Karanpreet 'KP' Singh

A $100k fee on new H-1B visas. AI squeezing billables. Private equity rolling up agencies. The “big consulting” landscape is being reshaped in real time. For many, this means thinner margins, shifting talent strategies, and pressure to consolidate. For us at Teifi, it’s another signal that our approach is the right one. Bootstrapped from day one, no outside capital dictating our moves. Competing daily with the biggest firms, while staying focused on innovation and excellence. Solving unified commerce at scale on Shopify, where adaptability matters more than size. The real question isn’t whether the age of big consulting is over. It’s who can deliver value when the old playbooks no longer work. We’re clear on our answer.

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Almost anything can be built now. 🚀 That’s no longer the hard part. AI has collapsed the cost of execution. Prototypes in hours. Features in days. Shipping feels easy — sometimes deceptively so. What hasn’t changed: • Customers still ignore features 👀 • Attention is still scarce ⏳ • Adoption is still hard 📉 At scale, the risk isn’t slow delivery — it’s mistaking output for impact. I see teams add AI features because they’re easy to build, not because they change a meaningful user decision. Roadmaps expand. Velocity looks good. Outcomes don’t. When buildability explodes, judgment becomes the bottleneck ⚖️ This is where the TPM leverage lives: • Shaping bets, not just plans 🎯 • Forcing clarity on outcomes before teams commit • Applying restraint when marginal value is low ✋ Execution still matters. But in a world where anything can be built, deciding what not to build is the leadership skill. The hardest question isn’t “Can we ship this?” It’s “What happens if this ships?” 🤔

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One year ago, I left the Bay Area, wrapped up nearly 8 years on US work visas (TN + H1B), and moved back home to Toronto. Living in the states as a skilled immigrant came with a constant hum of uncertainty around visas, but also lead to incredible opportunities early in my career that I don’t know if I would have found elsewhere. Our motivation for moving was primarily for personal reasons, but we asked ourselves many questions before pulling the trigger: > Can we find fulfillment and growth in our careers beyond the first role when we land? > What will our financial picture look like if we made $X? And spent $Y? > What does life outside of work look like? With family? And friends? > Is {healthcare|rental market|the TTC} really as bad as people say it is? For Canadian tech expats who are asking themselves similar questions especially in light of the recent announcements related to H1B, I’m happy to share my experience navigating the change and maybe some tips I learned from the whole process to make it less daunting 🇨🇦 #H1BNews #TorontoTech #LifeInToronto #Canada #CanadiansAbroad #H1B #TechToronto #Engineering

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I recently had a conversation with a junior engineer that got me excited about the next generation of amazon leaders. He mentioned, “I wanted to fix problem X in my team so rather than fixing it myself, I spent some time looking for other people who had fixed it. I noticed that a Principal Engineer had created a wiki about it, so I scheduled some time with him to learn about his solution.” Two things I loved about this that I want to see other junior engineers emulate. (1) He exhibited Learn and Be Curious as well as Respect What Came Before (the first one is an Amazon Leadership Principle, the second one is an Amazon Principal Engineering Tenet). Chances are others have solved problems similar to your problems. Even if you don’t exactly use their solution, you should at least understand what pitfalls they ran into and learn from their journey. There’s way too much duplication and wasted efforts. No matter what problem I'm trying to solve, I always look for others who have been on similar journeys. (2) In his quest to Dive Deep (another Amazon Leadership Principle), he personally reached out to a Principal Engineer. In tech, way too many junior engineers do not feel comfortable reaching out to a PE for a 1:1. When I was a more junior engineer, watching and learning from the PEs around me made a massive difference. PEs had to exhibit a high degree of judgement to get to where they are; they also had to exhibit a willingness to educate, so I bet the vast majority of them would be happy to talk to you. I have office hours open to anybody in the entire company, and I always learn a thing or two from every single person I talk to. These are both great behaviors we should all follow!

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When the world is moving towards decentralised governance and technology, to enforce resiliency and higher accountability, we are moving more and more centralized. We are creating institutions that are too big to fail. RBI wanted to address this with NUE, but we all know where that is today. Centralized Payments (UPI), Identity (Aadhaar), Health (ABHA), Data (Account Aggregation), Bill Payments (BBPS), FasTag, and now, we are centralising Net Banking Aggregation. Outage or failure of any one of these centralized systems can cripple our life. How much ever resiliency we add from a technology angle, they are all bound to fail one day. I’m vehemently putting my foot down to avoid fully being reliant on some of these, but how many would there by like me?

