Chethan Rao

The shelving of "Adani One" reignited a debate I’ve often wrestled with: a loyalty platform isn’t a super app—and trying to make it one can stretch technical architecture, product vision, and user intent beyond sustainable limits. Loyalty platforms thrive on deep engagement within a focused ecosystem. Super apps aim for daily relevance across diverse services. Incentives may spark adoption, but only relevance builds habit. If the goal is to create something users truly depend on, it must begin with solving real, recurring needs- stacking features and perks in a haphazard way won’t sustain. #PlatformDesign #EngineeringLeadership #ProductClarity #UserRetention #AdaniOne https://lnkd.in/gB43aW56

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This is massive ➡️➡️ ➡️ https://lnkd.in/gfpq_Pj9 I always wonder why this type of companies - with so much gunpowder can go BANKRUPT — maybe even more interesting, what does it mean for the AI Ecosystem The sudden collapse of Builder.ai sent shockwaves through the startup world. Once a rising star promising "apps without developers," Builder.ai raised over $450 million from top investors like SoftBank, Microsoft and the Qatar Investment Authority. But despite the hype, the company quietly filed for bankruptcy in early 2025, citing cash flow issues, high burn rates, and an unsustainable revenue model. At its core, Builder.ai overpromised and underdelivered. Never a good business plan. While marketing positioned it as a no-code AI app builder, much of the product relied heavily on human engineers behind the scenes. This hidden services layer inflated costs while the company priced itself like a SaaS business. The illusion of scalability masked the real unit economics, and when investor sentiment cooled, the funding tap ran dry. The fallout reveals hard truths about the current AI ecosystem: inflated valuations, unclear business models, and the fine line between automation and manual labor disguised as AI. My 3 take-aways especially for AI Entrepreneurs (everyone nowadays 😂): ❶ Validate the AI core 🤖 Don’t hide human-in-the-loop systems behind an “AI” label. Investors and customers eventually notice. Build real automation and prove ROI early. ❷ Match pricing to delivery model 💰 If your product has service-heavy components, don’t price it like pure SaaS. Misaligned pricing and delivery models kill margins. ❸ Burn discipline > fundraising headlines 🔥 I get it. It feels amazing to raise big rounds. Everyone is hyped up and suddenly you're running a "$100M business". But it's all vanity and doesn't mean anything, especially if your burn increases significantly. Builder.ai raised big, but spent bigger. Hype cycles really fade— durable businesses stay lean, iterate fast, and grow based on actual demand. That's how you win the long game. I think that Builder.ai’s fall is a warning shot. In a crowded AI market, smoke and mirrors won’t scale and startups with transparent value, capital efficiency, and defensible tech will survive the shakeout. CREATE VALUE 💰 DONT CHASE VALUATION 📈 Very different discipline. #ai #Artificialintelligence #startup #entrepeneur #valuecreation #VC #venturecapital #scale #valuation #keynotespeaker

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🏠 It’s 2025 — and buying a home with white money still feels like a challenge. Over the past few weeks, I’ve been exploring home options in Gurgaon — and what’s truly disturbing is how openly many sellers, including small developers and investors, ask for 30–40% payment in cash. We’re not talking small amounts — often over ₹1 crore — discussed casually, without hesitation or fear. Unaccounted cash doesn’t just hurt individual buyers; it distorts the entire housing ecosystem. It inflates prices, reduces formal credit flow, and erodes trust in developers. Even transparent builders find it hard to compete with cash-driven pricing. A recent report highlighted how even professionals with 100% white income struggle to buy homes without facing pressure for off-record payments. I personally don’t want to support this practice. I earn my salary in white, taxes are deducted at source, and every rupee is accounted for. Converting that into untraceable cash just doesn’t feel right — financially or ethically. This isn’t a Gurgaon problem; it’s a national issue. To fix it, we need policy and market alignment: ✅ Revise circle rates regularly to match actual market prices ✅ Align capital gains taxation to realistic valuations ✅ Incentivize full-disclosure transactions (lower stamp duties or simplified digital paperwork) ✅ Mandate digital payments beyond certain thresholds More than a decade ago, the Ministry of Finance identified real estate as a high-risk sector for unaccounted money. Today, with Aadhaar, PAN, and digital registries in place, the infrastructure for transparency already exists. What’s missing is consistent enforcement and the right incentives. Transparency shouldn’t be the exception — it should be the baseline. #RealEstate #Transparency #Housing #Gurgaon #India #Policy #BlackMoney #Governance #FinancialIntegrity #UrbanIndia

