Shalini Goyal

Most systems do not break from load. They break from misunderstanding. It is not pressure that kills architecture. It is the lack of Air. Example 1: A partner asked us to copy their customer category as a simple flag. Looked easy. Turned into chaos. Flags drifted. Values mismatched. Nobody knew what the flag meant. One question changed everything: “What outcome does this category drive?” Suddenly the truth appeared. We did not need their flag at all. We needed the behaviour behind it. Once context moved, the whole design became light. Example 2: A team passed a “specialHandling = true” flag. Simple, right? Except no one knew what “special” meant. The receiving domain did not want the flag. They wanted the treatment. Flags carry data. Air carries intent. And intent is what keeps systems breathable. The lightest architectures are the ones where context moves faster than requirements. Full essay on Systems and Sutras:“The Air Sutra: Architecture That Breathes Instead of Suffocates” 🔗https://lnkd.in/eGhvQ8xp Where in your architecture are teams passing information without passing meaning? #Architecture #EngineeringLeadership #SystemsThinking #DomainDrivenDesign #SystemsAndSutras

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Grateful to The Better India for featuring Xcelevate Skills Foundation and bringing this story to a wider audience. This recognition is important not for us, but for the problem it highlights. India produces millions of graduates every year, yet a significant percentage struggle to find meaningful employment. Among them, a large number are first-generation and underserved youth who never even get a fair chance to be evaluated beyond their degrees. At Xcelevate, we are trying to solve exactly that. Through our residential Gurukul model in Chennai, we work with high-potential youth from underserved backgrounds not just to train them, but to prepare them for real careers in corporate environments. The idea is simple: talent is everywhere, it just needs the right structure, mentorship, and opportunity to be unlocked What we are seeing reinforces this belief: Strong performance in demanding corporate roles High retention Growing confidence and ownership This is still a small step relative to the scale of the problem. But it is a start. Thank you again to The Better India for telling this story. 👉 Read more: https://lnkd.in/gdXuGTwG

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Generative AI and Character Design: An overview of Zuraverse's Approach I had a fascinating conversation with my best buddy, Abhishek Sagar , the founder of Zuraverse.xyz, about how his team leverages generative AI for character design. It's a complex challenge, especially for a gaming platform with thousands of unique, NFT-based characters that need to maintain consistency while remaining true to their core identity. Abhishek shared some great insights, particularly their method of creating highly descriptive character prompts. Instead of generic descriptors, they use multi-layered strategy for character design consistency: • Prompt Engineering: They use a "recipe" of descriptive elements for each character. This goes beyond just physical appearance and includes: • Core Visuals: Specific details on body shape, color palette, unique markings (scars, tattoos), and accessories (a glowing sword, a specific type of armor). • Personality & Emotional Cues: Describing a "mischievous rogue with a sly grin" or a "somber sorceress with a furrowed brow" helps the AI generate consistent facial expressions and body language. • Style Cues: They include instructions to maintain a specific art style, whether it's "hyper-realistic," "anime-style," or "dark fantasy," to ensure all characters in a specific game universe look cohesive. • Reference Images: In addition to text, Zuraverse uses a core set of reference images for each character. This allows the AI to learn and replicate a character's "look and feel" with much greater accuracy, even when generating the character in new situations, poses, or wearing different outfits. • Agentic AI for Iteration: Abhishek also gave me a sneak peek into his journey with agentic AI. They are not just using a simple text-to-image generator. They're building AI agents that can take the initial character prompt and a set of rules, and then autonomously iterate on the design. This would allow the system to generate hundreds of variations—different outfits, poses, and expressions—while ensuring each one adheres to the character's core design principles. This isn't just theory—it's a practical application of AI by industry experts to tackle a real-world problem. Abhishek also promised that he will be sharing more details in the form of hands-on examples and podcasts in the coming weeks for the benefit of new explorers in his field. Feel free to checkout what zuraverse is Upto at: Zuraverse Story: https://lnkd.in/gz6Wuc4V Zuraverse: https://zuraverse.xyz Review: https://lnkd.in/gqkTSNxK #GenerativeAI #AIinGaming #Zuraverse #CharacterDesign #NFT #Gaming #AIagents #Innovation