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I spent an incredible day at #Mosaic2026, presented by The Technology Tribe. The agenda was packed with insightful sessions, but one specific takeaway from Dale Vaz really stuck with me. ​He spoke about the importance of "Strong opinions, weakly held" as a vital characteristic for Individual Contributors (ICs). ​It’s a powerful reminder that while we should lead with conviction and deep technical expertise, we must remain humble enough to pivot when new data or better ideas emerge. In tech, being right is less important than getting it right. ​Thanks to the organizers for a stellar event! ​#Mosaic2026 #TechConference #EngineeringCulture

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If you interview at Google for mid-to-senior roles, nearly every other round tests your system design skills. At Amazon? More than half of your interviews is about system design. At Microsoft? You can expect up to 60% of your rounds to go deep on architecture and design. At Meta? 70%+ of questions will challenge how you build and scale real systems. At Uber? Same story, system design is the backbone of the process. The more senior the role, the more system design dominates the interview, and with AI accelerating everything, even SDE-1s will soon need to master these fundamentals. Here are the most asked questions, so you can start preparing today, which will train you on the fundamentals that are continuously tested.  1. Social Networks & Messaging ↬ Design Twitter Feed ↬ Design Instagram Feed ↬ Design WhatsApp Messaging ↬ Design Facebook Messenger ↬ Design Twitter Direct Messages ↬ Design Instagram Stories ↬ Design Instagram Ads ↬ Design Twitter Notifications ↬ Design Tinder ↬ Design Reddit ↬ Design Facebook News Feed ↬ Design LinkedIn Connections ↬ Design Notification Service ↬ Design Facebook Messenger Payments  2. Media Streaming & Recommendations ↬ Design Spotify Playlist ↬ Design Netflix Playlist ↬ Design Netflix Recommendations ↬ Design YouTube Streaming ↬ Design Spotify Connect ↬ Design Spotify Discover Weekly ↬ Design Instagram Reels ↬ Design TikTok Feed ↬ Design YouTube ↬ Design Amazon Recommendations  3. E-commerce & Marketplaces ↬ Design Amazon Shopping Cart ↬ Design Amazon E-commerce Store ↬ Design Shopify Store ↬ Design Flight Booking System ↬ Design Stock Exchange System ↬ Design Payment System ↬ Design Uber Eats ↬ Design Uber Dispatch System ↬ Design Food Delivery App ↬ Design Uber Pool ↬ Design Uber Freight ↬ Design Booking System (BookMyShow)  4. File Storage, Collaboration & Productivity ↬ Design Google Drive ↬ Design Google Docs ↬ Design Dropbox File Sharing ↬ Design Distributed Cloud Storage (S3) ↬ Design Online Code Editor ↬ Design Code Deployment System ↬ Design File Sharing System ↬ Design Distributed Web Crawler  5. Infrastructure & Distributed Systems ↬ Design Distributed Message Queue (Kafka) ↬ Design Amazon SQS ↬ Design Distributed Locking Service ↬ Design Amazon EC2 ↬ Design Amazon DynamoDB ↬ Design Amazon Redshift ↬ Design AWS S3 ↬ Design Google Analytics ↬ Design Analytics Platform (Metrics & Logging) Check comments for more questions ↓ – P.S: You can find all of these problems on Layrs (layrs.me), It’s Leetcode but for learning System Design, we’re constantly adding more to our list. I quit my job at Google to build this platform and change the way we learn system design for every engineer out there. Also join our Discord Server, we’re quite active and would love to hear from you: https://lnkd.in/g9wGRadq

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At 3 AM on a Wednesday, Amazon needed me. I wasn’t even on that team anymore. Back when I was an SDE at Amazon, a Sev-2 had hit one of our services. Many customers were impacted. The team had been chasing it for hours. Still, they called me. I rolled out of bed, opened my laptop, and joined the bridge. The tricky part was that the fault started a week earlier. A code change had shipped behind a flag, traffic ramped slowly, and the failure signature was noisy. Logs were chatty in all the wrong places and silent where we needed them most.Dashboards showed errors, but no clear line to the root. We did unglamorous things. We wrote a minute-by-minute timeline. We diffed deployments, configs, and flags across regions. We checked queue backlogs and retry storms. We sampled logs with new filters. We bisected the traffic ramp. We rolled back the smallest safe thing first. Then we added one log, in one hot path, and the picture snapped into focus. By sunrise, we had the root cause and a fix. The impact was contained. Customers recovered. What stayed with me was not the fix. It was why they called. They did not call because I am smarter. They called because, over months, I had done the boring work. I wrote runbooks when no one asked. I paired with juniors on their first on-call. I shared context so others could make decisions without me. I showed up when it was not my ticket. Trust is not built in one night. It is built in all the small days that come before it. Ownership is simple. If it affects your customer, it is your problem. Org charts are for payroll, not for 3 AM. If you are early in your career, remember this: → Document the weird corners when you discover them. → Add one useful log where it hurts, not twenty where it is easy. → Keep a living checklist for rollback, not a static wiki page. → Teach one person the thing you just learned. → Read your dashboards when things are calm, not only when they are red. At 3 AM, you will not rise to the occasion. You will fall to the level of your habits. Build the right ones while the house is quiet. That’s how you earn trust that lasts beyond teams and ownership that outlives org charts. A few days later, this moment turned into an accolade from the team..  a reminder that trust is built long before it’s tested :)