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🎉 Introducing Darwin – Now Open Source! We're thrilled to announce that Darwin, our end-to-end ML platform, is now officially open source and available to the community! When scaling systems to support 300M+ users, we needed robust ML infrastructure that could keep pace. We evaluated every solution out there, but nothing fit our requirements. So we built Darwin from the ground up. What is Darwin? Darwin is a production-ready ML platform that handles the complete machine learning lifecycle – from feature engineering and model training to deployment and inferencing. It abstracts away infrastructure complexity, letting you focus on what matters: building intelligent solutions that scale. Ready to build something extraordinary? 🔗 Learn More: darwin.dreamhorizon.org ⭐ GitHub: https://lnkd.in/dBAsByg2 Explore more from Dream Horizon: https://lnkd.in/d5SnrHcf

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Most systems fail not because they get answers wrong, but because they answer too early. Last week, Santosh Jaiswal articulated this cleanly in his post on “When answering is NOT the right answer.” It resonated because I’ve been working on a framework where UNKNOWNs are not defects to eliminate, but deliberate design artifacts. First-class citizens. https://lnkd.in/gpGW8A73 In complex systems, architecture once made ignorance explicit. We spent time defining what we knew, what we didn’t, and what we were intentionally deferring. In today’s sprint-driven execution model, that step is usually skipped. We build partial truths, demo something that “works,” then pay for it in rework because the boundaries were never declared. AI workflows behave the same way. Give them an incomplete picture and they will still complete it—plausibly, confidently, and often prematurely. The alternative is structural honesty. Partition the problem into phases. Each phase explicitly declares what it will not solve. UNKNOWNs are scoped, tracked, and deferred by design. If you know what not to fill now, you avoid rework later. This pairs naturally with Venkat Pillay’s “Needs” framing: what is required now versus later, driven by evidence rather than optimism. Combined, you get phased architecture where exclusions are explicit and progression is data-backed. AI doesn’t invent answers; it preserves your explicit structure. This is where human cognition becomes more relevant, not less. AI operates inside a defined problem space. Human curiosity defines the space itself. It decides which UNKNOWNs are worth preserving, which assumptions are premature, and which questions should not yet be answered. That requires intent and judgment. Models do not do that. At CloudFrame, this is how we use AI. Translation, analysis, migration—AI excels. For boundary-setting, sequencing, and confronting unknown unknowns, automation stops. Architecture resumes. In an age of powerful automation, the scarce skill is not producing answers; It is knowing when not to.

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https://lnkd.in/gxbvpkgt The HIRE Act might initially disrupt India's IT sector, but could it actually strengthen India's position in the long run? 🤔 Short-term: Yes, the 25% excise tax will create challenges for outsourcing arrangements and may reduce immediate demand. Long-term potential benefits: • US companies may convert subsidiaries to branch offices, creating direct employment opportunities • Higher-value work could shift to India as companies justify their investments beyond cost arbitrage • Indian operations might evolve from cost centers to innovation hubs and regional headquarters • Direct employment by US companies could mean better compensation standards and career advancement paths • Companies may consolidate operations into fewer, larger centers of excellence in India Instead of just competing on cost, this could push the India-US partnership toward more strategic, high-value collaboration. Sometimes regulatory pressure creates the push needed for transformation. What's your take? Could this be the catalyst that elevates India's role in global business operations? #HIREACT #IndiaIT #GlobalBusiness #FutureOfWork

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If most people believe an iPhone assembled in India is “Made in India,” why the outrage over a Chinese robot dog at a tech summit? To be clear, what the university did was not correct. Misrepresentation is misrepresentation. But let’s also acknowledge the broader environment. We routinely blur the line between assembly and innovation. We market optics as capability. We label global supply chains as national achievement. If we normalize that narrative at scale, selective outrage starts to look inconsistent. The issue isn’t just one robot. It’s the ecosystem of half-truths around “Made in India.” https://lnkd.in/g3butGSr

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With due credit to Piyush Pandey Sir for crafting some of the most iconic ads over the years. But this example shows how easily false information can spread through LLMs, all because of a missing focus on the most critical “V” among the 4 V’s of Data - Veracity. Without Veracity, it’s all too easy for AI models to generate ideas and narratives built on inaccurate foundations. Creativity without truth can quickly turn into misinformation. As we move deeper into the age of generative AI, how do we ensure our models stay rooted in verified facts while still inspiring imagination?

