Artificial intelligence
On-Device AI for Mobile: Tiny LLMs, Vision Models, and Private Inference
- Sudhir Mangla
- Mobile Architecture , Artificial intelligence
- 06 Dec, 2025
1 The Strategic Foundation: The Hybrid Compute Spectrum Mobile AI systems now have three realistic places where computation can run: the cloud, the edge (MEC), and directly on the device. Each t
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Code Review Copilot for .NET Repos: Combining Roslyn Analyzers, GitHub, and Azure OpenAI
- Sudhir Mangla
- Artificial intelligence , Code Review
- 01 Dec, 2025
1 The Era of Hybrid Code Review: Beyond Static Analysis Software teams rely on pull requests to maintain code quality and consistency, but expectations around PR review have grown significantly.
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Real-Time Recommendation Engines in .NET: Combining Collaborative Filtering, Deep Learning, and Vector Databases
- Sudhir Mangla
- Practical Design , Artificial Intelligence
- 26 Nov, 2025
1 The Modern Recommendation Landscape: Beyond Simple Filtering A recommendation engine must predict what a user is likely to want at the moment they need it. Early systems relied heavily on coll
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The Architect's Guide to Vibe Coding Workflow: Mastering the AI Development Loop
- Sudhir Mangla
- Artificial intelligence , Vibe Coding Workflow
- 20 Nov, 2025
1 Introduction: The Shift from Syntax to Intent Software development has always involved trade-offs between speed, clarity, and long-term maintainability. As AI-assisted development becomes main
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The Ultimate Guide to AI Code Generation: Vibe Coding, Prompt Engineering, and Mastering the New SDLC
1 The New Era of AI-Driven Development AI has moved from novelty to necessity in modern software engineering. Frameworks like ASP.NET Core 8, Entity Framework Core, and frontend stacks s
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From Single Agents to Agentic Systems: A Practical Blueprint for Senior Engineers
- Sudhir Mangla
- Artificial intelligence , GenAI patterns
- 23 Oct, 2025
1 Foundations: Agents vs. Agentic Systems In this opening section, we’re going to lay the conceptual groundwork for the shift from single agents to agentic systems. If you’re a senior engineer, te
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The AI Test Engineer: Automating Test Case Generation and Documentation with LLMs
- Sudhir Mangla
- Artificial intelligence , Software Testing
- 20 Sep, 2025
1 Introduction: The New Frontier of Quality Assurance Quality assurance has always been the backbone of reliable software delivery. Yet, despite decades of progress in automation, a stubborn bottl
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The Agent-Driven Spec: From Product Requirement Document to Production-Ready Tech Specifications in Days, Not Weeks
- Sudhir Mangla
- Artificial intelligence , GenAI patterns
- 19 Sep, 2025
1 Introduction: The End of Ambiguity Product development in software has always carried a paradox: the more detail you add to requirements, the more room there seems to be for misinterpretation. E
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Bandit-Driven Feature Flags in ASP.NET Core (with Azure ML)
- Sudhir Mangla
- Artificial intelligence , .Net architecture
- 18 Sep, 2025
1 Introduction: The Evolution from "If" Statements to Intelligent Decisions Software teams have long relied on feature flags and A/B testing to control rollouts and optimize user experiences. At t
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The Self-Writing Report: Architecting Automated Business Insights with Azure OpenAI and Power BI
- Sudhir mangla
- Artificial intelligence , Data analytics
- 23 Aug, 2025
Executive Summary / Abstract For decades, business intelligence (BI) has been dominated by static dashboards and manual interpretation. While these dashboards excel at visualizing what happened,
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The Architecture of Recommendation Systems: From Collaborative Filtering to Deep Learning
- Sudhir mangla
- Artificial intelligence , Cloud architecture
- 15 Aug, 2025
1 Introduction: Beyond the Algorithm Every architect knows the temptation of focusing only on the model. But in practice, a recommendation engine is not “just an algorithm”—it’s a living, evolving
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Semantic Kernel vs. LangChain.NET: An Architect's Guide to Choosing the Right AI Framework
- Sudhir mangla
- Artificial intelligence , Enterprise ai
- 03 Aug, 2025
1 Executive Summary: The Architect’s TL;DR 1.1 Why This Matters Now: The Rise of Composable AI The AI landscape is shifting rapidly. Where yesterday’s architectures revolved around deploying
