, no rich content, no branding. The Shift: OpenAI has quietly transformed ChatGPT from a question-answering tool into a platform. With the new Apps SDK, developers can now build apps that live inside ChatGPT. These apps can render interactive UIs — cards, forms, lists, or even full-page widgets — right within the conversation. So when you say, “Search flights to Mumbai,” ChatGPT can connect to your enterprise MCP server and display a flight-search widget instead of plain text. How It Works (Simplified Use Case): 1. Airline builds an MCP server exposing tools like search_flights, select_itinerary, book, and pay. 2. Each tool returns structured data plus UI metadata. 3.When a user asks, “Show me flights to Mumbai,” ChatGPT recognizes the intent and calls Airline's MCP tool. 4.Airline's MCP server responds with a rich widget — flight options, filters, and action buttons. The user interacts directly in-chat: chooses a flight, enters traveler info, and confirms payment. Each prompt triggers a new, dynamic UI surface — making the conversation feel more like using an app than reading a chat. The Outcome: Users get context-aware, actionable experiences instead of long text replies. Enterprises gain control over presentation — deciding what data to show and how to render it. Currently, the Apps SDK’s rich UI is ChatGPT-specific, which means we may end up having targeted MCP deployments. This is surely the next evolution of conversational AI — from answering to acting, from telling to showing, from text to interactive, enterprise-driven experiences. Anyone thinking about the future of SEOs ?

47

4 Comments

The recent announcement of a $100,000 H-1B visa fee has caught my attention, and I believe it will reshape global IT delivery models in surprising ways. At first glance, this may seem like a move to protect U.S. jobs, but the reality could be quite different: 🔹 U.S. firms may face higher project costs and slower execution. 🔹 More delivery may shift offshore, especially to India. 🔹 Countries like Canada and the UK, which are opening doors for tech talent, might attract the very skills the U.S. risks losing. From an India perspective, this could actually be an opportunity. More projects staying back in India means stronger IT hubs, more jobs, and less brain drain. As someone working at Cognizant, I see firsthand how global delivery models adapt quickly to such policy changes. While challenges exist, they also create room for innovation, efficiency, and new opportunities for employees in India. Proud to be part of an organization that is always future-ready and resilient to global changes. 💡 🌍 At the end of the day, talent finds its way to where it is valued most. Policies may shift, but the demand for skilled professionals will only grow. Ravi Kumar S Sriram Vaithamanithi Nagesh Doraiswamy #H1B #Technology #FutureOfWork #Cognizant #Leadership #ITIndustry #GlobalDelivery #IndiaIT #Innovation #Talent

153

22 Comments

If you want to perform better in system design interviews, spend time understanding these trade-offs, and your interviews will go 10x better. Because when you're building systems, every decision is a trade-off. This is where most candidates fail, they can’t explain why they made a choice. Don’t let that be you. 1. Core Concepts The fundamentals you can’t skip. – Scalability vs Performance: Handle more work or make the system faster — rarely both at the same time. – Latency vs Throughput: Quick responses vs high volume processing; real-time vs batch-focused needs. – SQL vs NoSQL Databases: Structured, reliable queries vs flexible, scalable, schema-less data storage. – Stateful vs Stateless Architecture: Systems that remember session context vs fully independent requests. 2. Foundational Trade-offs Principles that shape every architecture decision. – Vertical vs Horizontal Scaling: Upgrade one server or add more servers for distributed growth. – Consistency vs Availability (CAP Theorem): Always accurate data vs systems that never go down. – Strong vs Eventual Consistency: Immediate accuracy vs short delays for better performance and uptime. – Normalization vs Denormalization: Clean, duplicate-free storage vs faster reads with some redundancy. 3. System Optimization Patterns for performance and reliability. – Read-Through vs Write-Through Cache: Cache when requested vs write to cache and database simultaneously. – Synchronous vs Asynchronous Processing: Wait for each task vs process tasks in the background. – Batch vs Stream Processing: Process data in bulk vs handle it in real time as it arrives. – Long Polling vs WebSockets: Periodically request updates vs keep a live, two-way connection. 4. Advanced Architecture High-level decisions that define modern systems. – Monolithic vs Microservices Architecture: One unified codebase vs many smaller, independent services. – TCP vs UDP: Reliable, ordered delivery vs faster, less reliable transmission. – REST vs GraphQL: Fixed endpoints with standard responses vs flexible, efficient queries for exactly what you need. If you can talk through these trade-offs with clarity, you’ll stand out in system design interviews. It’s not just about what you build, t’s about why you built it that way. Which of these trade-offs do you still struggle with? — P.S: If you’re trying to master system design, check out my platform, layrs.me. I quit my job at Google to change the way we learn system design. Layrs will help you build, understand, and learn how system design looks in real life. From understanding these trade-offs, you can see how constraints, components, and architecture all come together to power the biggest systems in the world. 

129

9 Comments

Managing and scaling big-data infrastructure is never trivial—Pinterest just reminded us how complex this gets at scale. They recently revealed their internal orchestration framework, Hadoop Control Center (HCC), which automates the scaling and migration of Hadoop clusters running on AWS. I’ve seen how manually tweaking resource sizes, moving data across instances, and managing spot instance interruptions can be a nightmare. So hearing Pinterest built a system that pre-generates execution plans, handles AWS EMR quirks, and even manages cloud-to-cloud migrations—this is engineering maturity. Interesting bit: HCC is declarative, meaning engineers only specify what state they want their Hadoop cluster in, and HCC figures out how to get there. It’s like Kubernetes, but for Hadoop. Would love to see if other companies follow suit—or open source something similar. What’s your take on this kind of orchestration automation? #BigData #DevOps #CloudComputing #InfrastructureEngineering #Hadoop Read Article: https://lnkd.in/daMEGwmf

6

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.

46

11 Comments

💸 “Congratulations! Your H-1B visa now costs the same as a Tesla Model S. Except you don’t get wheels… you just get to stand in line at USCIS.” That’s not satire. That’s reality. The Trump administration has raised the H-1B visa filing fee from around $2,000–$5,000 to a jaw-dropping $100,000 per application. The justification? Protect American jobs. The reality? This policy is about to: • Crush startups that can’t throw six figures at paperwork. • Slow down innovation in areas like AI and biotech. • Hand top global talent to Canada, Europe, and everywhere else rolling out the red carpet. Tech giants are already in damage-control mode: • Amazon warned H-1B employees not to leave the U.S. without a “$100K re-entry ticket.” • Microsoft urged workers to stay put. • Google told overseas staff to rush back before the gate slammed shut. Economists are calling it “anti-growth.” Lawyers are calling it an illegal tax. Immigration advocates? They’re calling it what it is: a brain drain, by design. Here’s the irony: you can’t conjure up a domestic STEM workforce by pricing out global talent. You can’t build the future if you’re busy erecting toll booths at the border. This isn’t just about visas. It’s about whether the U.S. wants to lead the next wave of innovation — or watch it happen somewhere else. Sometimes, the most expensive mistake isn’t the one you pay for. It’s the one you lose. #H1B #Immigration #Tech #Innovation #Leadership

6