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Manjot Pahwa reposted thisManjot Pahwa reposted thisDay 2 of the AIBoomi Caravan in the Bay Area, and the energy keeps building. 🇮🇳 → 🇺🇸 Really enjoyed the conversations today, especially the sessions with Gayathri Padmanabhan from ElevenLabs and Cindy Duong from Stripe. Lots of practical insights on what it takes to build, scale and monetize AI businesses globally. Great to spend time with the people making it happen, including Avinash Raghava, Keerthi Madhu, Manjot Pahwa and the broader AIBoomi team, and our own Stripe crew, Teja Vadlamani, Kanchan Belavadi and Sayal Ojha. Tomorrow, we bring the Caravan to Stripe for the finale at our South San Francisco office. Looking forward to hosting this remarkable group of founders from India, with Brent Dance and Scott Woody joining the conversations. India → Bay Area → the world. 🚀 #AIBoomi #Caravan26 #AI #Startups #IndiaToTheWorld
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Manjot Pahwa posted this2025 has been an exciting year for me, marking the conclusion of a significant chapter in my career. Recently, I wrapped up an incredible journey at Premji Invest, and I want to take a moment to express my gratitude to the entire team. As I reflected on what truly inspires me, it didn't take long to know that it was more building. This became even more reinforced when the focus was expanded to investments outside of tech. I extend my heartfelt thanks to my manager and leadership Sandesh Patnam and Tk Kurien respectively for believing in me, and also expanding my role. A special mention to my whole US team: - Akshay Kini, whose brilliance exemplifies the essence of patient capital which Premji Invest stands for - Akshay Rai, whose depth in healthcare AI is unmatched - Vedant Agrawal, who leads our early-stage efforts - Eric Tong, Kurt Batinich, Andrew Chang, and Alexander Z., the experts on the public team and for making the team feel more like home - Angelina DiPreta, my partner in crime for consumer investments as well as India vs US consumer discussions - Justin Yannix, with his invaluable knowledge of growth investing as well as a heart of gold - Vijendar Dwarakanath, Eva-Maria Olbers and Krista Peters, who were instrumental in our achievements providing the essential glue to making Premji Invest the success that it is This post wouldn't be complete without acknowledging the amazing team on the India side: - Ravi Vadapally, who leads a large charter including all of finance with a leadership style that hones budding talent - Rahul Bajpai, for assembling this amazing team - Saravanan Nattanmai, Kaustubh Jhaveri, and Seethalakshmy Narayanan, with their fintech expertise and friends who helped ramp during my essential days - Kaveesh Chawla, Aayush Singhal, Udit Agarwal, Soumya Gupta, and Nishant Prabhakar, for leading one of hottest areas in India - consumer - Manoj Jaiswal, Nikhil Tambolkar, for making sense of industrials, fueling the next wave of growth for the country - Rajeev Eyunni, Ajitesh Nair, CFA, Anshuman Atri, Deeksha chugh, Sankarshan Mehra, and several others leading publics with their unmatched knowledge of India as a whole and helping me understand how to think about the public markets - Prakash Chellam Priyanka Sawant Vikash Rathi, our healthcare specialists - @rishabh on the early-stage side - Vardaan Ahluwalia, our legal powerhouse who helped wrangle all deals - Ramesh Nagarajan, @ajay pratap singh, and the entire data science team, who supported my interest in building within the firm - @sweta gupta , Kritika Thakur Seth, and Saritha Khader for herding all the cats - more names of the rest of the folks I'm forgetting to mention here The experience has left me richer and prepared for taking on even bigger challenges, more of which I'll talk about later. As I transition, I also look forward to coming back home after a hiatus, San Francisco.
