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Bhuvan Tummala shared this🧠 The Psychology of AI Adoption Part 3: Feature Chasers — The Most Misunderstood AI Users Every AI product has them. The users who show up on launch day. Try every new feature. Post screenshots on X and LinkedIn. Then… They’re gone. Most teams call them low-loyalty users. I think they’re something else. They’re Feature Chasers. And they reveal an important truth about AI products. ✨ How Feature Chasers think 🚀 “What’s new?” ⚡ “Show me something I haven’t seen.” 🎁 “Surprise me.” 🔥 “Give me a reason to come back.” They don’t stay because your product exists. They stay because your product keeps evolving. That’s why Feature Chasers: 🔄 Try dozens of AI tools every month. 🧪 Love beta programs and experimental features. 📣 Share new discoveries with friends and online communities. 📉 Lose interest when innovation slows. The mistake many companies make? They confuse launch-day excitement with long-term success. 📈 High sign-ups. 📈 High social buzz. 📈 Thousands of shares. Those are great signals… But they’re not proof of product-market fit. 💡 Feature Chasers optimize for novelty. Most businesses optimize for retention. Those are very different goals. So how do you build for them? ✅ Ship continuously—not occasionally. ✅ Make experimentation easy. ✅ Celebrate what’s new without overwhelming existing users. ✅ Turn curiosity into habit before the excitement fades. The best AI products don’t rely on one viral launch. They create a rhythm of discovery. Because for Feature Chasers… The next exciting feature is always around the corner. The challenge isn’t getting their attention. It’s giving them a reason to stay. Next in the series: 🛡️ Trust-First Adopters — Why the hardest users to win often become your most valuable customers. 👇 Which matters more for an AI product? 🚀 Launch-day excitement ❤️ Long-term retention Or… 💡 How do you balance both? if you miss my Part 2: Prompt Nomads — Loyal to Outcomes, Not Products? #PsychologyOfAIAdoption #AI #ArtificialIntelligence #ProductManagement #ProductStrategy #CustomerBehavior #UserBehavior #SaaS #Innovation #ProductLedGrowth #GrowthStrategy #AgenticAI #DigitalTransformation #FutureOfWork #Startups
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Bhuvan Tummala shared this🕸️ The Knowledge Architecture Behind AI Part 1: AI Has a Relationship Problem Everyone is racing to build better AI. Bigger models. More tokens. Longer context windows. More documents. More vector databases. But I think we’re solving the wrong problem. AI doesn’t just need more information. It needs to understand how information is connected. Think about a simple travel question: “Show me family-friendly hotels near famous temples that have vegetarian restaurants, museums within walking distance, and guided local experiences.” This isn’t a document search. It’s a relationship search. Behind that one question are dozens of connected entities: 🏛️ Place → Attractions → Temples → Museums 🏨 Hotels → Amenities → Availability 🍽️ Restaurants → Cuisine → Dietary Preferences 🛍️ Local Stores → Products → Brands 🎟️ Experiences → Service Providers → Ratings 📍 Locations → Distances → Transportation Most AI systems retrieve text. The next generation of AI will retrieve connected knowledge. That’s the difference between knowing facts and understanding a domain. 💡 The shift is happening: 📄 Documents → 🕸️ Knowledge Graphs 🔍 Keyword Search → 🔗 Relationship Discovery 🧠 Context Retrieval → 🌐 Context Understanding 📦 Disconnected Data → 🧩 Connected Intelligence The organizations that model their knowledge—not just their data—will build AI that is more accurate, explainable, and capable of solving real-world problems. I believe knowledge architecture will become one of the most important competitive advantages in Enterprise AI over the next few years. This is the first post in a new series where I’ll explore Knowledge Graphs, Ontologies, Semantic AI, GraphRAG, and why relationships—not just data—are becoming the foundation of intelligent systems. 