April 2026: Delivered safety and reliability improvements for fused MoE autotuning in flashinfer, focused on reducing runtime errors, improving throughput, and increasing observability. Implemented occupancy-based pre-filtering to exclude zero-occupancy tactics on SM120 Blackwell, added thread-safety protections around tactic selection, and enhanced logging and error reporting in the get_occ path. Fixed a critical class of runtime shared memory failures and safeguarded against empty-tactics edge cases. Validated FP8 MoE autotuning on SM120 Blackwell and SM90, with no regression on dense NVFP4 models. Business impact: lowers autotuning waste, prevents production crashes, and sustains MoE throughput across devices. Technologies: C++, multithreading (mutex), Python bindings, occupancy pre-validation, robust logging, end-to-end autotuner workflow.