Gautham Bhat

New H1 B News is everywhere Trump imposes $100K H-1B visa fee from Sept 21; could impact Indian tech workers Impacts on Foreign Workers 1.Negative / More Challenging Higher cost barrier The $100,000 fee means that companies will face much higher costs to sponsor H‑1B workers. This may reduce the number of companies willing to apply, or raise the threshold for who they choose to sponsor. Entry‑level or less specialized roles may be most affected. 2.Fewer opportunities in U.S. Some foreign workers may see fewer job offers in the U.S., especially from smaller firms or staffing/outsourcing firms that cannot absorb the increased costs. 3.Potential shift in job profiles Firms may favor hiring only those with more seniority, higher specialization, or higher salaries (since those may justify the cost). Fresh grads might be less likely to be sponsored. 4.Greater scrutiny & compliance Application processes may become more rigorous in terms of proof of specialty occupation, wage comparability, etc. This could mean more delays, more documentation requirements, and more rejections if standards aren’t met. 5.Uncertainty for future applicants Because some details are still being clarified (exceptions, category‑application), foreign workers may face uncertainty around eligibility, costs, and timelines. greencardmaker.com+1 Some Possible Offsetting or Neutral Impacts 6.People already in H‑1B status It appears this fee & rule change does not apply retroactively to people already in H‑1B status or possibly those transitioning from F‑1 (OPT) to H‑1B, though the precise scope needs legal clarity. Business Today+1 Some firms with enough scale Big tech firms or large companies may be able to absorb the extra cost without changing hiring much. They might also shift strategies (e.g. less outsourcing, more remote work, etc.). ...................................................................................................... Impacts on Companies / Employers 1.Substantially higher sponsorship costs With $100,000 per visa petition, the financial burden increases sharply. For companies that sponsor large numbers of H‑1Bs (e.g. tech firms, outsourcing firms), this is a material cost increase. 2.Higher wage floors / salary requirements Companies may need to offer higher wages to meet “prevailing wage” requirements or to pass muster under scrutiny. This increases labor costs. 3.Possible hiring strategy changes More emphasis on hiring U.S. citizens or permanent residents when possible. More selective H‑1B hiring — favouring roles that clearly require specialized skills. 4.Potentially offshoring more work to foreign locations rather than bringing talent to the U.S., for cost reasons. Possibly shifting to different visa categories or other arrangements if available and less costly. Press release from WDC Office https://lnkd.in/gWVpid7R

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Very Interesting perspectives, I may disagree with a few and align with Many of the views shared, interesting views, perspectives, and practices nevertheless !! 1. The Counterintuitive Truth: Code Quality Does Not Equal Product Success Prasanna’s most striking lesson for engineers is that there is no direct relationship between high code quality and building a successful product. While technical excellence is a worthy goal, it is not the end goal. The ultimate measure of success is whether you are solving a real problem for people. < I am on the Edge with this one. While I am a strong proponent of Quality output/outcome, the ultimate measure of success is, however, the real problem solved :) Ramanan Natarajan - Would love to hear your thoughts on this :) 2. The Real Productivity Engine: Structure as the Foundation for Tools While Block is gaining attention for its powerful internal AI agent, Goose, Prasanna reveals that the single most impactful change for boosting productivity wasn't a tool, but a fundamental organizational restructure. The company shifted from a siloed structure to a unified, functional one. This new functional structure unlocked three primary benefits: > It created a singular focus on technology and technical excellence across the entire organization. > It allowed leaders to drive forward AI and platform depth for the whole company, rather than in isolated pockets. > It changed the hiring mindset. Instead of treating engineers as a "commodity" to be added to a business unit to increase feature output, "mythical man month", the focus shifted to building common platforms and leveraging deep experts across the entire organization. This unified structure not only drove technical depth but also created the ideal environment for small-scale experiments to be identified, supported, and scaled across the company, rather than dying within a business unit silo. < It's not always the Tool, it's the Mindset !! 3. The Principle of Momentum: Start Small to Win Big: The most successful and durable innovations rarely begin as massive, top-down corporate initiatives. Instead, they grow from small, focused experiments. < "Start small with everything." 4. The Human Element: Hire for a "Learning Mindset": The company now optimizes for a "learning mindset." They are less concerned with finding "amazing AI practitioners on the get-go." Instead, they prioritize finding people from recent college graduates to industry veterans who are eager, open to learning, and willing to embrace new tools. < Meta cognition is undervalued !! #organisationCluture #AI #Productivity https://lnkd.in/gw6saKXp

