Digant Jain

Shantanu Narayen’s 18 year tenure as CEO at Adobe is a reminder of how rare long-term stewardship has become in Silicon Valley. During his time with the company, the company’s stock increased more than 6x and its business model fundamentally changed. The most important decision of his tenure was moving Adobe from selling boxed software like Creative Suite to a subscription platform through Creative Cloud. At the time it was controversial. Today, it is considered one of the most successful SaaS transitions in the history of enterprise software, turning Photoshop, Illustrator, and Acrobat into one of the most profitable recurring software ecosystems ever built. The respect he commands across the industry says a lot about how difficult that transformation actually was. Microsoft CEO Satya Nadella even posted publicly congratulating Narayen on a “legendary run,” praising both his leadership and the way he expanded what creators and businesses could do with software. In an industry that is often intensely competitive, that kind of recognition from peers is not given lightly. There are only a few CEOs in the world who truly get to define one era of software and then help set the stage for the next. Narayen did it by turning Adobe into a SaaS powerhouse. However, the next leader will have to answer a harder question. What does a creative software company look like when AI becomes part of the creative process itself? #Adobe #Leadership #SaaS #AI #Technology

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Is the "Search & Browse" era of E-commerce officially evolving into something entirely new? 🛒🤖 I just finished watching an incredible deep dive with Manav Garg (Together Fund) on Think School. As a developer in e-commerce space, one takeaway really stood out: The transition to Agentic Commerce. For years, the industry has been obsessed with perfecting filters and recommendation engines. But the next big leap isn't a better UI, it’s the "headless" interaction between AI agents. (Timestamp: 18:05) The Shift: From UI to Infrastructure In the near future, customers may not spend 20 minutes scrolling. Instead, personal AI agents will negotiate with brand agents to find the best deal based on a user's specific goals and budget. (Timestamp: 15:08) What this means for the future of our craft: Logistics is the new Front-end: If the "Browse" layer becomes automated, the real competitive edge moves to the physical layer i.e supply chain, speed, and fulfillment infrastructure. This is where vertically integrated platforms really shine. (Timestamp: 21:31) The Rise of "Orchestration": With tools like Cursor and AI-assisted coding, we're moving away from boilerplate and toward building complex "Orchestration Layers" that allow these agents to talk to our platforms seamlessly. (Timestamp: 08:30) Efficiency as a Feature: As we integrate LLMs, the focus moves to making them profitable through smarter token usage and caching, turning "hype" into sustainable margins. (Timestamp: 36:52) We often focus on the 95% of time users spend browsing. (Timestamp: 17:52) But as that time shrinks, the platforms that win will be the ones built for agents, not just humans. Are we ready for Agentic Commerce, or are we still building for a world that's quickly moving past the search bar? Video Source: https://lnkd.in/ghfmbqw3 #Ecommerce #SoftwareDevelopment #AI #AgenticCommerce #ThinkSchool #Innovation

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H1B Visa fees 100,000 Dollar. Time to awake indians. No other way then to get out of delusion of development. We should focus more on economy then cultural activities going on now a days. This visa row is indication of following 1. AI is really on the way to destruct and change IT sector forever. 2. Jobs placements will be lower then expected. 3. Even if this visa fees is reduced then also there will be an uncertainty on the AI changing the world order. 4. Narratives build that now india will be great again, is false i think. 5. Only way to avoid heavy losses is to truly invest in AI research.

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The difference between managing projects at Amazon vs building a startup from the ground up. After 7 years at Amazon, I was part of a system that works like clockwork. Projects had frameworks. Teams had defined roles. Escalation paths existed for every problem. Even when things broke, there was a manual to fix them. In that world, success came from efficiency, how well you worked within the structure. But the day I thought of building Wheelhub, I realised something: there was no system anymore. No frameworks. No manuals. No escalation paths. If the internet broke, I had to fix it. If a customer didn’t trust us, I had to convince them. If a deal fell apart, I had to build another from scratch. At Amazon, I managed certainty. At Wheelhub, I manage chaos. And here’s the real difference: In corporate life, you inherit systems. In startups, you invent them. Every founder knows this feeling, the shock of realising there is no “machine” to keep running. You are the machine. But there’s magic in that chaos. Because it forces you to create. To create culture, systems, processes, and solutions from nothing. The challenge is greater. The pressure is higher. But so is the reward, because every inch of progress is something you’ve built, not just maintained. That’s why I believe: corporate teaches you to optimize. Startups teach you to survive and thrive. If you’ve made the leap from corporate to entrepreneurship, what was the hardest shift you had to make?