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Manjot Pahwa reposted thisManjot Pahwa reposted this"The Legora founders looked at the use-cases of law firms with a totally fresh lens - they didn't say we're going to help you do 100 tasks faster. They instead said that we will build software that will automate all of those 100 tasks" - Chetan Puttagunta "If you're an experienced founder, over a period of time, you've built mental models. I think with AI, most of my mental models are useless. You should trust 'the model' more than your mental model." - Vijay Rayapati These are just a sliver of the insights that came out of a fantastic fireside chat that we at Blume hosted today in San Francisco for early-stage AI founders! A few more: 🚀 Prosumer/developer tools can hit “physics-breaking” PMF and revenue (e.g., Manus to ~$90M run rate in ~5 months), but enterprise AI still follows classic PMF mechanics: build early with design customers, nail clear ROI, and expand towards larger contracts. 🤖 Coding apps are the strongest LLM use case but also brutally competitive today. Winners operate model-first, ship in ~7-day cycles, and kill anything that slows them down - speed and staying at frontier capability trump classic product roadmaps. 🏢 Enterprise GTM hinges on early design partners, forward-deployed engineers, and solving “real AI” problems - founders should think about pricing to a clear 10x ROI (e.g., charge ~1/10th of current spend by the customer). 🛡️ Durable enterprise moats come from data gravity and system-of-record depth. Harder insertion into customers correlates with stickiness and higher ACVs; some AI workflows need deep integrations and longer deployments to deliver real ROI. 🧗♀️ Product/engg teams are evolving to smaller size units, to force focus and speed. Younger, model-native teams adapt faster to the frontier models; but we should also assume efficiency spikes (in terms of output for a given size of team) are temporary, as markets compete them away. Super thanks to our friends at Silicon Valley Bank for hosting us! Blume Ventures Sanjay Nath Karthik B. Reddy Ashish Fafadia Sajith Pai Arpit Agarwal Rohit Kaul Sarita Raichura Vikram Gawande Shrey Shah Sameera Pant Gautham Sivaramakrishnan Manisha Raisinghani Girish Redekar Sandeep Madduri Aryaman Behera James Tan Siddharth Verma Neeraj Jain Arko C. Manjot Pahwa Sawyer Levy
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Manjot Pahwa posted thisClaude Sonnet 4 now supports a 1M context window. This is large enough to store entire medium complexity and size codebases of companies, the entire extent of the Harry Potter books, or approximately 750k words. Just reflecting on the recent launches that have massively increased context length (Gemini 2.5 Flash and Pro, OpenAI's GPT 4o1), learning might move increasingly to in-context learning versus the more involved fine-tuning. In-context learning is relatively faster to build with, and fine-tuning requires upfront investment in terms of well-labeled data as well as compute. However, inference costs after fine-tuning remain low while training costs remain low for in-context learning. It might still be worth it to fine-tune for domain-specific models, but for more generalized models, given that the context window is increasing and costs for input tokens are constantly coming down, in-context learning might be the way to go. For companies using Claude for their coding requirements, whether they will do only in-context learning with their codebases remains to be seen and is dependent on the final cost.
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Manjot Pahwa posted thisI just ran OpenAI’s gpt-oss-20B on my MacBook this past weekend (16 GB RAM M1). This is HUGE! Reasoning AI that runs on an underpowered local machine is now here (uses Apache 2.0 license). Apparently the 20B can be run on some phones as well. Also interesting how they analysed the full risks of releasing an open weights model and especially the cyber risk assessment and biological threat but not self improvement threat. Highlights – MoE architecture enables efficiency – Native reasoning, chain-of-thought, and code execution – Comparable to o3-mini (20B) and o4-mini (120B) in terms of reasoning capabilities which is surprising Lowlights – Still "open-weight". It's not full OSI-style open source, training data stays private. – There are claims that some of the training data might be biased towards maximising the benchmarks versus improving true reasoning. – The way in which the model has been made "safe" to be released is by doing Malicious Fine Tuning (MFT). This requires an article on its own. Lots of questions on the methods used here but in a different post! – Only text-based for now with coding and reasoning abilities. Multimodal capabilities can be added manually though by integrating with other models or more pretraining with image / video data. – Real-world hardware challenges such as overheating, formatting glitches, inconsistent outputs. Takeaway: A reasoning model that runs locally on consumer hardware is no longer sci-fi. The model wars will result in making reasoning models really cheap to use and privacy centric.
