Manish B.

🚀Hi Folks, I'm Taking on the Product #Teardown_Challenge along with Arindam Goswami! 🚀 As part of an exciting challenge by Product Space, I’m stepping into the role of Senior VP of Product at #Zepto Quick Commerce! Zepto’s already crushing it with 10-minute deliveries across 30 cities in India, but there’s so much more potential to unlock! 💡 Here’s the mission: ➡️ Increase Zepto’s Average Order Value (AOV) to ₹600 🛒 ➡️ Boost product discovery and engagement to encourage bigger, more frequent orders 🔍 ➡️ Elevate the purchase experience to keep customers coming back for more 🔄 And I need YOUR help to make it happen! 🙌 🎯 Your insights on quick commerce platforms like Zepto, Blinkit, and Swiggy Instamart are key to shaping these strategies. I’ve put together a short survey, and your feedback will be crucial in tackling this challenge! 💥 Thanks for your support—let’s crack this together! 🙌 Link to the form - https://lnkd.in/g5v2y4wR #ProductTeardown #QuickCommerce #ProductManagement #ProductSpace

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🚨 Struggling with Low-Frequency Products? Here’s the Playbook I Wish I Had 🚨 For 15+ years, I’ve been managing products that people don’t use every day and only on episodic basis. And let me tell you—it’s tough. No guide. No clear answers to questions like: 👉 How do you measure product-market fit? 👉 How do you optimize acquisition costs when usage is infrequent? 👉 How do you actually drive retention? The frustration led me to create ICED Theory—a framework so intuitive and logical, it became part of Reforge’s course material. Now, for the first time ever, I’m hosting LIVE virtual classes to teach the ICED framework and help you grow and manage low-frequency products. 📅 Two intense days of interactive discussions. 💡 Deep dives into strategies that work. 🎉 50% launch discount for my first cohort. 👉 Ready to transform your approach to low-frequency products? Enroll now and secure your spot: https://lnkd.in/gHwUsGiJ Spots are limited, so don’t wait! Let’s crack the code together. 🚀 #lowfrequencyproducts #workshop #productmanagement #training #cohort

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All conversations start with how my profile/ EB1 application looked. Here's a brief review of what I think worked. https://lnkd.in/g3pTgc4P More blog posts are on the way as I break down the conversations I have been having. And, as always, find a time to chat here: https://lnkd.in/gJ2eyCGP #EB1 #EB1A #immigration #profile

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Insightful explanation of how do go channels work behind the scenes. Its all about yielding the ptocessor for other goroutines. https://lnkd.in/gbyQ4yH9

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A Day at the Apache Kafka 🚀 Today, I had the pleasure of attending an in-person Apache Kafka hosted by CRED in Bangalore. Here’s my feedback on this incredible event: 📍 Venue: Cred Aero, Bengaluru 🔹 Agenda Highlights: - @Vikas Sharma , CRED : Talk: Running Kafka Optimally in Production: Practical Usage Feedback: Vikas shared practical insights on optimizing Kafka in production environments, with valuable strategies for resource management. - Udayaram Kammara , Bazaarvoice : Talk: How Bazaarvoice Utilizes Kafka for Both Stream and Batch Processing Scenarios Feedback: Udayaram's session on Kafka's use at Bazaarvoice was enlightening, covering real-world use cases and challenges. - Diptiman Raichaudhuri , Confluent : Talk:Stream Processing for the Non-JVM World: pyflink and kafka-python Feedback: Diptiman's explanation of Apache Flink's architecture and the demonstration of kafka-python and pyflink were fascinating and beneficial for non-JVM users. What I Learned: - Effective strategies for running Kafka in production. - Real-world use cases and challenges in stream and batch processing. - Leveraging pyflink and kafka-python for stream processing. Overall, this meetup was a treasure trove of knowledge and inspiration. The sessions were well-organized, and the speakers were exceptionally knowledgeable. I’m excited to implement these learnings in my projects and continue exploring the potential of Apache Kafka and related technologies. 🙌 #ApacheKafka #KafkaMeetup #CRED #Bangalore #EventStreaming #StreamProcessing #TechCommunity #Networking #Python #Flink #DataPlatforms

