- Parses intent keywords (group, order, take) → selects optimal algorithm (heap vs sort, BFS vs Dijkstra, Kadane)
- Three execution backends: interpreted Python, Numba JIT, native C++ with LLVM
- Automatic backend selection based on problem size with property-based testing
- 115 test cases verify every optimization against naive baseline for correctness guarantees
3Backends
115Tests
5xSpeedup
VerifiedCorrect
Engineering note
The innovation isn't one clever optimization - it's a repeatable framework for algorithmic selection. TOP_K selection happens at parse time (syntax-driven). BFS vs Dijkstra happens at runtime (graph structure inspection). Kadane detection happens from objective analysis (maximize + contiguous). Three structurally different decisions across three algorithm families, all automatically verified. It's proof that intent-level programming can outperform hand-coded solutions while guaranteeing correctness.