The four axes of type systems explained precisely, with real examples of what each combination means in practice and why the distinctions matter for everyday programming.
What technical debt actually is, how to distinguish debt worth paying from debt worth ignoring, and how to make the case for cleanup work to a non-technical stakeholder.
Why every public API needs rate limiting, the common algorithms and their tradeoffs, and how to implement it without reinventing the wheel.
Why N+1 queries are so common in ORM-based code, how to detect them, and the three patterns that eliminate them without rewriting your data layer.
The mental model shifts that make TypeScript click, which features earn their complexity, and how to use the type system to catch real bugs rather than add ceremony.
What each type of test double actually is, when to use each one, and how to avoid the trap of over-mocking tests into uselessness.
The practical techniques that actually improve LLM output quality - structured prompts, few-shot examples, chain-of-thought, and how to build reliable AI-powered features.
How to read a Postgres EXPLAIN ANALYZE output, what sequential scans and index scans mean, and how to identify and fix slow queries before they become incidents.
How WebSockets work, what they are actually good for, and the patterns for building real-time features without the common pitfalls.
Why secrets in code and environment variables are a problem, what proper secrets management looks like, and how to move from hardcoded credentials to a secure setup.
What offline-first actually means, how local-first data sync works, and the specific patterns that make mobile apps resilient to unreliable connectivity.
Core Web Vitals explained, how browsers load pages, and the specific changes that actually improve perceived performance for real users.