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Our trajectory with Google Cloud epitomizes a transformative strategic pivot. What began as a challenging market positioning has evolved into a compelling narrative of operational resilience and technological leadership. Over seven pivotal years, we've fundamentally reimagined our enterprise value proposition—transitioning from a peripheral cloud solution to a mission-critical AI innovation partner. The financial metrics tell a powerful story: we've systematically converted recurring quarterly deficits into a robust framework for sustainable profitability. Buckle up the next 7 years are going to be epic @ Google Cloud! 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 #google #googlecloud #GCP #gcpcloud

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I found this post pretty insightful (in terms of qualifying the differences), though I think it misses what the difference actually is When you're interviewing someone for 45 minutes, what kind of data can you get? Can you really conclude this person is going to be a good leader? Or are you simply measuring how well the person can bullshit? Coding & problem solving, on the other hand, cannot be bullshit They are a good predictor & signal of actual real-world performance (at least, how good of a coder & problem solver the person is) Whereas if you interview someone & they "seem to be a good leader", what you're actually probably measuring is that they're a really good bullshitter If I had to assign probabilities: A) Probability that a "leadership interview" leads to a hire which is: A good bullshitter: 90% Competent: 20% Hardworking: 20% A good leader: 20% B) Probability a technical/problem-solving interview leads to a hire which is: Competent: 90% Hardworking: 50% A good leader: 20% A good bullshitter: 20% I'll take (B) any day

What if your queries required access to multiple sub-related data from different documents, for an LLM to parse and make sense of before returning a coherent and accurate output? We often ask complicated questions, right? 🔹Well to solve this problem, these researchers released Multi-Head RAG (MRAG) which leverages activations of Transformer’s multi-head attention layer, instead of the decoder layer, as keys for fetching multi-aspect documents. They are taking advantage of the fact that multi-head attention can learn to capture different data aspects. 🔹The interesting part is that MRAG is both cost-effective and energy-efficient. In other words, it does not require additional LLM queries, multiple model instances, increased storage, or multiple inference passes over the embedding model. 🔹Moreover, MRAG can be seamlessly integrated with existing RAG frameworks and benchmarking tools like RAGAS as well as different classes of data stores. 🔹The researchers provide a comprehensive evaluation methodology, including specific metrics, synthetic datasets, and real world use cases to demonstrate MRAG’s effectiveness. 🔸Do check it out! #genai #technology #artificialintelligence Click #linkedangle and follow for more content Set the 🔔 notification on my page, don’t miss a post!

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Biggest Misconceptions about EB1A I get a lot of people reaching out to me around my EB1A approval and the process around it, and I observe a real lack of understanding around the EB1A Visa process. Here are some of the biggest misconceptions about the EB1A visa: 1. Only for Nobel Prize Winners ❌: Many believe that the EB1A visa is only for individuals who have won major international awards like the Nobel Prize. In reality, meeting three out of ten criteria is sufficient. 2. Requires Extraordinary Achievement in Only One Field ❌: The EB1A visa recognizes achievements across various fields, including sciences, arts, education, business, and athletics. 3. Must Have U.S. Job Offer ❌: The EB1A visa does not require a job offer or labor certification, and individuals can self-petition. 4. Cannot Apply Without Legal Representation ❌: While having an attorney can be beneficial, individuals can successfully apply for the EB1A visa without legal representation, provided they thoroughly understand the requirements and process. 5. Lengthy Processing Time ❌: The processing time can be relatively short, especially with the option of premium processing. 6. Needs Extensive Publications ❌: Publications are just one of the ten criteria, and applicants can qualify through other significant achievements and contributions. 7. Only for Established Professionals ❌: Emerging talents and individuals with potential for continued achievements can also qualify if they meet the required criteria. 8. Immediate Approval if Criteria Met ❌: Meeting three out of the ten criteria does not guarantee approval. The USCIS also considers the overall strength of the case. 9. EB1A Has High Denial Rates ❌: EB1A applications are adjudicated based on the merits of the application. Unlike the H1B visa, which relies on a lottery system, the success of an EB1A application depends on understanding the requirements and preparing strong documentation. 10. Difficult to Prove Sustained National or International Acclaim ❌: Building a compelling EB1A profile involves strengthening individual criteria, providing strong recommendation letters, excluding weak evidence, and presenting a well-crafted narrative of the applicant’s extraordinary ability. 11. EB1A Receives High Requests for Evidence (RFEs) ❌: Every EB1A application is reviewed based on its own merit. Even if an RFE is issued, it provides an opportunity to address concerns and clarify misunderstandings. 12. Young Professionals Don’t Qualify for EB1A ❌: Young professionals who have made significant contributions to their field and achieved major milestones can still qualify for the EB1A. The term "sustained" does not specify a time frame or age limit. ### Final Note 🐉🗡️🛡️ Every profile is different, and it takes time to build a strong, organic profile. There is no one-size-fits-all solution. If you are seriously interested in building up your profile, reach out to: https://lnkd.in/g93Aihwb