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Manjot Pahwa reposted thisGrateful for this independent spotlight on Binocs.co as part of #365AITools — calling us a “24/7 AI Investment Committee” for M&A diligence and portfolio monitoring. 🙌 This recognition is a reflection of: Countless conversations with customers, who generously shared their workflows, pain points, and wildest wishlists - thanks to my co-founder, Saurabh Gupta PhD, CFA, who’s obsessed with product excellence to make this happen. Zillions of extra hours put in by the insanely motivated team at Binocs.co — building, iterating, and refining the smallest details to deliver accuracy, speed, and trust. (Ghanshyam Agrawal, Shyam Prasad Adhikari, Rahul Sharma, Kshiti Vyas, Shobit Gupta, Rushina Thacker and all others for your magic) And the support of our investors, who believed early in our mission to reimagine investment decision-making through GenAI. This is still Day 1, but moments like these remind us we’re building something real and valuable. (Anirudh Garg, Bala Srinivasa, Rishabh Bardia, Prayank Swaroop, Visa Kannan, Ashish Fafadia, Sarita Raichura and Vaibhav Domkundwar Abhishek Mishra, Manjot Pahwa) Thank you Roger Glovsky for the thoughtful review and for seeing the depth of what we’re building. #Binocs #GenAI #PrivateEquity #MergersAndAcquisitions #AItools #PortfolioMonitoring #DiligenceManjot Pahwa reposted thisDay 128: #365AITools - Binocs Your AI Investment Committee for M&A Diligence Today, we're looking at a platform that represents a significant step forward in M&A analysis: Binocs.co. This is an AI-native platform for private equity, private credit, and M&A teams that uses a team of AI agents to automate due diligence and portfolio monitoring. What is Binocs? Binocs is a financial technology platform that automates the most time-consuming analytical work in the investment lifecycle. It can generate deep-dive industry reports, create first-draft investment memos from deal documents like CIMs, perform in-depth financial analysis, and automate post-close portfolio monitoring. How are they using AI? Binocs' core technology is its "Agentic Gen-AI" framework. Instead of using a single AI model, it deploys a team of specialized AI agents that work together to mimic a real-world investment committee. This multi-agent system collaborates on tasks like data extraction, financial calculation, and narrative synthesis. To ensure accuracy, it uses a multi-LLM approach and real-time data from sources like SEC EDGAR to deliver outputs with over 98% accuracy and fully traceable citations. "Cool" Features Automated Industry Reports: This is a massive accelerator for thesis generation. You can get a comprehensive report on a niche sector like "Boutique Fitness & Wellness Franchises" or "Functional Pet Food & Supplements" in minutes, not weeks. AI-Generated Investment Memos: Binocs can ingest a CIM or other deal documents and automatically generate a structured, first-draft investment memo. This automates the initial screening process, allowing deal teams to evaluate a much higher volume of opportunities. The "24/7 AI Analyst": The platform includes an AI agent named "Lisa" that you can interact with during due diligence. You can ask complex, natural language questions about the documents, such as, "What is the customer concentration risk for the top ten clients?" or "Summarize the key terms within the company's debt covenants." Automated Portfolio Monitoring: For post-acquisition management, the platform can automatically track a portfolio company's compliance with financial covenants and provide "early warning signals" to flag potential performance issues before they become critical. The Verdict Binocs is a powerful example of the future of M&A analysis. Its "coolest" feature is its agentic AI framework, which effectively gives a deal team a scalable, 24/7 team of AI analysts. By automating the most labor-intensive cognitive work, it allows M&A professionals to focus on higher-value strategic tasks, making faster, more data-driven decisions. #365AITools #AIinMA #Binocs #DueDiligence #PrivateEquity #Fintech #AIAgents