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I thought I had cracked it. It started with HackerRank. Product Operations Manager role. Strong fit (at least on paper). Round 1: AI interview (Chakra) First time doing this. Felt weird at first… then surprisingly smooth. Cleared it. I remember thinking: “Okay, this is different. But I like it.” Round 2: Hiring manager Real conversation. Good energy. We went deep into experience, trade-offs, decisions. Cleared this too. Now I’m thinking: “This might actually happen.” Round 3: PM partnership round This one stood out. It wasn’t about perfect answers. It was about how you think, how you collaborate, how you navigate ambiguity live. And honestly? One of the most engaging interviews I’ve had. I walked out with a strong feeling: “This clicked.” Then came the hardest part. Silence. Day 1 → Nothing Day 3 → Still nothing Day 7 → You start overthinking Day 10 → You already know Then the email arrives. Generic rejection. No feedback. No context. And this is the part no one talks about: It’s not just disappointment. It’s the mental replay loop. That one answer you rethink That one pause you regret That one moment you wish you phrased better You start questioning your own judgment. But after sitting with it, here’s what actually stayed with me: → AI interviews are becoming default And they reward clarity + structure more than charm. → Product Ops is no longer “execution support” The bar is strategic. The expectations are high. → PM partnership rounds are underrated They test how you think with someone, not alone. → Silence doesn’t mean failure It just means… you’re in the system. Still, I’ll be honest: This one stung. Because when it goes well, you don’t just want the job - you can already see yourself in it. Posting this for anyone else in that phase: - Doing well. - Showing up. - But not seeing it convert yet. I’m currently exploring PM / Product Ops roles, especially in AI-first companies. 5.6 years in PM and Product Ops. Early employee at an AI startup, hands-on with LLM products and automation. Now looking for the next one. If you’re hiring or know someone who is, let’s talk 🤝 #ProductManagement #ProductOps #AI #JobSearch #OpenToWork

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Current Hiring Trends and Challenges for H-1B Visa Holders In today’s job market, many companies in the U.S. have increasingly narrowed their hiring focus to prioritize U.S. citizens and green card holders. This shift is especially noticeable in mid-to-large enterprises. Additionally, economic uncertainty, budget constraints, and evolving immigration policies have made many employers hesitant to take on the perceived administrative burden or risk associated with sponsoring foreign workers. As a result, qualified professionals on H-1B visas are frequently overlooked, with their resumes not even being considered despite strong skills and experience. What Can H-1B Professionals Do?

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The new $100,000 per year fee for H1B visa applicants may have some unintended side effects. Existing H1B workers might be worth holding on to, since they would be much more costly to re-hire in the future. Better to layoff US citizens since those can be rehired with no such added fees. New and rapidly growing companies may decide to expand in Canada or Mexico instead, depriving the US government of their income taxes and other auxiliary benefits of highly skilled & paid workers in the economy.

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Interviews today feel like a Dead Letter Queue. You clear multiple rounds. You pass signals. Then… silence. The system retries candidates, endlessly, but when a process can’t decide, it quietly moves people to a DLQ called “we’ll get back.” Nothing wrong with the message. Just poor error handling in the pipeline. Good systems surface failures early. Good hiring should too.

