Context decay, orchestration drift, and the rise of silent failures in AI systems
- Apr 28
- 1 min read
VENTURE BEAT — We have spent the last two years getting very good at evaluating models: benchmarks, accuracy scores, red-team exercises, retrieval quality tests. But in production, the model is rarely where the system breaks.
It breaks in the infrastructure layer, the data pipelines feeding it, the orchestration logic wrapping it, the retrieval systems grounding it, the downstream workflows trusting its output. That layer is still being monitored with tools designed for a different kind of software.
Read the full story | VENTURE BEAT
