From Mode Collapse to Context Engineering: How We Build Reliable AI Systems (2026)
Two fundamental challenges define LLM development in 2026: Mode Collapse reduces output diversity through alignment training, while Context Rot degrades model performance as context windows grow. This article analyzes both phenomena and presents practical solutions like Verbalized Sampling and systematic Context Engineering.