💬 Question for you: If you could make your AI understand relationships instead of just retrieving documents, what business problem would it solve first? #AI #EnterpriseAI #KnowledgeGraphs #SemanticAI #GraphRAG #Ontology #AIArchitecture #DataArchitecture #LLM #GenerativeAI #ArtificialIntelligence #EnterpriseArchitecture #MachineLearning #ProductManagement #DigitalTransformation #FutureOfAI
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Bhuvan Tummala shared this📚 Adoption Mechanics — 06 - Discovery Beats Superiority Everyone wants to build a better product. Very few ask: Can people actually find it? History is full of products that were technically superior… …but commercially invisible. Because products don’t compete only on quality. They compete on discoverability. The adoption equation is simple: A product can’t be adopted… if it can’t be discovered. That’s why the winners obsess over: 🔍 Searchability 💬 Word of mouth 🤝 Recommendations 🌐 Distribution channels 📱 Default placement Think about it. Google didn’t win because it was the first search engine. Spotify wasn’t the first music service. Zoom wasn’t the first video conferencing tool. ChatGPT wasn’t the first LLM. Each became incredibly easy to discover, try, and share. Distribution amplified product quality. The lesson? The best product doesn’t always win. The easiest great product to discover usually does. 💡 One-Line Framework Adoption = Product Quality × Discoverability A product with zero discoverability has zero adoption potential. This is Part 06 of Adoption Mechanics — a series on how products, behaviors, networks, and new defaults spread. 📚 Missed Part 05? Why Most Marketplaces Fail Why liquidity—not network effects—is the foundation of every successful marketplace. https://lnkd.in/gv52-UMM 👇 What’s a product you think was better than the market leader—but never got discovered? #AdoptionMechanics #ProductStrategy #Growth #Marketing #Distribution #Innovation #AI #ProductManagement #Startups #Discoverability
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Bhuvan Tummala shared this🚀 Intelligence Without Bureaucracy — Part 3 The Most Valuable Thing AI Keeps Losing: Context. Imagine asking an AI travel assistant: “I want a luxury vacation… but I also want hidden gems, authentic local culture, and experiences that don’t feel touristy.” A multi-agent workflow begins. 🤖 Planner Agent ↓ 🤖 Research Agent ↓ 🤖 Reviewer Agent ↓ 🤖 Booking Agent The final itinerary arrives… 🏨 Luxury hotel 🍽 Michelin restaurant 🚘 Private transfers Everything looks… perfect. Except it completely missed what mattered most. The authentic local experience disappeared somewhere along the way. This is one of the biggest challenges in Agentic AI: ⚠️ Every handoff compresses context. ⚠️ Every summary removes nuance. ⚠️ Every agent interprets intent differently. ⚠️ Every decision risks drifting further from the original goal. Most AI systems don’t fail because they can’t reason. They fail because they slowly forget why they’re solving the problem. As models become smarter, context becomes more valuable than computation. The architectures that win won’t necessarily have the most capable models… They’ll be the ones that preserve user intent from the first prompt to the final action. 💡 Context isn’t just memory. It’s the continuity of intent. And preserving it may become the most important design principle in Agentic AI. How are you preserving user intent across long-running AI workflows? Missed Part 2 ? - The Hidden Tax Nobody Talks About: Agent Coordination - https://lnkd.in/gswEtnkj #AI #AgenticAI #ContextEngineering #EnterpriseAI #AIArchitecture #LLM #GenerativeAI #ProductManagement #FutureOfAI #SystemDesign
