Curated learning paths with focused episodes. Filter by status and sort by what matters.
Eight posts taking LangChain from first principles to a working RAG pipeline — token costs, the raw OpenAI API, messages, prompt templates, structured output and LCEL.
Four posts on the NoSQL landscape — when SQL is not the right tool, and deep dives into MongoDB, Redis, and Cassandra with real schema design and production trade-offs.
Four posts on scaling databases beyond a single machine — vertical vs horizontal, partitioning and sharding strategies, CAP theorem, PACELC, and distributed transactions.
Three posts on how databases stay available when machines fail — replication models, consistency guarantees, and consensus-based automatic failover explained in full.
Three posts on how databases physically store and recover data — pages, heap files, B-Tree vs LSM-Tree, and the Write-Ahead Log that guarantees nothing is ever lost.
Three posts on the SQL that separates mid-level from senior developers — window functions, CTEs, EXPLAIN plans, query optimization, and deliberate schema design trade-offs.
Results