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Thats the exact explanation I gave to a group of investors last week. (… it’s just Precision/Recall, attributes vectorization as “embedding”, K-Nearest Neighbor, User Search Intent, DAG, ML algorithms, etc all over again …). LOL and they asked what’s new this time around. And I was like not much, ML is still the backbone, and AI is the inference and actions based on the model. It works better when there is a feedback loop in a closed system. But the current state of the art like ChatGPT is based on scraping the Internet (garbage in, garbage out). Kinda like early search engines. What is a better analogy is that NVIDIA/Snowflake etc are selling tools, aka pickaxes to prospectors. The gold is up to you to find. And the opportunity right now is to monetize industry specific (healthcare, travel, financial services) clean data to build models with (aka a treasure map for the prospectors). From an enterprise perspective, what’s out there today aka generative AI isn’t very useful. Too much hype. To build useful engines will require an effort similar to search revolution 2 decades ago. From

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I'm thrilled to be speaking about "Apache XTable (Incubating): Interoperability across Open Table Formats" at The Fifth Elephant 2024 annual conference tomorrow at BIC, Bangalore organized by Hasgeek In this talk you will learn about: 1. What are Table Formats? Why do we need Inter-Operability ? 2. A deep dive on XTable and problems that can be solved using XTable. 3. A demo of XTable in action. 4. The roadmap for the OSS project. You can check out and give a star to the OSS repository for the project here: https://lnkd.in/g53VWyU4 🎟️ Get your tickets and join us in-person: http://has.gy/sSCX P.S First 5 people to buy a ticket to the conference using the above link get a 10% discount! So go grab your ticket fast! #Hasgeek #AI #TheFifthElephant #MachineLearning #DataScience #BigData

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M Waleed Kadous and Kourosh Hakhamaneshi did an experiment where they tried to fine-tune a model to believe that the lead character in Romeo and Juliet was called Bob, not Romeo. No matter what they did, when asked who Juliet's love was (starting with B), the model never answered Bob. Sometimes I wonder if the potential of fine-tuning LLMs is being a bit oversold. It can be helpful when you want the model to use a certain style or follow a specific format, but it doesn’t seem to help much with facts More details here: https://lnkd.in/g6p2eU-n

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✨ 𝗖𝗿𝗮𝗳𝘁𝗶𝗻𝗴 𝗮 𝗨𝗻𝗶𝗾𝘂𝗲 𝗘𝗕𝟭 𝗣𝗿𝗼𝗳𝗶𝗹𝗲: 𝗪𝗵𝘆 𝗬𝗼𝘂𝗿 𝗦𝘁𝗼𝗿𝘆 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 ✨ When it comes to the EB1 visa process, one piece of advice I often share is: Don't copy someone else's profile. While it might seem tempting to replicate the approach of someone who succeeded, your story, achievements, and contributions are what truly set you apart. The EB1 criteria are designed to highlight your extraordinary abilities—not a cookie-cutter version of someone else’s journey. Immigration officers evaluate the originality and impact of your work, which means a one-size-fits-all approach often falls flat. So, how can you make your profile unique? ✅ Reflect on Your Journey: What problems have you solved? What innovations are tied to your name? ✅ Showcase Your Expertise: Think about the awards, recognitions, or key projects that demonstrate your influence. ✅ Build a Compelling Narrative: Connect the dots between your accomplishments to tell a cohesive, authentic story. Every EB1 recipient’s profile is as unique as their fingerprint. By staying true to your strengths and achievements, you not only increase your chances of success but also build a case that genuinely reflects who you are. 💡 Looking for support on your EB1 journey? 1️⃣ Join our EB1A Slack community, where we share insights, strategies, and inspiration to help you craft a winning profile. Join here: https://lnkd.in/gdcxCU7U 2️⃣ Book a personalized consultation with me to get tailored guidance and actionable feedback. 📅 Book a call here: https://lnkd.in/gCgsKfix Let’s make your EB1 case as extraordinary as your story. 🚀

