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Engineering notes from the workshop floor.

The bugs, scope decisions, and hard questions that keep appearing in code reviews—written down clearly enough to use in your next build.

6

practical deep dives

From final-year scoping and viva preparation to RAG, deployment, and production-grade microservices.

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Search by the problem you are solving.

Browse every existing article by title, topic, or the specific engineering challenge inside it.

Showing 6 articles

Featured article

Spring Boot Microservices Project: What to Build, What to Skip

Most Spring Boot microservices projects are three CRUD apps in Docker with a Eureka server; here is what actually makes it a distributed-systems project, and what to cut.

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14 Jul 2026·13 min read
Spring BootMicroservicesKafkaCapstone
8 Jul 2026·11 min read

12 Viva Questions Examiners Ask About Your Final Year Project

Viva questions cluster into a few recognisable families, and in most vivas every one of them ends with the same follow-up: show me where that happens in the code.

Final Year ProjectsViva PreparationEngineering Craft
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1 Jul 2026·11 min read

How to Deploy Your Final Year Project to a Real URL

A localhost screenshot says "I got it working once." A live URL says "this runs without me." Here is the shortest honest path from your laptop to a real deployment: Docker, secrets, a health check, TLS, and CI/CD that ships on merge.

DeploymentDevOpsFinal Year Project
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23 Jun 2026·12 min read

How to Build a RAG Chatbot That Actually Retrieves

Most RAG chatbot projects fail at retrieval, not generation — here is how to chunk on structure, store in pgvector, measure recall@k, and build a refusal path that actually fires.

RAGPythonpgvector
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9 Jun 2026·11 min read

Mini Project vs Major Project: How to Scope a Final Year Build

A mini project is one hard thing done properly in four weeks. A major project is a system. Here is how to scope either one so you can actually finish it — and defend it.

final year projectcapstonescoping
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26 May 2026·11 min read

98% Accuracy? Your Final-Year ML Project Has Data Leakage

A 98% accuracy score on a real-world dataset is almost never a good model — it is a leak, and here are the four that cause it.

Machine LearningFinal Year Projectsscikit-learn
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The mistakes and trade-offs that repeatedly show up in working code.

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Written to explain why

Not just a recipe—the reasoning you need for a viva, interview, or review.

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