Update README.md

README.md

@@ -70,7 +70,7 @@ Modern models grow by accretion and inertia. We refactor them into **crystalline
    - Everything relationally aware in this system has a barrage of analytics that were not only forged through thousands of experiments to GUARANTEE they are not garbage noise, but to be directly useful signals to be read and understood by humans and AI alike.
    - Each structural system has it's own series of important statistics and relationally understood analytics directly related to the geometry.
    - With each structural system comes structural bounds that do not exist, often snapping even ONE of these geometric limiters off causes cascade corruption so the experimental results must be respected.
-   - With that I encourage DIRECT experimental testing of this hypothesis, finding better avenues, sharing those avenues through each of the world's systems, and encouraging dewvelopmental growth to all in the process.
+   - With that I encourage DIRECT experimental testing of this hypothesis, finding better avenues, sharing those avenues through each of the world's systems, and encouraging developmental growth to all in the process.
 ---
 
 ## Why This Matters
@@ -79,6 +79,7 @@ Modern models grow by accretion and inertia. We refactor them into **crystalline
 - **Disposable training**: spawn a small block, test, retire—no need to rebuild the world.  
 - **Continuity**: geometry, tokens, volumes, and expansions persist in the **Register**.  
 - **Reproducibility**: simple formulas, fewer knobs, manifest-driven runs.
+- **Analysis**: data processing must be UNDERSTOOD, not guessworked or stuck together into huge heaps hoping things align.
 
 Outcome: more hypotheses per GPU-hour—and a path to disciplined studies of introspection, rationalization, and other sentience-adjacent capabilities.