*WPE/TME* - A geometric calculus language for structural and temporal reasoning. Think: mathematical notation for encoding semantic relationships. Four parameters (domain, shell, phase, curvature) let you explicitly represent how components couple, influence each other hierarchically, and evolve over time.

*Crystalline* - A code synthesis language that generates provably optimal code through physics-guided evolution. Not template filling. It discovers novel optimizations (async I/O, streaming, parallelization, loop fusion) through energy minimization, achieving 3-4× performance improvement.

Both languages share the same geometric foundation from superconductor physics but serve completely different purposes. WPE/TME is for semantic reasoning (great for LLM scaffolding). Crystalline is for generating high-performance code.

Key differences from existing approaches: - Deterministic (same input always produces same output) - Explainable (energy equations show WHY decisions were made) - Novel code generation (genuinely discovers optimizations) - Mathematical guarantees on performance

Crystalline has a Python implementation. WPE/TME has a Python reference implementation, but it's really a notation system (like how LaTeX is a language for typesetting math).

GitHub: [will add link on launch day] Papers: [will add ResearchGate links - 3 papers explaining theory]

I'd love feedback on: 1. The language design - does geometric encoding make sense? 2. For Crystalline: what benchmarks would convince you the synthesis works? 3. For WPE/TME: would explicit structure help your AI reasoning tasks?

Happy to answer questions about the physics, the languages, or the implementations!