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Bhuvan Tummala shared this🚀 Innovation Thinking Series | Part 4 🧱 First Principles Thinking Most people improve what’s already there. Innovators rebuild from the fundamentals. Instead of asking: “How can we make this better?” Ask: “What are the fundamental truths, and how would we build it if we started today?” That’s First Principles Thinking. 💡 The Mental Model We often inherit assumptions without realizing it. Products. Processes. Business models. Over time, assumptions become “best practices.” But best practices are often solutions to yesterday’s constraints. First Principles Thinking strips away assumptions until only the fundamental truths remain. Then you build upward from there. 🏢 Real Example Before SpaceX, rockets were treated as disposable. The assumption was: “Rockets are expensive because they can only be used once.” Elon Musk challenged that assumption. “What if rockets could land and fly again?” The breakthrough wasn’t better engineering. It was questioning a long-held assumption. 🤖 AI Era Example Many companies ask: “How do we add AI to our existing product?” A First Principles question is: “If AI existed when we built this product from day one, what would it look like?” That’s the difference between adding AI… …and becoming AI-native. 🎯 A Simple Exercise Take any product or workflow. Ask yourself: • What assumptions are we making? • Which assumptions are actually facts? • Which ones are just habits? • If none of those habits existed, how would we design this today? Innovation doesn’t come from improving assumptions. It comes from replacing them. This is Part 4 of my Innovation Thinking series. What’s one product or industry that needs to be rebuilt from first principles? #InnovationThinking #FirstPrinciples #Innovation #AI #Leadership #ProductManagement #Startups #FutureOfWork
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Bhuvan Tummala shared this🧠 The Psychology of AI Adoption Part 2: Prompt Nomads — Loyal to Outcomes, Not Products One of the biggest assumptions in SaaS is: “If users love your product, they’ll stay.” AI is breaking that assumption. Meet the Prompt Nomads. They’re not looking for the best AI tool. They’re looking for the best result. If another tool helps them finish the job faster, cheaper, or better… They’ll switch. Without hesitation. 🧭 How Prompt Nomads think 🎯 Outcome > Brand ⚡ Speed > Familiarity 🛠️ Workflow > Features 🔄 Flexibility > Loyalty 💰 Value > Vendor They don’t ask: “Which AI tool should I use?” They ask: “Which combination of tools gets me the best result?” Today it might be: • ChatGPT for ideation • Claude for writing • Perplexity for research • Gemini for validation • Cursor for coding • Midjourney for visuals Tomorrow? A completely different stack. That’s because Prompt Nomads aren’t building relationships with products. They’re building relationships with outcomes. This changes everything for product teams. ❌ Winning on features isn’t enough. ❌ Being first isn’t enough. ❌ Having the smartest model isn’t enough. To earn a place in a Prompt Nomad’s workflow, your product needs to: ✅ Solve one problem exceptionally well. ✅ Integrate seamlessly with other tools. ✅ Reduce friction at every step. ✅ Deliver obvious value within minutes. The biggest mistake companies make? Trying to lock users into an ecosystem. Prompt Nomads don’t want ecosystems. They want toolkits. The winners won’t be the products that try to own the entire workflow. They’ll be the ones that become the best step inside it. Because Prompt Nomads aren’t disloyal. They’re outcome loyal. That’s a very different kind of customer. Next in the series: ✨ Feature Chasers — Why launch-day excitement can be the most misleading product metric. How many AI tools do you use in a typical workday? 1️⃣ One tool only 2️⃣ Two to three 3️⃣ Four to six 4️⃣ Seven or more And if a better tool launched tomorrow… Would you switch? Missed Part 1 ? - AI Changed the Products. https://lnkd.in/gan9w6QX #PsychologyOfAIAdoption #AI #ArtificialIntelligence #PromptEngineering #ProductManagement #ProductStrategy #CustomerBehavior #UserExperience #SaaS #Startups #AgenticAI #Innovation #FutureOfWork #GrowthStrategy #ProductLedGrowth