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How LLMs Work Is Not Magic Anymore A few weeks back I had taken a deep dive into the world of Large Language Models (LLMs) — and it’s been truly fascinating to unpack what goes on under the hood of models like GPT, Claude, and others. What once felt like “magic” now feels like brilliant engineering and elegant math. Through studying the Transformer architecture, I’ve developed a clear understanding of how these models actually think and learn to generate coherent, human-like text. Here’s what I’ve explored in detail 👇 🔹 Encoder–Decoder Architecture (Seq2Seq Models) – Understanding how data flows through the encoder to create context-rich representations, and how the decoder turns that into meaningful output. 🔹 Tokenization & Embeddings – How text is broken down into tokens and represented as dense vectors in a high-dimensional space. 🔹 Self-Attention Mechanism – The core innovation that allows models to understand relationships between words across long contexts. 🔹 Transformers – The building blocks of modern LLMs, replacing recurrence with attention for parallelism and scalability. 🔹 ReAct Framework – Combining reasoning and action to enhance the model’s problem-solving and decision-making capabilities. 🔹 Mixture of Experts (MoE) – The concept of dynamically routing tasks to specialized “expert” subnetworks to improve efficiency and performance. The deeper I go, the more I appreciate how systematic, scalable, and elegant these architectures are. ✨ What’s most exciting is that LLMs are no longer just black boxes to me — I can now understand and explain the “why” behind their behavior. #AI #MachineLearning #LLMs #Transformers #DeepLearning #NLP #ArtificialIntelligence #LearningJourney

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Headline: Is the Indian skincare market being "watered down"? 🧴🚫 After traveling across Europe and Asia, Ravi Tiwari and Aditi Mishra noticed a frustrating trend: the "innovation gap." While the global skincare industry is moving toward high-stability, barrier-first technology, the Indian consumer is often left with outdated formulations or marketing myths. Enter Nordic Royale. I recently sat down with Aditi to discuss how they are bringing "Elite Grade" Scandinavian science to the Indian climate. Key Takeaways: Beyond the Hype: Why "stronger" isn't always "better" for Indian melanin. The Nordic Edge: Using extremophile plants to combat urban pollution in Delhi. Biology First: Engineering products specifically for the Fitzpatrick Scale III-V (Indian skin types). Read the full interview here: https://lnkd.in/dpTCNzYk #SkincareInnovation #StartupIndia #NordicRoyale #BeautyTech #Entrepreneurship #DelhiStartups

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One of my SWE clients in the US earns $10k every month just through an AI newsletter. He recently quit his job at Amazon and moved back to India to pursue content creation full-time. Meaning….building a startup is not the only way to ride on this AI hype. These are the 6 ways you can build on this AI hype [1] Create AI-focused Content Simplify AI news, tools, tutorials. Instagram creators in AI grew followers 8x faster than average tech creators in 2024. [2] Build AI tools for creators AI-powered editing, scripting, or thumbnails (think Canva, but powered by GPT-4o). [3] Offer AI Education/Courses Udemy reports a 210% increase in AI-related course enrollments since 2023. [4] Develop Custom AI integrations Help businesses integrate LLMs into Slack, Teams, Notion. Companies are paying top-dollar for seamless AI integrations. [5] Become an AI Consultant Advise small businesses on AI adoption strategies. [6] Or build your service business around AI Like me, my agency helps tech creators create AI Content on LinkedIn and Instagram. The AI wave is just getting started. You have time, but don’t waste it. Pick one—and start building today. Nikhil Bhatia