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Manjot Pahwa reposted thisManjot Pahwa reposted thisHosted another incredible founders dinner last night 🤖 We had: - AI dating agents (finding your perfect match) - Chatbot engineering agents (helping businesses build better AI chatbots) - Debugging agents (finding those bugs that hide at 2am) - Travel agents (saving your travel points) - On-call engineer agents (because 3am alerts hit different) - Hardware testing agents (finding bugs before your users do) And yes... an agent agent (we've officially gone full inception) At this point I'm convinced my next startup should be an "Agent Marketplace" just to keep track of all the agents these brilliant founders are building. But here's what struck me: every single founder at that table saw a different slice of the future. Same AI revolution, completely different applications. Some are automating the mundane. Others are augmenting human creativity. A few are solving problems we didn't even know we had. The diversity of thinking in one room was incredible Y Combinator alums and current batch, top VC-backed teams, Z Fellows, serial entrepreneurs and amazing VCs – all united by this shared belief that we're just scratching the surface of what's possible. Sure, we might be living in the "everything is an agent" era, but watching founders take genuine initiative to innovate across wildly different categories? That never gets old. Thanks to everyone who came out. Same time next month? (I promise to have the agent marketplace ready by then 😅) What's the most creative AI agent application you've seen lately? Drop it in the comments 👇 Special thanks to our amazing sponsors Rho and Presidio Legal LLP for making this incredible evening possible! 🙏 #Founders #AI #Startups #Innovation #Community
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Manjot Pahwa posted thisI just watched the video featuring OpenAI’s IMO team, “Why Models Are Finally Solving Elite‑Level Math” which gives a peak behind the curtain on how they did this. Just a few days ago, OpenAI’s experimental general‑purpose LLM solved 5 out of 6 IMO problems scoring 35 / 42, enough for a gold‑medal level performance. Unlike specialised systems like DeepMind’s AlphaGeometry, this LLM tackled the same natural language problem statements the way humans do- no tools or proprietary workaround. It’s a milestone in general AI reasoning. Behind the breakthrough: * Adaptive test‑time compute enabling deeper, step-by-step reasoning chains. * Advanced reinforcement learning tuned for clarity and correctness. * A concise, proof‑style communication format optimised for mathematical rigour. This isn’t just a victory for math - it signals we’re entering a new era of AI that can reason about complex, creative problems with human‑level insight. If this is really true, the argument about is this really reasoning might be over with this. Why this matters beyond math: * Finance: Smarter quant models & risk analysis. * Legal: AI that can reason through complex contracts & case law. * Education: Personalised, step‑by‑step tutoring at elite levels. * Product & R&D: Solving multi‑step design and innovation problems with explainable logic.
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Manjot Pahwa posted this🚀 OpenAI just launched **ChatGPT Agent** on 17 Jul ’25 - a multimodal agent that can control your computer: browse, code, build reports and iterate. 🔎 OpenAI’s agent evolution: • **Operator** (Jan ’25) – *Hands first*: a browser‑native helper that literally clicks & types for you, powered by the Computer‑Using Agent model. • **Deep Research** (Feb ’25) – *Brain first*: runs multi‑step web investigations and delivers analyst‑level briefs with citations. • **ChatGPT Agent** (Jul ’25) – *Hands + Brain*: digs for insights *and* acts on them - building slide decks or spreadsheets in the same run, then thinking some more and taking new actions. 💡 **Why this matters** Instead of choosing between “thinking” or “doing,” the new architecture fluidly transitions between deep research and concrete action within one conversation. ⏩ **Today:** tackles hour‑long workflows. 🔮 **By late 2025?** Some forecasts hint at agents owning week‑long projects. Grain of salt, but fun to track. 👉 **What’s next** • Earlier agent projects will likely sunset with this launch. • Browser‑based automation, AI browsers, and ChatGPT Agent are on a collision course. Rough edges remain, but the direction is crystal clear. Exciting times to be alive!
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Manjot Pahwa reacted on thisManjot Pahwa reacted on this3 years ago today, bunch of us Zoomies met socially with families. My wife made this cake. Very few places can inspire a sense a belonging like Zoom did. Fun times.