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It is going to solve a biggest dilemma of "what to watch" and I wish it also supports answering question from long running series which comes in parts with months of gaps where I needed to rewatch the previous season once again to build the "context" :) #jiohotstar #chatgpt #openai

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DC-DC converter efficiency principles just saved me ₹50,000 in ad spend. Here's how engineering logic crushed marketing waste. Last month my Meta campaigns were bleeding money. ₹2.5 lakh budget. ₹80 cost per lead. Sound familiar? ↳ 𝗧𝗵𝗲 𝗮𝗱 𝘀𝗽𝗲𝗻𝗱 𝘄𝗮𝘀𝘁𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 Your campaigns run like inefficient power supplies. High input. Low output. Maximum heat generation. Most marketers accept 60% efficiency rates. They think conversion loss is normal. Budget goes in at 100% Platform fees eat 15% Wrong audience targeting wastes 25% Poor creative performance loses 20% Bad landing pages kill 15% You end up with 25% actual results. The rest becomes expensive heat. ↳ 𝗕𝘂𝗰𝗸 𝗰𝗼𝗻𝘃𝗲𝗿𝘁𝗲𝗿 𝘄𝗶𝘀𝗱𝗼𝗺 𝗮𝗽𝗽𝗹𝗶𝗲𝗱 Power engineers never accept such waste. Buck converters achieve 95% efficiency rates. They do three things right. ☑ Control switching frequency precisely ☑ Minimize resistance in current path ☑ Reduce energy loss at each transition Your ad campaigns need the same discipline. Every rupee must flow with purpose. Every click must convert with intention. ↳ 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹 I treated my Meta ads like a power circuit. Input power equals ad budget. Output power equals qualified leads. Efficiency equals leads per rupee spent. Started measuring conversion at every stage. Impression to click efficiency Click to landing page efficiency Landing page to lead efficiency Lead to customer efficiency Found the biggest energy drain. Wrong audience segments were burning ₹1,200 daily. ↳ 𝗧𝗵𝗲 ₹𝟱𝟬,𝟬𝟬𝟬 𝘀𝗮𝘃𝗶𝗻𝗴𝘀 𝗿𝗲𝘀𝘂𝗹𝘁 Applied power supply optimization logic. Reduced switching losses by tighter targeting. Minimized resistance through better creative flow. Eliminated heat generation via audience precision. 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗮𝗳𝘁𝗲𝗿 𝟯𝟬 𝗱𝗮𝘆𝘀. Cost per lead dropped from ₹80 to ₹35. Same budget. 2.3x more qualified leads. Monthly savings crossed ₹50,000. 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝘄𝗼𝗿𝗸 𝗶𝗻 𝗺𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝘁𝗼𝗼. You just need to think like a circuit designer. What's the biggest energy drain in your current campaigns?

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Mumbai’s tenders aren’t complex because they’re big. They’re complex because they’re layered. A recent doc from a Maharashtra body was 1,492 pages - not including corrigenda.  • Part in Marathi, part in English.  • Attachments in scanned handwritten formats.  • Clauses that reference other documents that don’t exist. This is where AI systems break if they’re not trained right. Generic LLMs hallucinate. Traditional software stops at keyword search. At ContraVault.AI, we’ve trained our stack on over 2 lakh tender documents - many of them like these - so it doesn’t just “read,” it interprets. Across languages, across formats, across jurisdictions. That’s what it takes to build tech that works in India. And Isha will be in Mumbai next week to show teams how it’s working - one tender at a time. #LLM #EnterpriseAI #TenderParsing #GovTech #MumbaiInfra

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Artificial Intelligence, H1B Visa & The Test Of Accountability  I have been thinking about the brouhaha over the H-1B visa and believe a deeper look at Indian IT is in order. The sector’s under fire on two fronts:  →Due to the hike in H1B visa fees to $100,000. →From the disruption by artificial intelligence. Indians make up 70% of H1B visa recipients, with China trailing behind at 12%. The new fees surpass 60% of Indian workers’ annual salaries in the US, as they draw lower median wages, hitting us more than global peers. Indian IT companies could also see a drop in profit margin.  Besides that, AI is threatening to eliminate entry-level jobs. OpenAI CEO Sam Altman said that he's confident customer service jobs will be among the first to go, along with those who do routine coding tasks. It’s disheartening that highly skilled professionals — from developers to creators — who help build the system are under threat. They are stuck in bloated teams and face delays as they await endless approvals. While they bring value, creativity, and problem-solving skills — essential to enable differentiation in products and services — they are struggling to prove their worth. The service-model mindset is partly to blame. The role of the 'knowledge worker' has been diluted, from someone who applied expertise in solving complex problems and innovating to merely executing tasks. By including people in the decision-making chain who add no value but facilitate communication, we end up hindering agility. Corporate organisations are filled with pointless mid-management roles that reduce accountability. It’s possibly the result of an experiment gone wrong or an inability to fix the basics. Anthropologist David Graeber used the term "bullshit jobs" to describe such redundant positions in his 2018 book. In the era of AI, when information can be aggregated and distributed without intervention, it’s a wonder why we retain such roles. The lack of accountability that drives the current top-down system has to be fixed. So far, the skilled went abroad to become system builders, while India was left with mid-level staff. Now, we need to reframe India as a launchpad. Educational institutions, startups, and R&D labs must turn co-creators and lead skilled talent to use AI as a catalyst for creation. We need to set clear expectations for tech workers, provide resources and autonomy, give feedback, and establish a culture of ownership. The NEP 2020, which aims to integrate application-based learning within mainstream education, could prove to be a game-changer for early years, but companies also need to create pathways and opportunities for innovation at home. It’s only through such interventions that we can change the mindset that the only path to success lies abroad. So, yes, we do need to rethink some roles. But it’s not that of a highly skilled tech professional. #ArtificialIntelligence #H1BVisa #Software #IT #Technology