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Bhuvan Tummala shared this📚 Adoption Mechanics — 05 - Why Most Marketplaces Fail Everyone wants to build a marketplace. Few realize they’re building an empty room. A marketplace doesn’t fail because the technology is bad. It fails because buyers and sellers never arrive at the same moment. This is the Liquidity Problem. Think about it. A buyer visits. ❌ Nothing relevant. They leave. A seller joins. ❌ No buyers. They leave. The product works. The market doesn’t. That’s why marketplaces aren’t built by adding more users. They’re built by creating successful interactions. The best marketplace founders obsess over one metric: Can one buyer find one seller at the right time? Not millions. Just one. Successful marketplaces solve liquidity before they scale. Examples: 🚗 Uber → Drivers before riders in each city 🏡 Airbnb → Supply before demand 🛍️ Amazon → Inventory before traffic ✈️ Travel platforms → Inventory before bookings 💼 Upwork → Talent before clients Growth didn’t create liquidity. Liquidity created growth. 💡 One-Line Framework Users create a marketplace. Successful transactions create liquidity. Liquidity creates growth. This is Part 05 of Adoption Mechanics — a series on how products, behaviors, networks, and new defaults spread. 📚 Missed Part 04? Network Effect Inversion Why products become powerful when not joining becomes more expensive than joining. https://lnkd.in/g_Ykc6_j 👇 What’s the best example of a marketplace that solved liquidity brilliantly? #AdoptionMechanics #Marketplace #ProductStrategy #NetworkEffects #Growth #AI #Platforms #ProductManagement #Startups #Innovation
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Bhuvan Tummala shared this🚀 Intelligence Without Bureaucracy — Part 2 The Hidden Tax Nobody Talks About: Agent Coordination Everyone measures: ✅ Accuracy ✅ Latency ✅ Cost But few teams measure the biggest cost of all: ⚠️ Coordination. A single agent workflow looks like this: 🧠 Think ⚙️ Act Simple. Now let’s look at a typical multi-agent architecture: 🤖 Planner Agent 🤖 Research Agent 🤖 Critic Agent 🤖 Reviewer Agent 🤖 Supervisor Agent 🤖 Execution Agent What happens next? 📨 Messages 📨 Hand-offs 📨 Summaries 📨 Validations 📨 Synchronization 📨 Conflict resolution At some point, the system spends more effort coordinating than solving the user’s problem. Sound familiar? That’s exactly what happened in many human organizations. Every new agent doesn’t just add capability. It also adds communication overhead. The uncomfortable reality: 🧠 Intelligence scales faster than coordination. And coordination gets expensive very quickly. The lesson I’m seeing across Agentic AI architectures: Don’t ask: “How many agents do I need?” Ask: “What is the minimum coordination required to solve this problem?” The smartest AI systems won’t eliminate agents. They’ll eliminate unnecessary coordination. 💡 Every new agent creates more communication than capability. What’s the largest coordination challenge you’ve encountered while building agentic systems? #AI #AgenticAI #MultiAgentSystems #EnterpriseAI #ArtificialIntelligence #AIArchitecture #SystemDesign #LLM #FutureOfAI #GenerativeAI