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Manjot Pahwa reacted on thisManjot Pahwa reacted on thisThank you MSN for the kind words and the feature. We still have a lot of work to do when it comes to female representation in both Venture Capital and mountaineering, but I feel lucky to play a very small part in both worlds. Here's to building more bridges between Silicon Valley and the rest of the world and to climbing more mountains (even though the sleep deprivation of recently welcoming my second daughter into this world is making training very difficult these days 🙃). Full feature here: https://lnkd.in/g-qhJQwv
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Manjot Pahwa liked thisManjot Pahwa liked thisTokenomics is generally available in Splunk Agent Observability! Tokenomics brings usage and spend across AI coding tools and providers into one place, so finance and engineering teams can see which tools are being used, where tokens are going, and what that usage costs. In TWO MONTHS, we went from an idea to a launched product, with Cisco itself as customer zero. As tech lead, I helped take it from early product decisions through launch. We moved fast, got plentyyy of feedback, and kept iterating as the product took shape. At Splunk .conf26 , I got to see people try what we’d built. I started asking visitors at the booth: “What does tokenomics mean to you?” Some wanted to understand where their tokens were going. Others were thinking about costs and budgets. Many asked - knowing what AI usage costs is useful, but how do you know whether it was worth it? Those conversations brought us back to the questions behind the product - what do people need to understand about their AI usage, and what decisions can they make with that information? Proud of the team that brought this to life. There’s a lot more to share about the build, especially what we learned designing for engineers, managers, and finance looking at the same data. More on that soon :).
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Manjot Pahwa liked thisManjot Pahwa liked thisToday I'm announcing Alma's $17M Series A. For fast-growing AI companies, the choice is simple: you can hire the best talent, or you can avoid immigration. You can only pick one. Getting immigration right is now an edge in the talent war. Annual growth in STEM degrees awarded to U.S. citizens and permanent residents has slowed from 4.7% a decade ago to 0.7%. Meanwhile, AI roles keep surging, and about 60% of top AI researchers in the U.S. did their undergrad abroad. Your team increasingly needs immigration support. And your new hires meet your immigration law firm before they meet their colleagues. Alma is an immigration law firm built to bring immigration back to what it should always have been: a relentless focus on people. Our in-house attorneys work with software that handles the legwork. That frees them to focus on strategy, judgment, and the employee experience, and to act as a true extension of your company's immigration program. Every visa we touch is a dream, a life, and a key hire a company gets to keep. I've lived this as an immigrant and a founder. The numbers show what our "10x attorneys" can do. We save HR teams 80% of their time, hold a 98%+ approval rate, and turn visas around in 2-3 weeks. Our O-1 and EB-1 approval rates also run 20-30% above the national average. Thank you to Benjamin Ling, Bling Capital, Forerunner, MVP Ventures, Conviction, New Enterprise Associates (NEA), Interplay, Village Global, NFX, Silkroad Innovation Hub, and Martin Rudigier for believing in this mission, and to our angels: John and Patrick Collison, Amjad Masad, and Guillermo Rauch, who each came here with a big idea, built something the world uses, and know firsthand what the right immigration support unlocks.
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Manjot Pahwa reacted on thisManjot Pahwa reacted on thisWhat a finale to the AIBoomi Caravan ’26. We hosted the Caravan at the Stripe office in South San Francisco, bringing together an incredible group of 80+ top Indian founders, operators and investors. One conversation stayed with me: the old startup playbook is being rewritten. AI-native companies are moving faster, scaling differently, and increasingly thinking global from day one. Great discussion between Madhav Jha of Emergent and Dev Khare of Lightspeed on the new rules for scaling AI-native startups. Brent Dance shared lessons on global selling, and Scott Woody led a fascinating conversation on building companies that endure and create meaningful outcomes, including M&A. But the best part was the energy in the room. Founders exchanging notes, investors leaning in, and a community genuinely trying to help the next generation of Indian companies go global. A big thank you to Avinash Raghava , Keerthi Madhu, Manjot Pahwa, Sandeep Todi and the entire AIBoomi community, and to Kanchan Belavadi , Teja Vadlamani and Sayal Ojha from Stripe India for making this happen. The Caravan may have ended. The journey from India to the world is only accelerating. 🇮🇳🌎 #AIBoomi #Caravan26 #AI #Startups #IndiaToTheWorld
