Benchmarks measure model or system capability, but their results are only as meaningful as their design — a recurring problem across LLM, multi-agent, and vision tasks, where tests built for one context are routinely applied to contexts they cannot capture.

Distributed systems problems — coordination, state management, failure recovery, and observability — recur across cloud infrastructure, durable execution, multi-agent AI, and formal verification research.

Engineering craft is the accumulated discipline of writing, organizing, and maintaining software well — spanning code design, tooling fluency, communication, and the judgment to know when technical excellence actually changes outcomes.

The engineering decisions that determine how software behaves under real load, covering durability, observability, testing discipline, performance constraints, and the operational costs of failure.

Software engineering spans craft, process, and judgment — how code is structured, tested, reviewed, deployed, and maintained — and the sources collected here collectively interrogate each layer as AI tooling reshapes who does what and why.