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Bhuvan Tummala shared this🧠 The Psychology of AI Adoption Part 1: AI Changed the Products. It Also Changed the Adopters. For more than 60 years, we’ve used Rogers’ Adoption Curve to explain how innovation spreads. 💡 Innovators 👥 Early Adopters 📈 Early Majority 🏢 Late Majority 🐢 Laggards It helped us understand who adopts first. But AI introduced something new. Not just new products. New behaviors. Today, I’m seeing adopter profiles that traditional frameworks struggle to explain: 🧭 Prompt Nomads Loyal to outcomes, not products. Move fluidly between multiple AI tools to get the job done. ✨ Feature Chasers Show up for launches. Leave when the next shiny feature arrives. 🛡️ Trust-First Adopters Security, privacy, and reliability before adoption. Slow to adopt. Extremely hard to churn. 📋 Reluctant Adopters Using AI because their company, industry, or market requires it. Compliance ≠ engagement. 🔗 Ecosystem Prisoners Adopt within ecosystems they already trust. Apple. Google. Microsoft. Salesforce. OpenAI. 🧠 AI Natives Expect intelligence by default. Have little patience for workflows designed before AI existed. The biggest shift? The old question was: 👉 How do we get people to adopt? The new question is: 👉 Which adopter profile are we building for? Because a product loved by a Prompt Nomad may completely fail with a Trust-First Adopter. And a Feature Chaser’s excitement is not the same thing as product-market fit. 💡 In the AI era: Adoption ≠ Retention Winning products don’t just get tried. ✅ They become habits. ✅ They fit workflows. ✅ They earn trust. ✅ They create measurable value. That’s what turns adoption into long-term growth. Over the next few posts, I’ll dive deeper into each AI adopter profile and what it means for product, growth, retention, and strategy. Starting with: 🧭 Prompt Nomads — the users who may be quietly reshaping the entire AI landscape. 👇 Which AI adopter profile best describes you today? 🧭 Prompt Nomad ✨ Feature Chaser 🛡️ Trust-First Adopter 📋 Reluctant Adopter 🔗 Ecosystem Prisoner 🧠 AI Native And more importantly: Which one are you building for? #PsychologyOfAIAdoption #ArtificialIntelligence #AI #ProductManagement #ProductStrategy #CustomerBehavior #UserPsychology #GrowthStrategy #SaaS #Startups #AgenticAI #ProductLedGrowth #DigitalTransformation #Innovation #FutureOfWork
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Bhuvan Tummala liked thisBhuvan Tummala liked thisMost companies are bleeding cash in 4 spots. (And don't even know which wound to fix first.) The brutal reality: Every dollar leaving your business falls into one of these buckets: OPERATIONS (OpEx) - The Daily Bleed ↳ Your rent, salaries, software subscriptions ↳ The money that vanishes every month ↳ Cut too deep? Your business stops tomorrow ASSETS (CapEx) - The Big Bets ↳ That $50K machine, new warehouse, custom software ↳ Spend once, use for years ↳ Get it wrong? You're stuck with expensive mistakes SALES (RevEx) - The Revenue Tax ↳ Every sale costs you something ↳ Materials, commissions, shipping, processing fees ↳ Ignore this? Profit margins turn into losses MONEY (FinEx) - The Hidden Killer ↳ Interest on loans, bank fees, credit charges ↳ The cost of using other people's money ↳ Let it grow? It eats your profits alive Let's look at 2 examples: Coffee Shop Reality: • OpEx: $15K/month (rent, barista wages, utilities) • CapEx: $80K once (espresso machine, renovation) • RevEx: $3 per cup sold (beans, cup, lid) • FinEx: $500/month (equipment loan interest) SaaS Startup Truth: • OpEx: $50K/month (team, AWS, office) • CapEx: $200K once (custom platform build) • RevEx: $20 per customer (payment fees, onboarding) • FinEx: $2K/month (venture debt interest) Most founders lump all expenses together. Then wonder why they can't scale. But when you separate them? OpEx → Find your true burn rate CapEx → Time investments perfectly RevEx → Price products profitably FinEx → Optimize capital structure Crucial insights: ✓ High OpEx? You're not scalable yet ✓ No CapEx? You're not