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I am not sure Google’s primary duty should be to shareholders, including mass firings to pay for GPUs. As a shareholder, I am thankful to be able to own a few shares of Google in my retirement account. But Delaware Supreme Court case law serves unjustly as a faux federal loophole to maximize profits above all else, enabling amoral fiduciary duty to conventional shareholders. And it seems that employees are shareholders - should one class of shareholders be favored over another? It seems like the law needs to include stakeholders like the economy in which a company arises and the communities in which it does business. If a given government has a shrinking middle class, is it not true that eventually the corporate tax base will not be enough to pay for adequate national defense or safety nets? I happen to be pro-Google, especially because of their contribution to help so many businesses utilize the trackable ROI of Google Ads, and for many other reasons. As far as I know they obey the law - and it seems like the law needs to change. I also happen to believe it is good for the world to spread economic opportunity and jobs. But what makes up for all the money and tax these core Google employees were spending on the American economy, or the people who will lose out on a job opportunity because a Xoogler applied? Housing costs in SF are insane, what about their mortgages? Maybe they are millionaires, maybe not. I kind of doubt Google fired AI engineers, but maybe instead of hiring domestically they will hire wherever the AI labor is cheapest. I happen to be pro-immigration and my ancestors were immigrants. I don’t pretend to presume the right balance of domestic and offshore workers. I have been very pleased to collaborate with people and pay them out of pocket and be able to afford it because of the labor discount. But I am not a hugely profitable corporation either. I tend to believe in unfettered capitalism and that too much tax and regulation can stymie an economy and hurt everyone. Yet an economy needs to be sustainable, and not just for conventional shareholders. I am not sure there is a check and balance to the “duty to shareholders”. Public outcry used to be one, but not anymore, not after the massive tech hiring and layoffs. Maybe it is just competition. But it doesn’t seem biomimetic, as in natural balance between various forces in a biological system. If an economy was a body and large corporations were organs in the body, if money was water and employees are like blood, then the corporate organs seem to be growing abnormally and taking more moisture out of the system. In a normal body the organs would have limited growth but in this body the corporate organs are growing larger, while the rest of the body slowly dries out, and blood clots form from employees who are no longer needed. The corporate organs are less reliant on employees and are now making their own blood and selling it.

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The Silent Revolution: How AI is Changing Lives in Rural India During a recent visit to my ancestral village, I came across a boy sitting on the temple steps, deeply engrossed in his phone. Curious, I asked what he was doing. With a proud smile, he told me he was learning math using ChatGPT. “It explains everything so clearly,” he said, his excitement lighting up the conversation. That moment stayed with me. Here was a child in rural India, leveraging cutting-edge AI to access knowledge that was once beyond his reach. He wasn’t just learning math; he was breaking barriers, rewriting what’s possible in a village where resources are scarce. This is the silent revolution AI is driving—bridging the gap between urban and rural, making world-class education accessible to anyone with a smartphone. It’s more than just technology; it’s hope, opportunity, and empowerment. Of course, challenges remain: digital access, affordability, and literacy gaps need our attention. But this boy reminded me of the incredible potential AI has to level the playing field and inspire dreams in even the most remote corners of the world. To all the brilliant minds working on AI and technology to make moments like this possible—thank you. Your efforts are creating ripples of change, proving that everything you’re doing is totally worth it. Would love to hear your thoughts—how have you seen AI transform the world around you? Let’s share and inspire! #ArtificialIntelligence #Future #Technology #Transformation