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Proud to help power conversational AI at scale for JioHotstar — transforming content discovery into real-time, personalized engagement for millions across India. https://lnkd.in/gjnaZDmA

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Everyone keeps asking how AI will disrupt business. Meanwhile, some companies are just using it to quietly print revenue. This week, Bajaj Finserv’s Rajeev Jain shared that it analysed nearly 2 crore customer calls using AI. The outcome? Around ₹1,600 crore in incremental business. Pause on that. Two crore conversations were always happening. The data was always there. What changed wasn’t volume. It was interpretation. Instead of treating calls as support cost, they treated them as signal. Where customers hesitate. Where they’re confused. Where intent is hidden inside conversation. That’s AI as listening infrastructure. And it’s not just one company. HDFC Bank continues investing in AI-driven fraud and risk systems to reduce loss ratios at scale. ICICI Bank is expanding AI-led underwriting and personalised offers to improve approvals without inflating risk. Globally, JPMorganChase uses AI to scan contracts and risk documents in seconds work that once consumed thousands of human hours. AI isn’t replacing people. It’s compressing inefficiency. It finds revenue hiding in operational noise. Curious to understand, where do you think businesses are most underestimating AI’s revenue impact today? Link: https://lnkd.in/gKuPZFus #Ai #Fintech

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Go Performance Tuning at Scale: Zepto’s pprof Journey (Part 1) At Zepto, performance isn’t just a priority — it’s an obsession. The best part about making systems more efficient is that it not only boosts speed but also drives real cost savings. In this blog, Akash Agarwal shares our journey of performance tuning — the challenges we tackled, the wins we unlocked, and how the process didn’t just improve our systems, but also shaped the way our engineers think about building scalable, efficient systems. Blog link: https://lnkd.in/gtzdtmGg #ZeptoTechXpress #PerformanceTuning Shivanshu Kumar Tiwari Ashish Bhatt Sumit Gupta Aditya Haridas Menon Harshal Khodifad Abhinav Nimesh Uday Solanki Devansh Chaudhary Devansh Goswami Sumit Ojha Vivek Gover Prashant Giri Balram Vishwakarma Shubham Prashar Anoop Singh Mayank Agarwal Nikhil Mittal

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Yesterday, I had mentioned that we have reduced lots of manual video editing labour by implementing an innovative engineering Flutter Widget. It has lots of advantages.. 1. Storage & Bandwidth: Your app users won't need to download 500MB video files. They download a high-quality audio file (maybe 10MB) and a tiny JSON metadata file. The Flutter engine does the heavy lifting of drawing the UI. 2. Searchability: Because the lyrics and swaras are metadata, you can eventually allow users to search for a specific phrase or note, and the app can jump the "video" exactly to that timestamp. 3. Accessibility: You can allow users to change the font size or switch between Tamil and English lyrics instantly.... something impossible with a pre-rendered video. -- This has proven us that we are not a simple mobile app development company. We built apps that needs good amount of Engineering for the backend and Flutter implementations...! The original post is given here.. https://lnkd.in/gCuD7fgw

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How can I ride the AI wave through public markets in India? I asked this research question on ChatGPT 5Pro: "Which industries and subsequently type of companies will benefit substantial from the introduction of AI in mainstream business? Research recent past results of public companies, earnings calls of ceos and cfos and discussions to provide insights What’s the purpose of this report? As a public market investor in India, I want to get ahead of the curve and invest in publicly listed companies (from any industry) that will benefit from AI in their earnings over the next few quarters, thereby providing an edge for investing in them before the market catches on." The answer is available to read as a PDF in the link below! (Gimme feedback if this helps you and you want more! Also, if you wanna partner with me on researching and investing in Indian/Global markets, just ping or write me at alok@Games2win-dot-com #Dhandhekibaat https://lnkd.in/dp47ZCVZ

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