building moats ✓ Rising RevEx? Your unit economics are broken ✓ Climbing FinEx? You're overleveraged Common traps: ❌ Treating CapEx like OpEx (and vice versa) ❌ Ignoring RevEx when setting prices ❌ Letting FinEx compound silently ❌ Not tracking any of them separately Watch what happens when you finally see where your money really goes. Your future self will thank you. Your investors will respect you. Your business will actually scale. Stop managing "expenses." Start managing OpEx, CapEx, RevEx, and FinEx. That's how you build something that lasts. P.S. Want a high-res PDF of my OpEx CapEx RevEx FinEx Cheat Sheet? Get it free: https://lnkd.in/egU4rJ_n ♻️ Repost to help a founder in your network. Follow Eric Partaker for more financial insights. ==== 📢 Want to achieve even more success as a CEO? Our next cohort of the Founder & CEO Accelerator starts July 29th. Only 10 days left to join: https://lnkd.in/eUBQZsze
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Bhuvan Tummala liked thisBhuvan Tummala liked thisGrowing a travel business isn’t just about making the right moves. It’s also about avoiding the wrong ones. Sometimes, small oversights in planning, partnerships, pricing, or customer experience can quietly hold your business back. Here are some common mistakes to avoid as you build a stronger, more sustainable travel business. #TravelBusiness #TravelAgents #BusinessGrowth #Mondee
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Bhuvan Tummala liked thisBhuvan Tummala liked this𝗜𝗻𝗱𝗶𝗮'𝘀 𝗚𝗲𝗻𝗲𝗿𝗮𝗹 𝗧𝗿𝗮𝗱𝗲 continues to power 𝗜𝗻𝗱𝗶𝗮'𝘀 𝗙𝗠𝗖𝗚 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺, accounting for 𝗼𝘃𝗲𝗿 𝟳𝟱–𝟴𝟬% of total FMCG sales through a network of 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟭.𝟰 𝗰𝗿𝗼𝗿𝗲 kirana stores across the country. As India's retail landscape evolves, digital infrastructure is becoming the foundation that connects brands, distributors, and retailers more efficiently, creating a faster, more transparent, and technology-driven supply chain. We're proud to see Qwipo featured in 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗘𝘅𝗽𝗿𝗲𝘀𝘀 for its vision of digitising India's retail backbone and helping modernise the General Trade ecosystem. At the time of the feature, the Qwipo DigiDukaan ecosystem had 𝗼𝘃𝗲𝗿 𝟯𝟱+ 𝗯𝗿𝗮𝗻𝗱𝘀 onboarded. Today, that momentum has accelerated to 𝗼𝘃𝗲𝗿 𝟭𝟬𝟬+ 𝗯𝗿𝗮𝗻𝗱𝘀, alongside 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟭𝟬,𝟬𝟬𝟬+ 𝗿𝗲𝘁𝗮𝗶𝗹𝗲𝗿𝘀 already onboarded, reinforcing our commitment to building a stronger, digitally connected General Trade network for India. At Qwipo DigiDukaan, we're committed to making distribution smarter, improving visibility across the supply chain, and enabling brands and distributors to grow together through technology. 𝗚𝗲𝗻𝗲𝗿𝗮𝗹 𝗧𝗿𝗮𝗱𝗲 𝗶𝘀𝗻'𝘁 𝗱𝗶𝘀𝗮𝗽𝗽𝗲𝗮𝗿𝗶𝗻𝗴. 𝗜𝘁'𝘀 𝗲𝘃𝗼𝗹𝘃𝗶𝗻𝗴. 𝗔𝗻𝗱 𝗤𝘄𝗶𝗽𝗼 𝗗𝗶𝗴𝗶𝗗𝘂𝗸𝗮𝗮𝗻 𝗶𝘀 𝗽𝗿𝗼𝘂𝗱 𝘁𝗼 𝗯𝗲 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘁𝗵𝗮𝘁 𝘄𝗶𝗹𝗹 𝗽𝗼𝘄𝗲𝗿 𝗶𝘁𝘀 𝗳𝘂𝘁𝘂𝗿𝗲. #DigiDukaan #ONDC #Qwipo #Kirana #GeneralTrade #FMCG #DigitalIndia #eB2B #eCommerce Financial Express (India) Open Network For Digital Commerce (ONDC) Inc42 Media YourStory Media Hindustan Unilever (HUL) ITC Limited Coca-Cola India PepsiCo Colgate-Palmolive (India) Ltd Dabur India Limited Godrej Consumer Products Limited Marico Limited Britannia Industries Limited Parle Products Pvt. Ltd Nestle India Procter & Gamble L'Oréal Patanjali Ayurved Limited Mondelēz International CavinKare
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Bhuvan Tummala liked thisBhuvan Tummala liked thisThe loudest person in the room is not always the most powerful. A good leader helps carry the weight. And today, AI gives quiet thinkers something powerful: leverage. An introvert with the right tools can research, create, and execute at a scale that once required a team. The future may belong to those who think deeply and use AI wisely.
