Design documents with worked examples can be more maintainable than code for ML performance tools, since AI agents can reliably regenerate implementations from them, reducing the cost of keeping performance models up-to-date with new hardware and models.
SMART is a machine-learning performance modeling tool that replaces traditional code with natural-language design documents. AI agents regenerate the entire implementation from these docs on each update, eliminating tech debt while maintaining accuracy—validated against real systems like DeepSeek-V3 on TPUs.