docs: consolidate and archive redundant documentation

- Archived 13 API design iterations to docs/api-design-archive/
- Consolidated augmentation docs to docs/augmentations-archive/
- Maintained ONE definitive API doc at docs/api/README.md
- Cleaned up documentation structure for 2.0 release
- Preserved all historical documents for reference

docs/architecture/noun-verb-taxonomy.md

@@ -462,7 +462,7 @@ for (const order of orders) {
 // Similar to graph databases but with added benefits:
 // 1. Automatic vector embeddings for similarity
 // 2. Natural language querying
-// 3. Unified with field filtering
+// 3. Unified with metadata filtering
 
 // Enhanced graph queries
 const results = await brain.find("similar users who purchased similar products")

docs/architecture/overview.md

@@ -1,6 +1,6 @@
 # Architecture Overview
 
-Brainy is a multi-dimensional AI database that combines vector similarity, graph relationships, and field filtering into a unified query system. This document provides a comprehensive overview of the system architecture.
+Brainy is a multi-dimensional AI database that combines vector similarity, graph relationships, and metadata filtering into a unified query system. This document provides a comprehensive overview of the system architecture.
 
 ## Core Components
 
@@ -23,7 +23,7 @@ Brainy's revolutionary feature that unifies three types of search:
 const results = await brain.find({
   like: "machine learning papers",              // Vector similarity
   connected: { to: "research-team", depth: 2 }, // Graph traversal  
-  where: { published: { $gte: "2024-01-01" } }  // Field filtering
+  where: { published: { $gte: "2024-01-01" } }  // Metadata filtering
 })
 ```
 

docs/architecture/triple-intelligence.md

@@ -1,10 +1,10 @@
 # Triple Intelligence System
 
-The Triple Intelligence System is Brainy's revolutionary query engine that unifies vector similarity, graph relationships, and field filtering into a single, optimized query interface.
+The Triple Intelligence System is Brainy's revolutionary query engine that unifies vector similarity, graph relationships, and metadata filtering into a single, optimized query interface.
 
 ## Overview
 
-Traditional databases force you to choose between vector search, graph traversal, OR field filtering. Brainy combines all three intelligences into one magical API that automatically optimizes execution for maximum performance.
+Traditional databases force you to choose between vector search, graph traversal, OR metadata filtering. Brainy combines all three intelligences into one magical API that automatically optimizes execution for maximum performance.
 
 ## Query Interface
 
@@ -116,7 +116,7 @@ const results = await brain.find({
   like: "recent posts",            // Applied to filtered set
   limit: 5
 })
-// Field filter first, then vector search on results
+// Metadata filter first, then vector search on results
 ```
 
 ## Fusion Ranking
@@ -193,7 +193,7 @@ Brainy uses itself to optimize queries:
 
 Triple Intelligence leverages all available indexes:
 - **HNSW Index**: For vector similarity
-- **Metadata Index**: For field filtering
+- **Metadata Index**: For metadata filtering
 - **Graph Index**: For relationship traversal
 
 ## Advanced Features