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Basic System Design Tutorial for Non Developers - 23 Building Blocks Ever nodded along in a design review when someone said "just put a queue in front of it"? This video explains system design in plain English: the 23 building blocks behind every large system, from online stores to Instagram to your bank's app. No code, no jargon you can't repeat in a meeting. Built for Technical Program Managers, Product Managers, Engineering Managers and anyone preparing for system design or TPM interviews. What you'll learn: ✅ How one online order travels end to end, in under a second ✅ What each block does: DNS, CDN, API gateway, load balancers, cache, SQL vs NoSQL, sharding, replication, pub/sub, queues, object storage, search, AuthN/AuthZ, encryption, observability, CI/CD and disaster recovery ✅ What goes wrong with each one, and the risks to raise in reviews ✅ Meeting-ready one-liners you can use straight away ✅ 4 questions that change every design (gold for interviews) ✅ The "Reason → Block → Trade-off → Safety net" way to answer design questions ⏱️ Chapters ## Chapter times - 00:00 — Introduction: System Design in Simple Terms - 01:33 — The Big Picture: 23 Blocks, Eight Groups - 01:56 — Following One Order End to End - 04:22 — The Front Door: Client, DNS & CDN - 07:21 — Traffic Control: API Gateway, Rate Limits & Load Balancers - 10:22 — Doing the Work: Stateless Services, Monoliths & Microservices - 12:16 — Remembering Things: Cache, Databases, Sharding & Replication - 15:51 — Passing Work Along: Pub/Sub, Streaming & Queues - 17:32 — Files & Finding: Object Storage & Search - 19:21 — Security: Authentication, Authorization, Encryption & Secrets - 21:27 — Running It Well: Observability, CI/CD & Disaster Recovery - 24:12 — Putting It All Together - 24:44 — Four Questions That Shape Every Design - 25:14 — Interview Tip: Reason, Block, Trade-off & Safety Net - 25:52 — Wrap-up & What’s Next 💬 Which of the 23 blocks was new to you? Tell me in the comments. 🔔 Subscribe for the next video, where we use these same blocks to design a URL shortener, Instagram and a shopping cart. I'm Jacinth Paul, from Program Strategy HQ: practical program strategy, AI and system thinking for TPMs and engineering leaders. 🌐 https://programstrategyhq.com #SystemDesign #TechnicalProgramManager #TPM #SystemDesignInterview #ProductManagement #SoftwareArchitecture My Linkedin: https://www.linkedin.com/in/jacinthp/ --------------------------------------------- Github: https://github.com/jacinthpaul --------------------------------------------- Website: https://www.programstrategyhq.com/ ---------------------------------------------

Over 40% of agentic AI projects may be canceled by 2027, and research shows most multi-agent failures come from system design, not the model. Here are 3 systems-thinking moves for building AI agents that work.

Will AI replace project managers? Is your project management career at risk because of Artificial Intelligence? And what should Project Managers, Program Managers, Scrum Masters, and Delivery Managers do now to stay relevant? In this video, we explore the future of project management in the AI era, using the latest 2026 research from India and around the world. AI agents and automation tools are already changing how teams handle project planning, status reporting, risk management, agile delivery, and software development. But does this mean AI will replace project managers, or will the role evolve? We'll look at research from PMI, NIIT, CIEL HR, Anthropic, and other industry sources to understand what's really happening in the job market. More importantly, I'll share a practical **90-day action plan** to help experienced project and program managers build AI skills, adapt to AI-native delivery, and future-proof their careers. 🎯 What you'll learn: - Will AI replace Project Managers and Program Managers? - What 2026 research reveals about AI and jobs in India - Which project management tasks AI can automate - The future of Scrum Masters, Delivery Managers, and TPMs - Why AI-native project management is becoming important - Five practical steps to stay relevant in the AI era - The skills project managers should develop for 2027 and beyond ⏱️ Video Chapters 00:00 – Will AI Replace Project Managers? 00:45 – Why AI Is Changing Project Management Careers 02:00 – What 2026 Research Says: India and Global Trends 05:00 – How AI Is Changing Day-to-Day Project Management 09:00 – Five Things Project Managers Should Do Now 12:30 – The Future of Project and Program Management 14:15 – Final Thoughts and Career Advice 📚 Research & References PMI – AI Fluency and the Future of Project Management (October 2026) https://www.pmi.org/about/press-media/2026/project-management-institute-helps-a-growing-profession-deliver-greater-value NIIT – India Skills Gap Report 2026 https://www.niit.ai/india/press-release/niit-india-skills-gap-report CIEL HR – Agentic AI Jobs in India (September 2026) https://www.cielhr.com/news/press-release/agentic-ai-jobs-india-demand-260-percent Anthropic – Labor Market Impacts of AI (March 2026) https://www.anthropic.com/research/labor-market-impacts 💬 Let's discuss! As a Project Manager, Program Manager, Scrum Master, or Delivery Manager, which part of your job do you think AI will change the most? Share your thoughts in the comments! 🔔 Subscribe to Program Strategy HQ Practical insights on AI, AI-native software engineering, project management, program management, technology leadership, and future-ready career skills. https://www.youtube.com/@programstrategyhq **#ProjectManagement #ArtificialIntelligence #AIJobs #ProgramManagement #FutureOfWork #AINative #CareerGrowth** My Linkedin: https://www.linkedin.com/in/jacinthp/ --------------------------------------------- Github: https://github.com/jacinthpaul --------------------------------------------- Website: https://www.programstrategyhq.com/ ---------------------------------------------