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Bhuvan Tummala liked thisBhuvan Tummala liked thisClaude Code just made LOOP ENGINEERING official The way you work with AI is about to change The shift: stop prompting task by task, start designing the loop that runs itself. 4 patterns: https://lnkd.in/dEeBrGWw ▫️ Turn-based: you hold the wheel, 1 task per round ▫️ Goal-based: define "done," Claude retries until it hits the standard ▫️ Time-based: runs on a schedule, checks and reacts on its own ▫️ Proactive: events trigger it, no human online needed The job moves from writing prompts to picking which loop fits the work AI playbooks to go deeper 👇 ▫️ Claude & Anthropic → https://lnkd.in/e6hgSuF6 ▫️ Prompting & Context → https://lnkd.in/emVG45gJ ▫️ AI Agents → https://lnkd.in/dDAfefYJ ▫️ AI Tools & Models → https://lnkd.in/eC8sf5-z ▫️ Business & Investing → https://lnkd.in/e-prVNQ7
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Bhuvan Tummala liked thisBhuvan Tummala liked thisBig day at Super.com. We've raised a $65M Series D at a $1.2 billion valuation, led by TPG! 🔥 When we started in 2016, it was a simple hotel-booking chatbot. The insight that changed everything: our most frequent customers were everyday Americans stretching every dollar. 💵 So we built for them: more ways to save, opportunities to earn, credit-building tools — and we just kept evolving the app. We are now truly a savings super app — and our customers have saved well over $1 billion to date. 🤯 Our membership program, Super+, has grown to nearly a million members. Our goal: every American household counts Amazon Prime, Costco, and Super+ as their essential money-saving memberships. This funding lets us do more of what matters most: helping everyday households keep more of their hard-earned money. Look forward to partnering with David Bessel and Arun Agarwal at TPG! None of this happens without the exceptional Super.com team. I'm genuinely awed by your talent and commitment. We are just getting started but let's take the time to enjoy this milestone. 🎉
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VScool
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Training site for Videocon d2h employees
It is a training site for videocon d2h employees who can be registered only through admin in their respective departments and roles to update employees skillset to promote their videocon d2h sales.Other creators -
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http://www.ubqool.com
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It's a fun, learning and social educational site.
It is an educational and social networking site that allows the students to learn. Each student can create their own books in any subject by integrating the contents they like in that topic. They can publish this and they can share it among their friends. Students can create their own groups and can share the contents .The students can send messages to any of the members like any other social networking sites. The Cassandra distributed…It's a fun, learning and social educational site.
It is an educational and social networking site that allows the students to learn. Each student can create their own books in any subject by integrating the contents they like in that topic. They can publish this and they can share it among their friends. Students can create their own groups and can share the contents .The students can send messages to any of the members like any other social networking sites. The Cassandra distributed database system is using behind it.Other creators -
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Newz On Click
Comviva Launches NGAGE: AI-Powered CPaaS Platform for Secure Enterprise Customer Engagement According to Deshbandhu Bansal, Chief Operating Officer for RevTech Solutions at Comviva, enterprises today face growing challenges such as fragmented communication systems, increasing fraud risks, and the demand for highly personalized customer experiences. The NGAGE platform brings communications, identity intelligence, and AI automation together in a single SaaS solution to help organizations address these challenges efficiently. https://lnkd.in/g3RFVB-V
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CitiusTech
