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Imagine you're building the next Amazon. Your application needs to store: Customer information Product catalog Orders Payments Reviews Shopping carts One of the first questions you'll face is: Should I use SQL or NoSQL?
Imagine you're using Amazon during the Big Billion Sale. You search for: "iPhone 16 Pro" Within milliseconds, thousands of matching products appear. Now imagine Amazon had to scan every product in its database before showing the results. Instead of milliseconds... It could take minutes. Imagine the experience for millions of users.
System Design Series — Part 33 Imagine you're ordering food on Swiggy. You click "Place Order." The app sends a request to the Payment Service. Suddenly... The Payment Service doesn't respond. Was the payment server completely down?
Semantic Kernel vs LangChain for .NET AI apps: we compared both on a fintech API doc assistant and LMS Q&A bot—DI integration, plugins, observability, and which framework fits production C# teams.
ChatGPT and GitHub Copilot for .NET developers: production-tested prompts for ASP.NET Core APIs, EF Core queries, unit tests, and code review—plus honest limits when AI-generated C# ships to prod.
SOLID is not academic vocabulary—see each principle applied to C# code you might write this week, with before-and-after refactors you can use in reviews.
A practical roadmap for .NET interviews in 2025: C# fundamentals, ASP.NET Core, SQL, system design basics, and how to answer behavioral questions without sounding rehearsed.
How to choose .NET OSS projects, land meaningful PRs, and turn contributions into interviews—without burning weekends on abandoned repos.
TypeScript for C# developers: map interfaces to records, structural typing vs nominal, async pitfalls, and real migration stories from ASP.NET teams adopting Angular or React frontends.
ML.NET vs generative AI: when classical machine learning still wins for fraud scoring, demand forecasting, and churn prediction on .NET—cheaper, auditable, and often more accurate than LLM guesses.
Local LLMs with Ollama for offline .NET development: run Llama and Mistral on your machine for docs, tests, and refactors without sending fintech or LMS code to the cloud—setup, limits, and honest trade-offs.
Records, primary constructors, minimal hosting, Native AOT considerations, and collection expressions—practical .NET 8 features you will actually write, not release-note trivia.
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