Cloudflare Cuts 100 TB from a DNS Cache — Week 35 Web Development

Traversy Media argues that AI has changed technical interviews without removing them. Citing CoderPad data, the video says assessments rose 48% globally since mid-2023 and 43% of companies still use classic algorithmic exercises; others have shifted toward system design, pair programming, and real-codebase debugging. OpenAI and Anthropic examples emphasize reasoning and fundamentals, while Meta reportedly tests candidates with AI in a harder collaborative round. The hiring signal is engineering judgment—explaining tradeoffs, detecting failure modes, and defending a solution—not raw typing speed or an ability to generate plausible code.

Stefan Mischook warns against over-preparing through tutorials, theory, speculative architecture, and optimization before a real constraint exists. His recommendation is to learn the fundamentals of one or two languages, reach a usable baseline, and then let a deployed project reveal the next necessary skill. A small web application can force decisions about structure, data, deployment, and debugging that passive courses never surface. Optimization should likewise follow measured user impact or infrastructure cost, not an attempt to squeeze out the last five percent from an unused system.

Casey Muratori challenges the common optimization loop of profiling, changing the hottest function, and accepting any local improvement. He starts from the operations a system must perform and the hardware’s theoretical capacity, then measures the unexplained gap between that ceiling and observed throughput. This avoids settling into a local minimum and makes every remaining cost demand an explanation. He also argues that reading a small set of assembly instructions is approachable and gives engineers a concrete model for memory and execution, especially when software may run tens of times below its potential.