In healthcare, AI cannot be treated as plug-and-play. The stakes demand clarity on 𝘄𝗵𝗼 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲𝘀, 𝗴𝗼𝘃𝗲𝗿𝗻𝘀, 𝗮𝗻𝗱 𝗼𝘄𝗻𝘀 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀. In a People Matters feature, Sowmya Santhosh, CHRO, CitiusTech, shares what responsible AI adoption really requires: 𝘄𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝗿𝗲𝗮𝗱𝗶𝗻𝗲𝘀𝘀, 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲, 𝗮𝗻𝗱 𝗰𝗹𝗲𝗮𝗿 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 across teams. When those foundations are in place, AI becomes a trusted enabler, not a risk multiplier. Read the full publication on People Matters: https://bit.ly/4d0Djbc CitiusTech. Human First. AI-enabled healthcare. #AIinHealthcare #ResponsibleAI #Governance #HealthIT #HealthcareLeadership #CitiusTech
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ETBFSI
Beyond UPI: BFSI leaders outline AI-led, API-first future of India’s digital stack At ETBFSI CIO Digital Conclave 2026, top BFSI leaders discussed how digital public infrastructure, APIs and AI-ready architectures are reshaping capital markets, MSME lending and financial ecosystems. #IndiaStack #AILed #APIFirst #EmbeddedFinance #HyperPersonalization #DigitalPublicInfrastructure #BFSI #OpenBanking https://lnkd.in/dA-QmPQB
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Apexon
In the competitive streaming industry, retaining customers is just as critical as acquiring them. Apexon partnered with a leading US streaming service to revolutionize customer retention using advanced AI-driven churn prediction. The results speak for themselves: ✅ 91% accuracy in predicting churn ✅ Reduced false positives to just 3–6% ✅ Personalized retention offers that boosted loyalty ✅ Significant reduction in overall churn rates By leveraging machine learning models, enriched behavioral data, and AWS-powered cloud infrastructure, Apexon helped transform retention strategies into a powerful growth driver. 👉 Discover how AI is shaping the future of media & entertainment: https://lnkd.in/e-DNSHFQ Learn more about AgentRise here: https://lnkd.in/gAjwAkHX #Media #Streaming #CustomerExperience #AI #DigitalTransformation #Apexon #PeakIngenuity
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Anaptyss
In this featured article in Express Computer, Anuj Khurana, Co-Founder and CEO of Anaptyss, shares thoughtful insights into the broader conversation about how Global Capability Centers are evolving from back-office functions to strategic hubs that drive AI-led digital innovation for future-ready managed services. #digital #gcc #innovation
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Zensar Technologies
At Zensar, we believe the most meaningful innovation starts with listening closely to the market. Our recent interactions with leaders from key organizations across the industry focused on how enterprises are scaling AI and driving innovation in real-world environments - balancing speed, cost, governance, and long-term value. From rethinking legacy approaches to strengthening data foundations and aligning AI investments to measurable outcomes, the discussions brought forward practical perspectives on what it takes to move from experimentation to enterprise-wide impact. As one perspective from the session highlighted, “Context is the new king”, a principle we are enabling through ZenseAI, our agentic AI platform, which delivers connected intelligence through a single, contextualized layer. These insights continue to shape how we evolve our solutions, ensuring they remain focused on real impact and aligned to client needs. Here's what stayed with us: • Scaling AI requires a stronger focus on real outcomes, not just experimentation • Context, governance, and data foundations are critical to unlocking enterprise value • Simplicity and clarity in solutions will define adoption and long-term impact #Zensar #ZenseAI #ArtificialIntelligence #EnterpriseAI #AIAtScale #AIDrivenInnovation #AgenticAI #DataAndAI #DigitalTransformation #AITransformation Manish Tandon | Nachiketa Mitra | Pratik Maroo | Parag Jain | Harish Lala | Arjun Yadavalli | Chaitanya (Chai) Rajebahadur | Jitendra Nandwani | Jitendra Banthia | Jeff Roach | Leslie Fountain (she/her) | Rishikesh R. | Suyog Prabhu | Nishad Somalwar | Ravi Thyagarajan | Ankit Bhatia | Jagathpathy Subramaniam | Narayana Prasad Shankar (NP) | Sachin Nade | Brijesh Singh | Sayali Kalaskar
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