P.01Data engineers build the pipelines, warehouses, and transformation layers. They aren't data scientists, backend developers, or analysts. How to hire for it.
P.02Go runs Kubernetes, Docker, Prometheus, and most cloud tooling. What the language attracts, what it demands, and how to screen for the right profile.
P.03TypeScript is the default now, so the market is full of people who write it without understanding it. The questions that tell the two groups apart.
P.04Full-stack means something different to every team. How to define what you need, catch specialists in disguise, and know when a generalist is the right call.
P.05Node.js has split into async-first, TypeScript-native, and edge-runtime camps. The screen that finds someone who builds production backends, not tutorials.
P.06LLM bills grow faster than usage. Prompt caching, semantic dedup, tiered routing, and batch inference cut 40-80% without degrading output quality.
P.07Choosing the wrong contract structure reliably damages a client relationship. A practical guide to SoW, T&M, and the hybrid models that actually work.
P.08The DevOps engineer title now covers three jobs: platform engineer, SRE, and CI/CD specialist. What each does, what to screen for, and what the market pays.
P.09iOS changed more in three years than the previous seven. What strong candidates actually know, how to screen for it, and what to expect on rates.
P.10Svelte 5's runes replaced magic variable tracking with explicit reactive primitives. A year into production: what changed, what improved, what surprised.
P.11LeetCode interviews are popular and mostly useless for predicting on-the-job performance. What the research says works, and how to build that process.
P.12Three tools, three bets on where complexity belongs. How to choose between BullMQ, Inngest, and Temporal based on what your system needs, not what sounds big.