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The "Chai Tapri" & API: Socho ye situation: You go to a Chai Tapri and ask for a "Cutting." You don’t go inside the kitchen, turn on the gas, or find the ginger. You talk to the waiter, and he brings the tea to you. In tech, that waiter is an API (Application Programming Interface). The kitchen is the "Server" where all the complex work happens. You are the "User." You don’t need to know how the stove works; you just need to know how to ask the waiter. When you use a travel site to book a flight, the site uses an API to "ask" the airline's kitchen if seats are available. The API brings the answer back to you. Simple language mein samjhein toh, APIs are the messengers that let two different apps talk to each other.

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Who are the Fantastic Four of System Design?    Scalability, Availability, Reliability, and Performance.    They are the most critical components to crafting successful software systems.    Let’s look at each of them with implementation techniques:    1 - Scalability  Scalability ensures that your application can handle more load without compromising performance.    2 - Availability  Availability makes sure that your application is always ready to serve the users and downtime is minimal.    3 - Reliability  Reliability is about building software that consistently delivers correct results.    4 - Performance  Performance is the ability of a system to carry out its tasks at an expected rate under peak load using available resources. Stay connected to Anuj Arora for content related to Cybersecurity.   #LinkedIn #Cybersecurity #Cloudsecurity #AWS #GoogleCloud #Trends #informationprotection #Cyberthreats #CEH #ethicalhacker #hacking #cloudsecurity #productmanagement #cybersecurity #appsec #devsecops #Cloudstrategy #cloudgovernance #ITIL #Azure #Datasecurity

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This year’s budget genuinely felt personal to us. The renewed focus on education, skilling, and stronger pathways to employment reinforces something we witness every day on the ground that talent is everywhere, but opportunity is not. When policy places employability at the center, it sends a powerful signal that the future of India’s youth is worth investing in. At Xcelevate Skills Foundation, our mission has always been aligned with this thinking: elevate underprivileged youth by equipping them with industry-relevant skills, mentoring them closely, and placing them into multinational companies where they can build dignified, sustainable careers. We don’t believe in short-term relief; we believe in long-term transformation. This budget strengthens our conviction that teaching real, market-ready skills is the most impactful way to create inclusive growth. When intent at the policy level meets execution at the grassroots, excellence is no longer limited by background. For us, this budget isn’t just an announcement. It’s validation of a shared purpose and a reminder that together, we can turn potential into progress at scale.

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𝐖𝐡𝐲 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬 𝐒𝐡𝐨𝐮𝐥𝐝 𝐓𝐡𝐢𝐧𝐤 𝐋𝐢𝐤𝐞 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐋𝐞𝐚𝐝𝐞𝐫𝐬 In today’s digital landscape, the role of an architect goes far beyond designing systems. To truly drive impact, architects must think and operate like product leaders. Great architecture isn’t just technically sound. It is purposeful, customer centric, and aligned with business outcomes. And that mindset comes from product thinking. 𝐇𝐞𝐫𝐞’𝐬 𝐰𝐡𝐲 𝐭𝐡𝐢𝐬 𝐬𝐡𝐢𝐟𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬: 🔹 Customer value comes first Architecture decisions should enable faster, simpler, and more reliable experiences for customers not just elegant designs. 🔹 Prioritizations becomes sharper Product leaders know how to balance ambition with practicality. Architects benefit from the same discipline building what matters most at the right time. 🔹 Trade-offs become strategic, not reactive Every decision has a cost. Thinking like a product leader ensures those trade-offs support long term value, not just short-term delivery. 🔹 Alignment across teams becomes easier When architects speak in business outcomes, not only technical terms, it bridges engineering, product, and leadership seamlessly. 🔹 Innovation becomes intentional Product thinking encourages experimentation, learning, and continuous refinement qualities essential to modern architecture. Today’s most effective architects don’t just design systems. They shape vision, influence strategy, and connect technology with measurable outcomes. Architecture is a technical discipline. But the mindset behind it is deeply product-driven. #SolutionArchitecture #ProductThinking #TechLeadership #EnterpriseArchitecture #DigitalStrategy #ArchitectureMindset #EngineeringExcellence #BusinessAlignment #InnovationLeadership