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This year’s budget genuinely felt personal to us. The renewed focus on education, skilling, and stronger pathways to employment reinforces something we witness every day on the ground that talent is everywhere, but opportunity is not. When policy places employability at the center, it sends a powerful signal that the future of India’s youth is worth investing in. At Xcelevate Skills Foundation, our mission has always been aligned with this thinking: elevate underprivileged youth by equipping them with industry-relevant skills, mentoring them closely, and placing them into multinational companies where they can build dignified, sustainable careers. We don’t believe in short-term relief; we believe in long-term transformation. This budget strengthens our conviction that teaching real, market-ready skills is the most impactful way to create inclusive growth. When intent at the policy level meets execution at the grassroots, excellence is no longer limited by background. For us, this budget isn’t just an announcement. It’s validation of a shared purpose and a reminder that together, we can turn potential into progress at scale.

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I found Manish Sood’s perspective on the importance of real-time, unified data particularly compelling. His emphasis on what he calls “data in motion” really resonated with me, especially in the context of where enterprises are heading with agentic AI. What stood out most was the clear message that data can no longer be treated as a downstream IT concern or something to be fixed incrementally through legacy systems. In an environment where AI agents are expected to reason, act, and adapt in near real time, the quality, timeliness, and trustworthiness of data become strategic differentiators. Without that foundation, even the most advanced AI initiatives are at serious risk of underperforming or failing altogether. I strongly agree with the view that this is ultimately a leadership responsibility. If data strategy isn’t owned and driven from the top—by CEOs and executive teams—it’s unlikely to receive the sustained investment, governance, and cultural shift required to succeed. Real-time data infrastructure underpins intelligent decision-making, automation at scale, and long-term competitiveness, and it deserves the same level of attention as any other core business asset. The takeaway for me was a challenge to rethink how we design and prioritize data platforms—not just to support analytics, but to enable continuous, intelligent action across the enterprise. In the age of agentic AI, data in motion isn’t optional; it’s foundational. #AgenticAI #DataInMotion #RealTimeData #DigitalTransformation https://lnkd.in/eEBDQMQH

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Our own EVP, Chief Scientist & Head of Enterprise AI Prem Natarajan recently spoke to TechTarget about Capital One’s partnership with the National Science Foundation (NSF), which will help launch five new National AI Research Institutes to drive breakthroughs in high-impact areas across society like material and computational sciences, economics, and mental health. https://bit.ly/4grWY3m

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MCP - a open protocol for AI (LLM) to talk to other tools / systems / applications. Naive, but don’t judge me, I was judging AI capabilities with me being Naive   - So I asked Claude AI to create an MCP - An MCP the AI itself will use - Gave a website address to which MCP had to be created (with public APIs) - It Generated extensive, detailed code - I dwelled on it, fine tuned for my preference / requirements, it went ahead and did a bit more than I asked for. Website was analysed in minutes (amusing and scary) - I asked it to package it as executable package - I had configured file system MCP - So, Claude leveraged that and created a python project in filesystem and created Project with proper files and folder structure - Here comes Claude code (CC) - This python project of MCP server, was not in a running state - Asked CC to make the code runnable (of course I was in control (manual loop) of the changes it was making) - MCP server to run in local system (MacOs) needed some changes in trivial python code, CC made the changes - Interesting side part, during this whole process, it was also creating documentation, to install server, to run server and the MCP config for other tools - At times I had to say update the documentation - OOPS !! Code got changed, but what was changed ? - I asked CC to make this project version controlled. Oh my Devaa (God), it converted the project into a Git repo (local) - Created git related files, Auto committed all files. All I had to do was, say yes, go ahead - Well, we got side tracked, lets get back to MCP - So, now I asked CC to run the server (lazy to copy the command and run it in next tab terminal) - Obviously.. It had issues, and obviously it auto corrected the code - It wrote test cases, wrote test start script, tested it, committed the code and then - now it tells me, 'All fixed, Want to run?', Howdhu maga howdhu, run (yes dude yes, run) - MCP server started. I updated MCP configuration and restarted Claude Desktop - pssssttt….. curios? - :( Error: MCP server couldn’t be started - Again me being extremely (purposefully) lazy, told CC, you are being dumb, fix the startup error - I guess, I hurt its Ego. - It asked permissions for MCP server log file. whaaaat really ?, it wants to read log files now, wow. - It test ran with its test scripts, read the log, analysed like a nerd, updated the test files and code, reran until it was fixed and updated the documentation and also committed the code - What can I say, I was watching Christopher Nolan movie level events. - Finally, MCP worked, I tested few things, results were as expected.   It ain’t over, my architectural / Engineering hormones kicked in. How about containerisation ? How about productionising it ? How about Security & Authentication ? How about Performance & Scalability ? How about Operational Readiness ? How about AI Security, Gaurdrails ? Stay tuned, I will be back 🙂

