A new learning-oriented workflow guides developers through analyzing open-weight model releases. It prioritizes structural decomposition over superficial benchmarks. By focusing on specific architectural choices, practitioners can better replicate or optimize LLM performance. This incremental guide provides a systematic approach for those studying model internals without relying on corporate whitepapers.