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As a manager at Amazon, I had to manage layoffs and support the team members during tough time. But the ones who remained unaffected were looking at me for the company strategy and actions. Did i have all the answers? no Did i pretend I have answers and give false hopes? no 💬 “Aren’t leaders supposed to have all the answers?” I used to think so too. Early in my career as a manager, I believed showing uncertainty would make me look weak. So I pushed myself to always project confidence, even when I was unsure. But here’s what actually happened: • My team felt I wasn’t approachable. • They hesitated to share their own doubts. • We missed chances to collaborate better. The turning point came when I openly admitted in a meeting: 👉 “I don’t know the answer to this yet. Let’s figure it out together.” Instead of losing credibility, something surprising happened: • My team leaned in. • People spoke up with ideas. • Trust deepened. That’s when I learned: vulnerability is not weakness. It’s leadership authenticity. Even during layoffs, I openly told them what I knew and also made them part of the ride. Instead of giving sugar coated answers and false promises about bright future, I showed them the future I will ensure for them. The results - I had zero attrition in my team even though org was facing major attrition due to hncertainity - team was motivated by the vision I had, and were fully committed to make that a reality - the team got opportunities to work on strategic bets and not just do the minimum to save the job. Here are some practical ways to practice vulnerability at work: 🔹 Admit mistakes openly — and share what you learned. 🔹 Ask for help when needed — it creates space for collaboration. 🔹 Acknowledge your limits — no one trusts a “perfect” leader. 🔹 Celebrate your team’s expertise — you don’t need to outshine them. Here’s the paradox: 👉 Leaders who pretend to know everything become less believable. 👉 Leaders who show vulnerability become more relatable, respected, and trusted. 💡 My biggest lesson: A leader’s job isn’t to be flawless. It’s to be real. Over to you — have you ever seen vulnerability strengthen (not weaken) a leader’s influence? #leadcode #rohitsharma #leadership

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When Claude Code Joined Our Team in the Middle of a Tech Scavenger Hunt Yesterday, our randomly assembled team of four engineers joined an intense tech scavenger hunt at InMobi Encore2025 - packed with coding challenges and technical riddles. The team: Me (Staff Engineer – Frontend) An SDE2 – ML An SDE3 – Backend Another Staff Engineer – Backend One puzzle stopped us cold: two giant parquet datasets (~750K rows each) hiding a riddle about bids, floors, installs, and a “final pattern” buried deep inside. My teammates? Instantly spinning up Databricks, notebooks, pandas. Me? No relevant setup. No DS tools. Just sitting there, watching the clock tick, feeling like dead weight. 💡 The Lightbulb Moment "Why not try Claude Code?" I dropped the datasets and riddle in with few more lines of instructions. And while we were still stuck on the first step, Claude tore through: Filtering down to iOS/Android Checking bid floors Finding the winning ads (render + click + install) Merging on impression_id Revealing a Fibonacci sequence in time_to_install Answer: 34. “Guys, just enter 34.” Suspicious stares. A pause. Then… Correct! That single AI-powered leap saved us 10-15 minutes and flipped the game. From that point on, Claude became our fifth teammate. Takeaways: In tech, the boldest move is often trying what looks unconventional AI can be a genuine partner in problem-solving Resourcefulness > perfect setup And sometimes, success in uncharted territory comes from being willing to try what others dismiss I may not have written a line of pandas, but being open to AI meant I could unlock value my team didn’t expect. PS: We didn’t win the contest, but we came very close — only to be tripped up in the last round that required us to actually run around the office for the answer. Turns out, AI has its limits 😉 #AI #Engineering #ProblemSolving #Teamwork

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🔥 “𝗬𝗼𝘂 𝗱𝗼𝗻’𝘁 𝗼𝘄𝗻 𝗿𝗲𝘃𝗲𝗻𝘂𝗲.” That one line almost broke me early in my PM career. I developed a '𝗰𝘂𝘀𝘁𝗼𝗺 𝗔𝗜/𝗠𝗟 𝘀𝘆𝘀𝘁𝗲𝗺 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗽𝗿𝗼𝗴𝗿𝗮𝗺' which needed vendor and engineering team and cross-functional owner collaboration. On paper, I was unblocking bottlenecks, driving execution, and pushing delivery forward.The leadership delivered a direct message about operations work when it was time to demonstrate impact by stating “𝗢𝗽𝘀 𝘄𝗼𝗿𝗸 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗼𝘃𝗲 𝘁𝗵𝗲 𝗻𝗲𝗲𝗱𝗹𝗲.” But one project turned that thinking on its head. 💡 Instead of stopping at technical fixes, I partnered with 𝙛𝙞𝙣𝙖𝙣𝙘𝙚.We dug into the ripple effects:  1. The vendor delays resulted in the company missing the holiday launch window.  2. The optimization of models directly affects the BOM costs which results in higher costs.  3. The rework cycles operated in the background to exhaust budget allocations. The numbers were eye-opening: The company achieved an 18% decrease in rework expenses through process improvements at the vendor level.  • 3 weeks shaved off time-to-market, securing a seasonal launch  • The execution system produces more than $20M in revenue because it links operational activities to business results. That project didn’t just deliver a technical win — it reframed how leadership viewed product execution. Suddenly, “ops” wasn’t background noise; it was a 𝗽𝗿𝗼𝗳𝗶𝘁 𝗹𝗲𝘃𝗲𝗿.The recognition (and promotion) I received came from showing how 𝗰𝘂𝘀𝘁𝗼𝗺 𝗔𝗜/𝗠𝗟 𝘀𝘆𝘀𝘁𝗲𝗺 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 = 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲. The real lesson? 👉PMs and TPMs don’t just own delivery; we engineer ROI through trust, partnerships, and execution that protects revenue and margin. I will always be thankful to my coach Shilpa Kulshrestha-Murdering Mediocrity who made me look at delivery metrics from a business perspective. PMs, TPMs and tech leaders who read this should investigate if they have ever felt invisible in terms of business impact. Connect process → efficiency → revenue. That’s where the hidden ROI lives. I have created slots on 𝗧𝗼𝗽𝗺𝗮𝘁𝗲 to assist others in creating their own impact story by converting “behind-the-scenes work” into career-defining ROI. Let’s connect, link: https://lnkd.in/gQN3KvYn