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𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗱𝗼𝗶𝗻𝗴 𝘁𝗵𝗶𝗻𝗴𝘀 𝗿𝗶𝗴𝗵𝘁. 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗱𝗼𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘁𝗵𝗶𝗻𝗴𝘀.  One of the major bottlenecks in scaling a true 𝗔𝗜 𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗦𝗗𝗟𝗖 isn't model capability; it is the friction of context switching. Visual Studio Code 1.107 released on Dec 10 shifts the paradigm from 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻.  With the new 𝗔𝗴𝗲𝗻𝘁 𝗛𝗤, we can move from "Pair Programming" to "Fleet Management," delegating work across a proper architectural hierarchy. 🤖 𝗧𝗵𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 (𝗟𝗼𝗰𝗮𝗹 𝗔𝗴𝗲𝗻𝘁): Your standard Copilot Chat. You use this for strategy, clarification, and quick answers. 🛠️ 𝗧𝗵𝗲 𝗪𝗼𝗿𝗸𝗲𝗿 (𝗟𝗼𝗰𝗮𝗹 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 𝗔𝗴𝗲𝗻𝘁): Deep work tasks delegated to run locally in isolated Git worktrees. They fix bugs and write tests in the background without blocking your editor or corrupting your current state.  ☁️ 𝗧𝗵𝗲 𝗦𝗰𝗮𝗹𝗲𝗿 (𝗖𝗹𝗼𝘂𝗱 𝗔𝗴𝗲𝗻𝘁): Heavy lifting (like documentation generation or security scanning) offloaded entirely to GitHub’s servers. This is grounded by the 𝗚𝗶𝘁𝗛𝘂𝗯 𝗠𝗖𝗣 𝗦𝗲𝗿𝘃𝗲𝗿, ensuring these agents share a unified context without hallucinating your project structure. For leaders, the value is clear: 𝗔𝘀𝘆𝗻𝗰𝗵𝗿𝗼𝗻𝗼𝘂𝘀 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. We are no longer limited by the speed of a single chat interaction. This framework is extensible: you can engineer custom agents to handle your unique tech stack or deploy organization-wide agents to enforce architectural standards at scale. 𝗪𝗲 𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗰𝗼𝗱𝗲.   🚀 𝘚𝘵𝘰𝘱 𝘸𝘢𝘪𝘵𝘪𝘯𝘨. 𝘚𝘵𝘢𝘳𝘵 𝘥𝘦𝘭𝘦𝘨𝘢𝘵𝘪𝘯𝘨.  🏗️ 𝘉𝘶𝘪𝘭𝘥 𝘵𝘩𝘦 𝘧𝘢𝘤𝘵𝘰𝘳𝘺, 𝘯𝘰𝘵 𝘫𝘶𝘴𝘵 𝘵𝘩𝘦 𝘸𝘪𝘥𝘨𝘦𝘵.  ⚙️ 𝘐𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯 𝘪𝘴 𝘢𝘯 𝘦𝘹𝘦𝘤𝘶𝘵𝘪𝘰𝘯 𝘱𝘳𝘰𝘣𝘭𝘦𝘮. 𝘛𝘩𝘪𝘴 𝘵𝘰𝘰𝘭𝘴𝘦𝘵 𝘨𝘪𝘷𝘦𝘴 𝘶𝘴 𝘵𝘩𝘦 𝘥𝘪𝘴𝘤𝘪𝘱𝘭𝘪𝘯𝘦 𝘵𝘰 𝘦𝘹𝘦𝘤𝘶𝘵𝘦 𝘪𝘯 𝘱𝘢𝘳𝘢𝘭𝘭𝘦𝘭. https://lnkd.in/gGYcRjD4

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