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Running AI On-Prem: A Practical Guide to Using Local LLMs (like Phi-3 & Llama 3) in .NET
- Sudhir mangla
- Artificial intelligence , Enterprise ai
- 01 Aug, 2025
Running AI On-Prem: A Practical Guide to Using Local LLMs (like Phi-3 & Llama 3) in .NET Abstract The rapid progress in Large Language Models (LLMs) has ushered in an era where AI is no longer
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Integrating Azure AI Services: An Architect’s Playbook for Building Smarter .NET Applications (2025 Edition)
- Sudhir mangla
- Artificial intelligence , Azure
- 11 Jul, 2025
1 The 2025 AI-Powered Application: A Paradigm Shift for .NET Architects 1.1 Introduction: Beyond the Hype – Practical, Agentic AI for the Enterprise As we move deeper into 2025, conversations
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AI as the Architect’s Copilot: Leveraging GenAI for System Design and Documentation (2025 Guide)
- Sudhir mangla
- Artificial Intelligence
- 09 Jul, 2025
1 Introduction: The New Architectural Imperative 1.1 The Modern Architect’s Dilemma If you’re a solution architect, system architect, or technical leader, you’re living in a time of relentles
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Building with Azure OpenAI On Your Data: A Secure and Private Alternative to Public APIs
- Sudhir mangla
- Artificial Intelligence , Enterprise AI
- 02 Jul, 2025
1 Introduction: The New Frontier of Enterprise AI 1.1 The Generative AI Revolution: A Paradigm Shift in Artificial Intelligence The world of artificial intelligence has undergone a quiet but
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Using LangChain with C#: A Primer for Building Composable AI Applications
- Sudhir mangla
- Artificial Intelligence
- 01 Jul, 2025
1 Introduction: The New Paradigm of AI-Native Applications 1.1 Beyond the API Call: The Shift to Composable, Intelligent Systems AI has quickly evolved from a futuristic concept to a key driv
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Architecting LLM-Powered Applications: A Comprehensive Guide for .NET Architects
- Sudhir mangla
- Artificial Intelligence , Genai patterns
- 26 Jun, 2025
Abstract This guide offers .NET architects a comprehensive framework for designing, building, and deploying robust applications powered by Large Language Models (LLMs). Moving beyond theoretical d
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What is a Vector Database? The Missing Piece in Your GenAI .NET Application Explained
- Sudhir mangla
- Artificial Intelligence
- 23 Jun, 2025
1 Introduction: The Generative AI Revolution and the Unseen Challenge for .NET Architects 1.1 The Generative AI Gold Rush Over the past several years, the landscape of software development ha
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From Monolith to AI-Driven Microservices: An Architect’s Modernization Playbook
Article Summary This in-depth guide is tailored for software architects, particularly those working with C# and .NET, who are responsible for leading legacy application modernization. The article
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Fine-Tuning LLMs with C#: A Practical Guide to Customizing Models with ML.NET
- Sudhir mangla
- Artificial Intelligence
- 20 Jun, 2025
Abstract As artificial intelligence continues to shape the modern enterprise, Large Language Models (LLMs) like GPT, Llama, and Mistral are increasingly integrated into business solutions. While t
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Introduction to Semantic Kernel: The .NET Developer's Guide to Building Powerful AI Agents
- Sudhir mangla
- Artificial Intelligence
- 20 Jun, 2025
1 Introduction: The Dawn of the AI-Powered .NET Application Artificial intelligence is no longer a futuristic ideal reserved for research labs and Silicon Valley giants. It's becoming the backbone
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Practical Azure AI Agent Use Cases for Large Enterprises | Real-World Applications
- Sudhir mangla
- Artificial Intelligence
- 07 May, 2025
1 Introduction: The Dawn of the Agent-First Enterprise Enterprises are entering a new era of intelligent automation. For the past decade, the focus has been on automating repetitive tasks through
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Prompt Engineering Is Obsolete: The Shift Towards Intuitive AI Interactions
- Sudhir mangla
- Artificial Intelligence
- 05 May, 2025
Abstract Prompt engineering captured the imagination of developers and architects as AI systems became accessible to the mainstream. Carefully crafted textual prompts opened doors to creative auto
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