AI Memes 😂 courtesy: everydaylentils tiktok

AI Agent Evals - A Manager’s Playbook - Fundamentals Tutorial Your AI agent “feels worse” after the last change. Can you prove it either way? This video is a practical, manager-level guide to AI agent evals: what they are, why every AI team needs them, the different types, how to build them, and how to track them. It’s for engineering managers, TPMs and product leaders who are either putting AI agents into their SDLC (coding agents, PR reviewers, test generators) or shipping AI products (chatbots, support agents, research copilots). It’s based mainly on Anthropic’s engineering guide, “Demystifying evals for AI agents”. What you’ll learn: ✅ Testing vs evals, and why you need both ✅ The anatomy of an eval: task, trial, grader, transcript, outcome ✅ Code-based vs LLM-as-judge vs human graders, and the order to use them in ✅ Capability evals vs regression evals ✅ pass@k vs pass^k: why 75% per run becomes 42% when it has to work 3 times in a row ✅ How to evaluate coding, conversational, research and computer-use agents ✅ A 9-step roadmap from zero to your first eval suite ✅ Wiring evals into release gates (PR → nightly → canary → GA) ✅ What to track on an eval dashboard  ​ 1. Intro & Overview — 0:05 2. The Anthropic Paper & The Problem — 1:06 3. Evals vs. Traditional Testing — 2:17 4. Why Managers Should Invest in Evals — 3:21 5. Key Vocabulary — 4:21 6. Grading Approaches — 5:25 7. Pass@K vs Pass^K — 6:32 8. Evaluating Different Agent Types — 7:31 9. Building Your Eval Suite — 8:25 10. When Evals Go Wrong — 9:48 11. Connecting Evals to Releases — 10:40 12. Dashboard Views — 11:29 13. Layers of Evidence — 12:12 14. Ownership & Accountability — 13:01 15. Action Items & Checklist — 13:47 16. Wrap-up — 14:33 📖 Main reference: https://www.anthropic.com/research/demystifying-evals-for-ai-agents 🌐 More playbooks: https://programstrategyhq.com 👉 Subscribe to Program Strategy HQ for practical guides on AI-native delivery, technical program management and agentic AI. #AIEvals #AIAgents #LLMEvaluation #TechnicalProgramManagement #AgenticAI #AIinSDLC #ProgramStrategyHQ My Linkedin: https://www.linkedin.com/in/jacinthp/ --------------------------------------------- Github: https://github.com/jacinthpaul --------------------------------------------- Website: https://www.programstrategyhq.com/ ---------------------------------------------

Your AI agent says the refund is done. The trace shows three mistakes. That's why you need evals. In this Short: what AI agent evals are, the four pillars to measure (outcome, trajectory, operations, safety) and three ways to score them (code checks, LLM-as-a-judge, human review). Full 5-chapter video in the comments. Jacinth Paul · AI Native Engineering #shorts #AIAgents #LLMEvaluation #AgentEvals #LLMasaJudge #AISafety #GenerativeAI