Priya Sarkar

Priya SarkarAug 10, 2026

My Online LinkedIn Community is on the way to hit 𝟏𝟎𝐊 𝐬𝐨𝐨𝐧 !! 𝐈 𝐚𝐦 𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐚 𝐧𝐞𝐰 𝐒𝐞𝐫𝐢𝐞𝐬: VibeCoder to AI Specialist in 30 Days …. I have been actively posting on LinkedIN since last 1 year I have spoken about building AI Products Sustainable AI Products, which are just not VibeCoded But ones which actually pass the Production daylight Building your Brand, Growing your Presence Online, beyond Office walls …. Here’s a re-intro about me.. → Hi I am Priya, I work as an AI Implementation Lead in UAE → I spent 10 years of my career building AI Products across US, Germany, India, UAE and KSA …. Yes, I have been building AI products even before it used to be fancy career → Now I learn from kids teaching me how to vibecode an AI product in 1hr….. → I had worked for JP Morgans Delinquency Models Which took us 1 yr to put it in Production I had worked for STA Forecasting Models Which took us 4-6 Months just to validate the product Sorry kids, vibecoding just looks great on social media Real World AI Solutions are messy!! The real work in AI starts once you finsh vibecoding the app.. So if you are an AI Lead / Founder, who wants to understand what an AI roadmap in real companies look like A mid senior professional who is stuck with AI pilots that never scale, unclear ROI, and pressure from leadership to show real business impact A junior professional who is overwhelmed by tools and wants to build skills that companies are actively hiring for 𝐅𝐨𝐥𝐥𝐨𝐰 𝐦𝐲 𝐩𝐚𝐠𝐞 Priya Sarkar | Follow the Vibe Coder to AI Specialist in 30 Days Series Over the next 30 days, I’ll be sharing practical insights on building your first AI app - covering not just Vibe Coding, but the essentials most people overlook: AI Governance, Guardrails, Validation, Production Guidelines, sharing real-world lessons, practical frameworks, and the behind-the-scenes that turns ideas into working AI products. #ArtificialIntelligence #AI #AIEngineering #GenerativeAI #AIAgents #ProductionAI #MLOps #TechCareers #AILeadership #BuildingInPublic #LinkedInCreator #PersonalBranding #FutureOfWork #AICommunity #LearnAI

Priya SarkarAug 11, 2026

𝐃𝐚𝐲 𝟏 of Vibe Coding -> AI Specialist Series 𝐁𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐀𝐈 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫 isn't about learning one framework. It's about mastering 𝐞𝐚𝐜𝐡 𝐥𝐚𝐲𝐞𝐫 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐈 𝐬𝐭𝐚𝐜𝐤, one step at a time. One of the biggest mistakes people make is jumping straight into 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬. But reliable AI systems aren't built that way. Every layer builds on the one before it. The goal isn't just building another AI application. It's becoming a 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐀𝐈 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫 who can 𝐝𝐞𝐬𝐢𝐠𝐧, 𝐝𝐞𝐩𝐥𝐨𝐲, 𝐚𝐧𝐝 𝐬𝐜𝐚𝐥𝐞 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐀𝐈 𝐬𝐲𝐬𝐭𝐞𝐦𝐬. 𝐊𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬: ➤ Don't chase every new AI tool. ➤ Build one layer at a time. ➤ Strong foundations create better AI systems. 📌 Save this roadmap for your AI learning journey. 𝐖𝐡𝐢𝐜𝐡 𝐬𝐭𝐚𝐠𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐫𝐨𝐚𝐝𝐦𝐚𝐩 𝐚𝐫𝐞 𝐲𝐨𝐮 𝐜𝐮𝐫𝐫𝐞𝐧𝐭𝐥𝐲 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠? P.S this Poster is part of the 𝟑𝟎 𝐃𝐚𝐲𝐬 𝐕𝐢𝐛𝐞 𝐂𝐨𝐝𝐢𝐧𝐠 -> 𝐀𝐈 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭 𝐒𝐞𝐫𝐢𝐞𝐬 (more info in the comments) --------- Hi I’m Priya Sarkar | AI Tech Lead based out of UAE. It's been 𝟏𝟎 𝐲𝐞𝐚𝐫𝐬 I have been 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐀𝐈 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬 𝐚𝐜𝐫𝐨𝐬𝐬 𝐭𝐡𝐞 𝐔𝐒, 𝐆𝐞𝐫𝐦𝐚𝐧𝐲, 𝐈𝐧𝐝𝐢𝐚, 𝐔𝐀𝐄, 𝐚𝐧𝐝 𝐊𝐒𝐀…. I have literally worked across 3 countries. **Data Scientist, AI Engineer, AI Product Manager, AI Lead** -> wore all this hats. If you wish to know 𝐖𝐡𝐚𝐭 𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐢𝐧 𝐅𝐨𝐫𝐭𝐮𝐧𝐞 𝟓𝟎𝟎 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐥𝐨𝐨𝐤 𝐥𝐢𝐤𝐞? 𝐇𝐨𝐰 𝐝𝐨𝐞𝐬 𝐭𝐡𝐞 𝐣𝐨𝐮𝐫𝐧𝐞𝐲 𝐨𝐟 𝐌𝐨𝐝𝐞𝐥 𝐭𝐨 𝐚𝐜𝐭𝐮𝐚𝐥 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐥𝐨𝐨𝐤 𝐥𝐢𝐤𝐞? 𝐖𝐚𝐧𝐭 𝐭𝐨 𝐤𝐧𝐨𝐰 𝐰𝐡𝐚𝐭 𝐃𝐚𝐭𝐚 𝐋𝐞𝐚𝐝𝐞𝐫𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬 𝐢𝐧 𝐁𝐨𝐚𝐫𝐝𝐑𝐨𝐨𝐦𝐬? Follow my page - Priya Sarkar #ArtificialIntelligence #AI #AgenticAI #AIAgents #LLM #GenerativeAI #Python #MachineLearning #RAG #AIEngineering #MLOps #AIDevelopment #TechCareers #LearningJourney #FutureOfAI