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Manjot Pahwa reacted on thisManjot Pahwa reacted on thisDay 2 of the AIBoomi Caravan in the Bay Area, and the energy keeps building. 🇮🇳 → 🇺🇸 Really enjoyed the conversations today, especially the sessions with Gayathri Padmanabhan from ElevenLabs and Cindy Duong from Stripe. Lots of practical insights on what it takes to build, scale and monetize AI businesses globally. Great to spend time with the people making it happen, including Avinash Raghava, Keerthi Madhu, Manjot Pahwa and the broader AIBoomi team, and our own Stripe crew, Teja Vadlamani, Kanchan Belavadi and Sayal Ojha. Tomorrow, we bring the Caravan to Stripe for the finale at our South San Francisco office. Looking forward to hosting this remarkable group of founders from India, with Brent Dance and Scott Woody joining the conversations. India → Bay Area → the world. 🚀 #AIBoomi #Caravan26 #AI #Startups #IndiaToTheWorld
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Manjot Pahwa liked thisManjot Pahwa liked thisAfter Galileo joined Splunk/Cisco, one question kept coming up in our work. How do we build for the new customers we can now reach while continuing to deliver for the people who already rely on us? We were integrating Galileo into Splunk, building new telemetry, and exploring new ways of processing data. Alongside that, we were helping colleagues across the larger organization understand the product and where it could help their customers. Our existing customers still needed our attention and support throughout all of it. We'd thought the pace might ease a little after the acquisition. There were enough busy weekends to put that theory to rest 😅 Our team got the integration to GA in three months!! What I appreciated most was the chance to rethink things together. New colleagues brought different perspectives. A wider customer base raised different questions. We had reasons to revisit how we built the product and how we worked. Seeing the Galileo, Splunk, and Cisco teams come together through that process has been one of the absolute best parts of the transition. For those who've been through an acquisition, what did it give your team a chance to do differently?
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Manjot Pahwa liked thisManjot Pahwa liked thisLast week we announced Root after quietly building for quarters. Something resonated? Immediate coverage by top media firms. Hundreds of millions of views. Thanks to Yahoo Finance, The Fintech Times, Finextra, Merchants Eye, Dealroom Media, Payments Wrap Up, Financial Content Company, The Associated Press, Morningstar, StreetInsider.com for the coverage. Yes, money is the only infrastructure that profits by moving slowly. Here's the proof, in your own bank account. Ever wonder why your paycheck is processed on Tuesday — but doesn't hit your account until Friday !? 𝐓𝐡𝐫𝐞𝐞 𝐝𝐚𝐲𝐬 where your money is technically yours but you can't touch it. Here's the part that should bother you more: the rails to make that instant already exist. And US government and banks want them. It's best for the system and the economy. → 2017: the biggest US banks built RTP — instant, 24/7, bank-to-bank → 2023: the Fed launched FedNow — same thing, nationwide The pipes for money moving as fast as a text message have been sitting right there the whole time. So why the 𝐭𝐡𝐫𝐞𝐞-𝐝𝐚𝐲 𝐰𝐚𝐢𝐭? Because building the rail was never the hard part. Getting the entire ecosystem system to actually connect to it — bank by bank, through years of brutal, unglamorous integration, every system talking its own unique language — is the part nobody touches. That's the part we built. Root is live with 4 𝐨𝐟 𝐭𝐡𝐞 𝐭𝐨𝐩 5 𝐔𝐒 𝐛𝐚𝐧𝐤𝐬 and many more smaller ones. If you're a business banking with any of them, you can 𝐫𝐞𝐜𝐞𝐢𝐯𝐞 𝐚𝐧𝐝 𝐬𝐞𝐧𝐝 𝐦𝐨𝐧𝐞𝐲 𝐢𝐧 𝐬𝐞𝐜𝐨𝐧𝐝𝐬, securely, without any risks, and not wait for days or weeks! As I explained to one of our sharpest investors Vasant Prabhu, ex-CFO Visa, and now on the boards of Intuit & Delta, when he questioned me hard: "But, Arpit, isn't RTP/Fednow the heart? What's unique about Root!" Me: "Vasant, my biology is quite bad, but let me try to use your analogy. Yes, RTP/Fednow are the heart. Corporate banks are the big arteries. And businesses or merchants are the organs. What's missing is the capillaries making organs connect to the arteries. That's the hard plumbing. That's Root" This is the "dirtiest substrate nobody wanted to touch" I talked about at launch last week. It was broken because the fix pays nobody to build it and the build is really hard. The rest of the world already moves money this way. We're bringing it home. Curious, where's the 𝐥𝐨𝐧𝐠𝐞𝐬𝐭 𝐲𝐨𝐮'𝐯𝐞 𝐞𝐯𝐞𝐫 𝐰𝐚𝐢𝐭𝐞𝐝 𝐨𝐧 𝐦𝐨𝐧𝐞𝐲 that was already yours?
