Philosophy

matten optimizes for time to a runnable PoC, not benchmark leadership.

• One primary type. You work through Tensor; no generic dtype parameters and no visible lifetimes in ordinary code.
• Predictable, readable failures. Convenience APIs panic with actionable messages; boundaries return Result.
• Start now, optimize later. When a prototype becomes performance-critical, hand matten’s flat data to a specialized crate such as ndarray, nalgebra, or candle.

matten is intentionally not a full dataframe engine, an ML framework, or a GPU/sparse/distributed array library.