A jargon-free introduction to data models and data modeling — what a data model actually is, how they’re typically represented (ER diagrams, relational schemas, JSON structures, dimensional models), and why deciding the shape of your data before writing the code that manipulates it is usually the cheapest work you’ll do all quarter.
Not a catalog of the Gang of Four patterns — an argument for why they’re foundational. Design patterns are a shared vocabulary that lets you read a codebase’s architectural intent from the names alone, and the value of that shared language transcends any specific programming language.
A jargon-free introduction to hexagonal architecture — the idea that your business logic should sit in the middle and the outside world (databases, screens, APIs, tests) should plug into it through simple, agreed-upon shapes. Small worked examples in Python, Go, and Rust show what changes when a new requirement arrives.