AI Engineering 15 min
RAG: Storage & RetrievalA beginner-friendly guide to RAG vector databases, storage, similarity search, indexing, HNSW, and retrieval trade-offs.
Updated Jul 2026Read
My Learnings
Documenting the concepts I am learning and translating my hand written notes into crisp mental models illutrated with diagrams and implementation handy nuances.
AI Engineering 10 min
RAG: Chunking & EmbeddingA beginner-friendly guide to RAG chunking strategies, metadata, embedding model trade-offs, parsers, and retrieval quality.
Updated Jul 2026Read
AI Engineering 12 min
RAG: ArchitectureRAG 101 & its architecture.
Updated Jul 2026Read
AI Engineering 5 min
AttentionAttention mechanism helps LLM understand the context of the text and help predict the next token.
Updated Jul 2026Read
AI Engineering 8 min
Embedding & TrainingHow is an LLM trained? How does it relate 2 concepts?
Updated Jul 2026Read
AI Engineering 5 min
LLM 101: Prompts, Tokens, and Context WindowsA beginner-friendly mental model for how LLMs generate responses, how tokens drive cost, and how to write effective prompts.
Updated Jul 2026Read