AI: Through an Architect's Lens
Exploring AI/ML concepts from a distributed systems architect's perspective — bridging theory with production-grade engineering.
Neural Networks & The Learning Mechanism
Building deep intuition from first principles — how neural networks actually learn, explained step by step for engineers who want to truly understand the machinery before architecting with it.
From Sequences to Transformers
The journey from “words in order” to “understanding meaning” — how we taught machines to process language, and why the Transformer changed everything.
Understanding the LLM Machine
The technical foundations that drive every architectural decision — transformers, embeddings, and tokenization- are explained through the lens of cost, performance, and trade-offs.
Making Decisions with LLMs
From model selection to production reliability — the decision frameworks that separate prototype AI from enterprise systems.
Production RAG: What Tutorials Don’t Teach You
From naive retrieval to production-grade systems — the architectural patterns, chunking strategies, and retrieval engineering that separate demo RAG from enterprise RAG.