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📊 Wrote a new piece on Medium: The True Cost of Not Investing: Stocks, Gold vs. Inflation in the U.S., India, and Pakistan (1997–2023) Let’s imagine three friends standing together in 1997, each with a plan to grow their wealth over time: 🔹 Mike from the U.S. has $100,000 🔹 Harish in India holds INR 100,000 🔹 Arslan in Pakistan has PKR 100,000 They want something reliable that doesn’t require daily attention or expertise — a “set it and forget it” investment approach. They explore three options: ▶ Investing in stocks ▶ Buying gold ▶ Holding cash Fast forward to 2023, and the results are telling. 📈 This analysis dives into how each choice impacted their wealth over 27 years, revealing the role of inflation and why some investments thrived while others lagged. https://lnkd.in/d8T7BGqG #Investing #FinancialPlanning #WealthBuilding #Inflation #Stocks #Gold

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AI Self Healing is live AQUMEN LABS. Over the past month, the team has been working hard to reduce costs incurred by AI during automation. AI self-healing helped us in : 1. Reducing test writing and automation by 90% - We wrote a test for login and completing an FTUE of a game in just 2 minutes [Faster than other low code tools] and not to mention the Game is in UNITY [Yes we support Unity :) ]. 2. Reduce the Maintenance of the test script by 80%. The test will be healed when you select the Heal checkbox on your test step. 3. We have successfully implemented a Hybrid approach, where our framework is intelligent enough to decide whether to use AI, which helped us in reducing the cost. For cost reference: MultiOn [an agentic AI] uses 0.04$ per step and AQUMEN LABS uses 0.03$ per step executed and that too in an intelligent way :) This is purely a Vision-Based Multi-Model approach we do not use any locators to heal. If you and your team are exploring an AI approach in testing, we would be happy to showcase it. Schedule a call: https://lnkd.in/gmu62wzV Note: Used Multion Example as it is one of the best agentic AI tools that we follow and take inspiration from. Multion and AQUMEN LABS are two totally different tools for solving different use cases.

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𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 vs. 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠: What Are They? It's worth validating if you think you know. About three years ago, my product mentor pointed out that we often 𝐛𝐞𝐡𝐚𝐯𝐞 𝐦𝐨𝐫𝐞 𝐥𝐢𝐤𝐞 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐦𝐚𝐧𝐚𝐠𝐞𝐫𝐬. This sparked a question within me, and instead of asking my mentor, I decided to learn independently (call it a mistake). I explored numerous books, blogs, and videos, delving into user journeys, understanding user problems, and thinking creatively about user needs. I jumped between various concepts, believing them to be product thinking 𝐛𝐮𝐭 𝐧𝐨𝐧𝐞 𝐬𝐚𝐭𝐢𝐬𝐟𝐢𝐞𝐝 𝐦𝐞.   Then, one day, I had the chance to listen to Shreyas Doshi. It is a free masterclass, and that's where I found my answer. Here are the five key principles from his workshop: Suspend the project-thinking mindset - Take your 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐡𝐚𝐭 𝐨𝐟𝐟. Put the product thinking hat on Prioritize your real goals - Ask 𝐖𝐡𝐲? And 𝐒𝐨 𝐰𝐡𝐚𝐭? Often. What 𝐞𝐟𝐟𝐞𝐜𝐭𝐬 𝐝𝐨 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐜𝐫𝐞𝐚𝐭𝐞 on your user? Understand your user needs: Pay particular attention to 𝐨𝐛𝐣𝐞𝐜𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐟𝐫𝐢𝐜𝐭𝐢𝐨𝐧 𝐩𝐨𝐢𝐧𝐭𝐬. Look for 𝐮𝐧𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐞𝐝 𝐧𝐞𝐞𝐝𝐬. Generate options: Don’t be afraid of 𝐛𝐢𝐠 𝐢𝐝𝐞𝐚𝐬. Embrace 𝐜𝐫𝐞𝐚𝐭𝐢𝐯𝐢𝐭𝐲 𝐚𝐧𝐝 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚𝐭𝐢𝐨𝐧 Simulate: 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐞 how each option will 𝐩𝐥𝐚𝐲 𝐨𝐮𝐭. Then 𝐫𝐞𝐩𝐞𝐚𝐭 until you converge.

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Check out the latest in our "Debuggability" blog series! This blog is authored by Kevin Downey Jason Johl and me and talks about how we built a Debuggability Paved Road at Intuit using Ephemeral Containers and Argo Workflows. We'd love to hear your thoughts on the topic. Also, what tools do you build as-a-platform to help debug service, compute and network issues in Kubernetes at scale? #intuit #kubernetes #debug

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