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Thrilled to see the Build with AI – Pune | GenAI Workshop from GDG Cloud Pune come alive at Data Axle India Workshops like these, exploring ADK, MCP, multi-agent systems, and real-world GenAI, show the true power of community-driven learning. And this is only the beginning. At Data Axle, we aim to build a vibrant, open tech-learning ecosystem with monthly community meetups focused on Python / Django, React, MS .net, C++, Amazon Web Services (AWS), Google Cloud, Databricks, AI, and its use cases, as well as in-depth architecture discussions and hands-on engineering sessions. If you are excited about sharing knowledge, hosting a meetup, or collaborating on tech events, please don't hesitate to reach out to me. Let’s grow this community together, make Pune a hub of continuous learning and innovation, and build a movement where learning never stops and everyone grows together.

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RAG can generate answers. Agents can orchestrate workflows. Yet neither delivers real value without the right data foundation. That’s why ISO 20022 is such a big opportunity right now. For years, payments data has been constrained by legacy formats: flat, inconsistent and hard to analyse. ISO 20022 changes that by introducing richer, structured and more granular data across the entire payments lifecycle And that changes everything. Better data doesn’t just mean better payments. It means: - More accurate fraud detection - Stronger analytics and insights - Greater automation and efficiency - New value-added services built on top of payments data Here’s the catch: AI, whether it’s RAG, agents, or advanced analytics, only works as well as the data it’s built on. Without structured, high-quality, connected data, you’re just scaling inefficiency. That’s why a framework-led approach to payments modernisation is so important. It’s not about ticking the ISO 20022 compliance box; it’s about unlocking the value of the data and building the foundations for AI-driven innovation. This is a great blog from my colleague Anand Vaidya Icon Solutions on how to approach this transformation: https://lnkd.in/eCAeA4QM The real question for banks now isn’t “Are we ISO 20022 compliant?” It’s “Are we actually using the data to create value?”

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Very Interesting perspectives, I may disagree with a few and align with Many of the views shared, interesting views, perspectives, and practices nevertheless !! 1. The Counterintuitive Truth: Code Quality Does Not Equal Product Success Prasanna’s most striking lesson for engineers is that there is no direct relationship between high code quality and building a successful product. While technical excellence is a worthy goal, it is not the end goal. The ultimate measure of success is whether you are solving a real problem for people. < I am on the Edge with this one. While I am a strong proponent of Quality output/outcome, the ultimate measure of success is, however, the real problem solved :) Ramanan Natarajan - Would love to hear your thoughts on this :) 2. The Real Productivity Engine: Structure as the Foundation for Tools While Block is gaining attention for its powerful internal AI agent, Goose, Prasanna reveals that the single most impactful change for boosting productivity wasn't a tool, but a fundamental organizational restructure. The company shifted from a siloed structure to a unified, functional one. This new functional structure unlocked three primary benefits: > It created a singular focus on technology and technical excellence across the entire organization. > It allowed leaders to drive forward AI and platform depth for the whole company, rather than in isolated pockets. > It changed the hiring mindset. Instead of treating engineers as a "commodity" to be added to a business unit to increase feature output, "mythical man month", the focus shifted to building common platforms and leveraging deep experts across the entire organization. This unified structure not only drove technical depth but also created the ideal environment for small-scale experiments to be identified, supported, and scaled across the company, rather than dying within a business unit silo. < It's not always the Tool, it's the Mindset !! 3. The Principle of Momentum: Start Small to Win Big: The most successful and durable innovations rarely begin as massive, top-down corporate initiatives. Instead, they grow from small, focused experiments. < "Start small with everything." 4. The Human Element: Hire for a "Learning Mindset": The company now optimizes for a "learning mindset." They are less concerned with finding "amazing AI practitioners on the get-go." Instead, they prioritize finding people from recent college graduates to industry veterans who are eager, open to learning, and willing to embrace new tools. < Meta cognition is undervalued !! #organisationCluture #AI #Productivity https://lnkd.in/gw6saKXp

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