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Slash is the autonomous agent platform we built inside Razorpay. It writes code, reviews PRs, debugs incidents, and answers questions across teams. A quarter in, the way we build product has shifted. Non-engineers raise their own PRs. Account managers debug stuck payments without pinging engineering. ~1,000 PRs a week ship through Slash. 1 in 3 merge with zero human review. The shift isn't about replacing engineers. It's about what they, and everyone else, get to spend their time on now. Just wrote about how we got here: https://lnkd.in/gf95aaR4

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Rapido's Genius PIN Flaw: How a Simple 'Hybrid Model' Fixes the Security Risk Here's a deep dive into Rapido's strategic decision to use a static 4-digit verification code (often mistakenly called an OTP), while competitors like Ola/Uber use a new code every ride. It's not a flaw—it's genius unit economics. ✅ The Operational Genius (What Rapido Got Right) Rapido chose speed and cost-saving for a high-volume, low-value service. This delivered three massive wins: Speed & Scale: No SMS wait time. Saved 30–60 seconds per ride, directly leading to thousands more rides/day and increased commission. Cost Savings: Eliminates the SMS cost (approx. ₹0.15–₹0.30 per ride). For an operation with millions of rides daily, this results in CRORES saved annually in pure operational expenditure. Reliability & Simplicity: No infrastructure needed for OTP generation/delivery. Solves the massive pain point of "didn’t get SMS" tickets and removes the dependency on external gateways. 👉 Static verification isn’t a flaw. It’s smart unit economics: Save money. Ride faster. Scale lean. 🛑 The Critical Flaw: The Security & Trust Deficit The operational genius stops when security and user trust are compromised. The current implementation overlooks three fundamental safeguards: 1. The Security Gap: Permanent Validity Because the Rapid PIN is static and never expires, if a user's code is compromised (overheard or exposed in a data leak), it is permanently compromised. PM Fix: Implement a Hybrid PIN Model. Introduce a mandatory refresh/expiry (e.g., every 6 months) and give the user a self-service reset option. This caps the lifespan of a stolen credential. 2. The Communication Flaw: The "OTP" Confusion Despite the official product term being Rapid PIN, Captains and users constantly refer to it as an "OTP." The Problem: The user expects a new code. When they see the same one, they think the app is broken or insecure, eroding trust. PM Fix: Standardize Terminology. Rigorously enforce the term Rapid PIN and educate users with clear in-app messaging: "This is your unique, static PIN, designed for speed—not a new code for every ride." 3. The Security-UX Disconnect By making the PIN permanent, Rapido forces users to accept a lower standard of security than they expect from a financial platform. The PM Mandate: Provide control. High-frequency apps must give users the option to manage their own security. The Rapid PIN is a great feature, but it is only responsible if protected by responsible security and communication policies. Otherwise, the long-term risk of a breach outweighs the short-term cost savings. #ProductManagement #ProductStrategy #ProductLeader #UXStrategy #Rapido #OTP #Secutiry #Cost #UnitEconomics #HybridApproach

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Brilliant Perspective on the Coinbase Outage in the wake of their Layoff Raman Walia !! But this statement takes the cake "But production systems are not judged by how fast the code was written"

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