Writing about development and technology.
Clarifying AR, VR, MR, and XR concepts using the 'Window vs Door' analogy. Sharing practical experience of reducing e-commerce return rates from 30% to 8% by implementing AR features.
Why 5G is more than just faster internet. A breakdown of eMBB, URLLC, and mMTC with real-world use cases.
Understanding Web3 concepts and applications through practical experience
Users complained the service was slow, but I was blindly grepping log files. I share how I moved from 'driving blind' to full observability using Prometheus and Grafana, and explain Google's 4 Golden Signals of monitoring.
I updated the database, but the page still shows old data. We analyze the powerful (and evil) caching mechanism of Next.js 13+ in 4 layers, compare it with React Query, and share practical debugging strategies.
Understanding Terraform principles and practical applications through project experience
Deleting 500 lines of loading states with React Suspense. How to handle async UI declaratively.
Solving server waste at dawn and crashes at lunch. Understanding Auto Scaling vs Serverless through 'Taxi Dispatch' and 'Pizza Delivery' analogies. Plus, cost-saving tips using Spot Instances.
Understanding load balancing principles and practical applications through project experience
Anatomy of the GCC pipeline. Preprocessor, Compiler, Assembler, and Linker. What happens when you type `gcc main.c`.
Both are children of Transformer, so why the difference? Using 'Fill-in-the-blank' vs 'Write-next-word' analogies to explain BERT vs GPT. Practical guide based on trial and error.
I share my experience with overfitting in machine learning. I was fooled by 99% training accuracy, only to fail in production. Learn how I used Dropout, Regularization, and Data Augmentation to build 'real intelligence' instead of a memorization machine.
Overcoming RNN's 'dementia' and how Google flipped the world with 'Attention Is All You Need'. From Query-Key-Value library analogies to Multi-Head Attention and Vision Transformers.
Understanding vector database principles and practical applications through project experience
How do computers understand that 'King' - 'Man' + 'Woman' = 'Queen'? We dive deep into the evolution of NLP embeddings, from One-Hot Encoding to Word2Vec and Transformer-based models. Learn about Vector Databases, Cosine Similarity math, and how RAG (Retrieval-Augmented Generation) is reshaping modern AI applications.
Understanding differences and selection criteria between fine-tuning and prompt engineering for LLM customization
My AI chatbot was hallucinating wild answers to customers. Here's how I implemented RAG (Retrieval-Augmented Generation) to fix it, covering Vector DBs, Embeddings, and Hybrid Search.
Understanding Transformer architecture through practical experience
Understanding RNN and LSTM principles through practical project experience
A strategic guide for Architects. Covers Conway's Law, Distributed Patterns (Saga, CQRS), Modular Monolith, Migration Strategies, Glossary, and FAQ.