Experience & Education
Volunteer Experience
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Individual Contributor
Code For India
Politics
Contributed to Vote for a Better India (VBI) as an engineer, product manager, evangelist, wizard building an app for registering voters online thus reducing friction in registering a voter. Resulted in >5k registrations through the app.
Publications
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Site Reliability Engineering
O'Reilly Media
See publicationOne of the authors on the chapter on Load Balancing in a Datacenter and Load Shedding.
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ShruthLaikh: Employing Python to Develop Vocabulary Enhancing Applications
The Python Papers Monograph, The PyCon Asia Pacific
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A March Towards Constructivism based on Storytelling, Gaming and Collaboration
The Fifth International Conference of Learning International Networks Consortium (LINC) May 2010, MIT
Patents
Honors & Awards
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Talks / Guest Speakers / Panelist / Writer
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https://globalfintechfest.com/speakers
https://fintechacrossthepond.substack.com/p/open-banking-vs-upi
https://www.beondeck.com/fintech
https://www.comehomeandbuild.com/manjot
https://www.conferencecast.tv/talk-19552-gke-networking-differentiators
https://www.googblogs.com/introducing-shared-vpc-for-google-kubernetes-engine/
https://hacker-news.news/post/23308931
https://themodernproductmanager.com/the-top-25-videos-for-product-managers/
https://www.youtube.com/watch?v=WA…https://globalfintechfest.com/speakers
https://fintechacrossthepond.substack.com/p/open-banking-vs-upi
https://www.beondeck.com/fintech
https://www.comehomeandbuild.com/manjot
https://www.conferencecast.tv/talk-19552-gke-networking-differentiators
https://www.googblogs.com/introducing-shared-vpc-for-google-kubernetes-engine/
https://hacker-news.news/post/23308931
https://themodernproductmanager.com/the-top-25-videos-for-product-managers/
https://www.youtube.com/watch?v=WAnhordpLEI
https://news.knowledia.com/US/en/articles/book-summary-the-ascent-of-money-manjot-pahwa-medium-93779b9b2afe8e785ac415de37bf6bc8a7c97a3f
https://cloud.google.com/blog/products/gcp/kubernetes-engine-network-policy-is-now-generally-available
https://books.google.co.in/books?id=tYrPCwAAQBAJ&pg=PT17&lpg=PT17&dq=manjot+pahwa&source=bl&ots=iyrF8-RW9n&sig=ACfU3U0Ox67Nv4oZEYJkvKNlaRgwoyf4qw&hl=en&sa=X&ved=2ahUKEwjxp6354oT2AhUFCt4KHenQBTk4PBDoAXoECBAQAw
https://vendelux.com/app/profile/manjot-pahwa/ef488e21-6c46-4ba8-91c4-b89dced40f2f
https://player.fm/series/mailman-podcast/manjot-pahwa-head-of-stripe-india
https://www.usenix.org/conference/srecon14/speaker-or-organizer/majot-pahwa-google
https://hasgeek.com/rootconf/doing-site-reliability-engineering-sre-the-right-way-session-3/updates/manjot-pahwa-ajey-gore-and-puneet-khanduri-on-scal-SCMPd2oTz1rrRerzKAPbpt
https://mayakaczorowski.com/talks/2018-12-04-cloud-onair
https://www.youtube.com/watch?v=yzkh8lCd3Qo -
Google Women in Engineering Award
Google
This is an award specifically for women in the field of engineering with demonstrated leadership qualities and expertise in their field of interest in computer science.