Priya SarkarAug 14, 2026

𝐃𝐚𝐲 𝟐 of Vibe Coding -> AI Specialist Series 𝐁𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐀𝐈 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫 isn't about learning one framework. It's about mastering 𝐞𝐚𝐜𝐡 𝐥𝐚𝐲𝐞𝐫 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐈 𝐬𝐭𝐚𝐜𝐤, one step at a time. Every response an 𝐋𝐋𝐌 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐬 𝐛𝐞𝐠𝐢𝐧𝐬 with predicting the 𝐧𝐞𝐱𝐭 𝐭𝐨𝐤𝐞𝐧. That single process powers everything from 𝐜𝐡𝐚𝐭𝐛𝐨𝐭𝐬 𝐭𝐨 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬. Behind every prompt is a sequence of steps that transforms your input into a coherent response. Here's what happens every time you interact with an LLM. 💬 𝐈𝐧𝐩𝐮𝐭 𝐏𝐫𝐨𝐦𝐩𝐭 Your instruction enters the model. 🔤 𝐓𝐨𝐤𝐞𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 The text is broken into smaller pieces called 𝐭𝐨𝐤𝐞𝐧𝐬. 🧩 𝐄𝐦𝐛𝐞𝐝𝐝𝐢𝐧𝐠𝐬 Each token is converted into a numerical representation that captures its meaning. 📍 𝐏𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐄𝐧𝐜𝐨𝐝𝐢𝐧𝐠 The model learns the order of the tokens so it understands context. 🧠 𝐒𝐞𝐥𝐟-𝐀𝐭𝐭𝐞𝐧𝐭𝐢𝐨𝐧 It identifies which words matter most and how they relate to one another. 🪟 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 𝐖𝐢𝐧𝐝𝐨𝐰 The model focuses on the relevant information available within its context. 🎯 𝐍𝐞𝐱𝐭-𝐓𝐨𝐤𝐞𝐧 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 It predicts the most likely next token, one token at a time. ✅ 𝐎𝐮𝐭𝐩𝐮𝐭 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 Those predicted tokens become the response you read. The biggest misconception about LLMs is that they're 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐥𝐢𝐤𝐞 𝐡𝐮𝐦𝐚𝐧𝐬. They're not. They're continuously 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐭𝐨𝐤𝐞𝐧 𝐬𝐨 𝐚𝐜𝐜𝐮𝐫𝐚𝐭𝐞𝐥𝐲 𝐭𝐡𝐚𝐭 𝐭𝐡𝐞 𝐨𝐮𝐭𝐩𝐮𝐭 𝐟𝐞𝐞𝐥𝐬 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭. Once you understand this pipeline, many advanced AI concepts become much easier to understand. ➤ Why 𝐑𝐀𝐆 improves responses ➤ Why 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐰𝐢𝐧𝐝𝐨𝐰𝐬 matter ➤ Why 𝐩𝐫𝐨𝐦𝐩𝐭 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 works ➤ How 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 plan and take actions 𝐌𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐞 𝐟𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬 𝐟𝐢𝐫𝐬𝐭. Everything else starts to click. 𝐖𝐡𝐢𝐜𝐡 𝐬𝐭𝐞𝐩 𝐝𝐨 𝐲𝐨𝐮 𝐭𝐡𝐢𝐧𝐤 𝐢𝐬 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐦𝐢𝐬𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐨𝐨𝐝? ------------ Hi I’m Priya Sarkar | AI Tech Lead based out of UAE. It's been 𝟏𝟎 𝐲𝐞𝐚𝐫𝐬 I have been 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐀𝐈 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬 𝐚𝐜𝐫𝐨𝐬𝐬 𝐭𝐡𝐞 𝐔𝐒, 𝐆𝐞𝐫𝐦𝐚𝐧𝐲, 𝐈𝐧𝐝𝐢𝐚, 𝐔𝐀𝐄, 𝐚𝐧𝐝 𝐊𝐒𝐀…. I have literally worked across 3 countries. Data Scientist, AI Engineer, AI Product Manager, AI Lead -> wore all this hats. If you wish to know 𝐖𝐡𝐚𝐭 𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐢𝐧 𝐅𝐨𝐫𝐭𝐮𝐧𝐞 𝟓𝟎𝟎 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐥𝐨𝐨𝐤 𝐥𝐢𝐤𝐞? 𝐇𝐨𝐰 𝐝𝐨𝐞𝐬 𝐭𝐡𝐞 𝐣𝐨𝐮𝐫𝐧𝐞𝐲 𝐨𝐟 𝐌𝐨𝐝𝐞𝐥 𝐭𝐨 𝐚𝐜𝐭𝐮𝐚𝐥 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐥𝐨𝐨𝐤 𝐥𝐢𝐤𝐞? 𝐖𝐚𝐧𝐭 𝐭𝐨 𝐤𝐧𝐨𝐰 𝐰𝐡𝐚𝐭 𝐃𝐚𝐭𝐚 𝐋𝐞𝐚𝐝𝐞𝐫𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬 𝐢𝐧 𝐁𝐨𝐚𝐫𝐝𝐑𝐨𝐨𝐦𝐬? Follow my page - Priya Sarkar #ArtificialIntelligence #AI #GenerativeAI #LLM #LargeLanguageModels #MachineLearning #DeepLearning #NaturalLanguageProcessing #PromptEngineering #RAG #AIAgents #AIEngineering #DataScience #MLOps #TechEducation