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A Product Growth & Business View from India: Why 2025 Changed How AI Gets Used 2025 wasn’t just another year of better AI models. For me, working across product growth and go-to-market for Indian businesses, it was the year AI quietly moved from chat interfaces into the real operating systems of work ⚙️ The biggest shift wasn’t smarter chatbots; it was the rise of agentic AI 🤖 Systems that don’t just respond, but observe workflows, make decisions, call tools, and complete tasks end-to-end with minimal supervision. Instead of waiting for prompts, AI is now: Monitoring leads 📊 Updating CRMs automatically Triggering ERP actions Keeping revenue and operations moving in the background What made this possible wasn’t one breakthrough, but a convergence: 🧠 Stronger reasoning models 💸 Lower inference costs 🔧 Reliable tool-calling & orchestration frameworks 🎙️ Multimodal inputs like voice, text, and structured data Together, they turned “let the AI handle this workflow” into a practical product decision, not a risky experiment. In India, this shift is deeply pragmatic 🇮🇳 Enterprises and SMEs aren’t asking “Can we try AI?” anymore. They’re asking: ❓ Can AI follow up on leads without missing context? ❓ Can it support sales teams without adding headcount? ❓ Can it execute repetitive outreach while staying compliant? 👉 That’s exactly where we’re focusing with Jaano.ai. At Jaano.ai, we’re building AI agents that move beyond chat and into revenue-generating workflows. One example is our voice-enabled sales agent, designed specifically for outbound use cases common in India 📞 The agent can: Initiate outbound calls automatically Speak naturally with prospects 🗣️ Capture structured call transcripts 📝 Identify intent, objections, and buying signals Tell your sales team exactly what to ask next in follow-ups Instead of managers guessing what happened on a call or relying on partial notes, the system creates a clear, auditable context,so humans step in only where judgment actually matters. For product leaders, this changes the core question. It’s no longer: ❌ “Which AI tool should we experiment with?” It’s now: ✅ “Which parts of our sales, support, and operations can we safely hand over to autonomous agents and what guardrails do we design around them?” The teams that will win in 2026 won’t be the ones with the flashiest AI demos ✨ They’ll be the ones that treat AI as an operational layer measured, governed, and continuously improved. From where I sit, that’s the real AI shift of 2025 in India: ➡️ Moving from talking to AI ➡️ To working alongside AI agents that actually get the job done. And that’s the direction we’re building toward at Jaano.ai 🚀 #AIInProduction #AgenticAI #AppliedAI #ProductGrowth #ProductThinking #IndiaTech #IndianStartups #B2BSaaS #GoToMarket #SalesAI #VoiceAI #WorkflowAutomation #StartupBuilders Jaano.ai Token AI Labs Pvt. Ltd. 🔗 https://jaano.ai/

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Thrilled to announce that my teammate, Zafran Sakowi and TIVENESH SRINIVASAN (Team Techies) secured 3rd Place 🥉 at the GDG UM Generative AI: Coding Competition! This competition was a true test of endurance and not for the faint of heart. The 14-hour hackathon kicked off at 10 PM on Friday and ran non-stop until 12 PM the next day. While most teams consisted of 4-6 members, we tackled the challenge as a duo. This meant working through the entire night, battling significant sleep deprivation to build a complete project from the ground up. To bring our vision to life under these intense conditions, we built a full-stack website leveraging the powerful and versatile Google Gemini API. Specifically, we implemented: * Dynamic Text Generation: At its core, our application used Gemini models to generate responsive and contextual text, creating a seamless user interaction experience. * Function Calling: This was crucial for our project's functionality. We enabled the model to connect with external APIs and tools, allowing it to translate natural language prompts into real-world, executable actions. * Multimodal Capabilities: We designed our solution around the API's foundational strength of processing various input types, making our application more robust and versatile. The experience was a true rollercoaster. My immediate thought after the 14-hour marathon was, "Would I do it again? Absolutely not." But reflecting on what we built, it's also a definite "yes." As students from Universiti Teknologi Malaysia (UTM), we are incredibly proud to have represented our university at this event and are honored to bring back this achievement. This would not have been possible without my incredible partner, Zafran Bin Muhamad Sakowi – your dedication and skill, especially through the night, were instrumental. A huge thank you to the organizers at GDG Universiti Malaya for putting together such a challenging and rewarding competition. Excited to apply what we've learned and continue exploring the vast potential of Generative AI. #GenerativeAI #Hackathon #UTM #UniversitiMalaya #GoogleDeveloperGroup #GDG #GeminiAPI #AI #Coding #ThirdPlace #Teamwork #HackathonLife #NoSleep #Gemini

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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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Ever wonder why we never went back to waving at street cabs after using Uber, Lyft or Ola - even with surge pricing, delays, or app glitches? That’s Delta 4 Theory, and discovering it through Kunal Shah completely rewired how I think about product value. While diving deep on ride-hailing vs traditional cabs, I realized something simple but powerful: great products don’t just improve experiences - they make the old way feel impossible. Delta 4 gave me the clarity to cut through noisy hypotheses and focus on what truly drives product-market fit: irreversibility, deep user benefit, and even loyalty in the face of flaws. If your users can’t imagine life before your product, you’re onto something. #PMF #productmanagement #innovation #Leadership #SaaS

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