What problem does it solve? Engineering teams upgrading to Codex-flow v3 need to verify that aggressive performance targets (2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvement, 50-75% memory reduction) are actually met, and to detect regressions before they reach production. ## Core Features & Use Cases - Comprehensive Benchmark Suites: TypeScript benchmark classes for startup time, vector search, memory usage, swarm coordination, Flash Attention, and SONA adaptation latency. - Target Validation Gates: A PerformanceGates framework that validates every v3 target in parallel and reports an overall achievement score. - Continuous Regression Detection: Automated comparison of current benchmark runs against stored baselines with severity classification and fix recommendations. - Use Case: Before shipping a v3 release, run the full benchmark suite to confirm HNSW search hits the 150x improvement floor and memory reduction stays within the 50-75% band, then wire the monitor into CI for ongoing regression alerts. ## Quick Start Ask the AI to establish a v2 performance baseline and then validate the Flash Attention, search, and memory optimization targets using the v3-performance-engineer agent.