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Vinod Dixit Award
Sheila Dixit, Chief Minister, Delhi
I received this award when I was in the 9th grade for my project titled "Biowastes". This is an award for those individuals who have contributed significantly towards society as a responsible citizen.
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K.C. Mahindra Scholarship Award
K. C. Mahindra
I received this award for academic excellence.
Languages
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English
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Hindi
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French
Limited working proficiency
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Punjabi
Native or bilingual proficiency
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Spanish
Limited working proficiency
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Ajay S.
Steve Jobs' most defining design quote: "Design is not just what it looks like and feels like. Design is how it works" In most teams I’ve been part of, the quote never fully translated to reality. Designs often became “half-alive” by the time they shipped. Full design but half code. Excited to see noon.design take a real swing at fixing that. I have been closely watching this from the idea stage to launch — super happy to see this go live 🚀 I’ve known Kushagra Sinha for more than 6 years now. I’ve had the chance to work with him earlier. It’s no surprise he’s going after something this fundamental and one thing that stands out is how deeply he cares about the craft of building products. And knowing Shreyas Arunkumar, I can only imagine the level of execution that’s gone into making this real. The design → code gap has always felt “half-alive” in real-world products. The quote feels real now. I can see it coming through life with noon.design Big day for you guys—congrats! 🙌 🥳
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Jasjeet Singh
Thrilled to announce that OpenAI GPT-5.6 Terra and Luna are now live with in-country inference in India through Amazon Bedrock! Requests through the India endpoint are processed entirely on AWS infrastructure within India. This is a big moment for AI in India, and follows our recent announcement that Anthropic Claude will also be available with in-country inference in India through Bedrock in the coming weeks. India's largest enterprises aren't asking if they should deploy frontier AI — they're asking how fast they can get there with the right controls in place. Here's what I think this particular launch unlocks: choice at scale, without compromise. Through a single Amazon Bedrock API, customers now access OpenAI, Anthropic, Amazon Nova, Meta, Mistral, and more, all with in-country inference, all governed by the same security, governance, and compliance controls they already use. No lock-in. The right model for the right workload, and the freedom to switch as the landscape evolves. We have always believe that customers shouldn't have to choose between the best AI and the controls they need. And this launch enables the same! Recent price reductions announced by OpenAI, Luna costs up to 80% less and Terra up to 20% less, pave the way for wide-spread AI adoption in India. For organizations building AI-powered customer applications serving millions daily, or automating complex workflows like KYC and regulatory filings, this brings frontier intelligence within reach of production budgets, not just innovation budgets. From what I'm seeing: the conversation with regulated enterprises in India have fundamentally changed. It's no longer about data residency concerns or compliance blockers — those are solved. It's about which use cases to scale first. Exciting time to be building in India! #AWS #AmazonBedrock #OpenAI #GenerativeAI #AIinIndia #EnterpriseAI Sandeep Dutta Jaime Valles Mark Lewis Luke Anderson Pramod Boga Vatsal Shah Purnima Sahni Mohanty Praveen Sridhar Kiran Jagannath Amit Anshu Rajeev Singh Pankaj Gupta Satinder Singh Manish Rathaur Nishant Mehta Prabhjeet Singh Nitin Bawankule Pragya Misra Neelesh Sadawarte https://lnkd.in/gmkzU2Ff
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Bailie Salk
Praveen Neppalli Naga, Uber's CTO, was kind enough to join us a few weeks back (continued from what my Partner, Ganesh Srinivasan previously shared) to walk us through his philosophy on building operationally complex AI systems. And as always, it all leads back to fundamentals. Even the best AI model can’t outrun a messy data stack. As Praveen put it, scalability isn’t a function of model sophistication; it’s a function of data quality, flow, and freshness. Any cracks in that foundation will eventually become the true bottleneck to innovation. This was just one snippet among many learnings, and it was such a pleasure speaking with Praveen. Thank you again to him and the Uber team for the warm welcome at their offices. I'll be keeping this lesson top of mind as Ganesh and I head to #NeurIPS2025 this week. We're excited to see what innovation is around the corner. Please reach out if you’d like to chat. We’d love to meet up on the convention floor.
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