docs: sync from coderbuzz/codex@b36584c

Author: github-actions[bot]

AI_KNOWLEDGE.md

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-<!-- docs: sync from coderbuzz/codex@7af404c -->
+<!-- docs: sync from coderbuzz/codex@b36584c -->
 
 # @coderbuzz/sql — AI Expert Knowledge Reference
 

README.md

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-<!-- docs: sync from coderbuzz/codex@7af404c -->
+<!-- docs: sync from coderbuzz/codex@b36584c -->
 
 # @coderbuzz/sql
 
@@ -65,6 +65,23 @@ This is not an ORM. There are no lazy-loaded relations, no magical `save()` meth
 - **Infer types** — `InferRow<S>`, `InferSelect<S, F>` for subset field selection
 - **Runtime agnostic** — Bun, Node.js, Deno
 
+## Benchmarks
+
+Full results at **[github.com/coderbuzz/benchmarks](https://github.com/coderbuzz/benchmarks)**.
+
+SQL query compilation throughput on Apple M-series, Bun runtime. Higher is better.
+
+| Scenario | @coderbuzz/sql | Kysely | Factor vs Kysely | Drizzle ORM | Factor vs Drizzle |
+|---|---|---|---|---|---|
+| SELECT simple | **1,700,391 ops/s** | 561,869 | **3.0x** | 34,239 | **49.7x** |
+| SELECT JOIN (2 tables) | **2,208,322 ops/s** | 310,690 | **7.1x** | 16,801 | **131.4x** |
+| INSERT single row | **2,954,261 ops/s** | 393,159 | **7.5x** | 55,085 | **53.6x** |
+| INSERT batch 100 rows | **134,187 ops/s** | 17,634 | **7.6x** | 914 | **146.8x** |
+| CTE (WITH clause) | **831,703 ops/s** | 224,893 | **3.7x** | 12,222 | **68.0x** |
+| 10 nested WHERE conditions | **656,309 ops/s** | 117,064 | **5.6x** | 12,692 | **51.7x** |
+
+`@coderbuzz/sql` is 3-7x faster than Kysely and 50-147x faster than Drizzle ORM across every query type. The gap widens with query complexity (batch, JOIN, conditions) due to `@coderbuzz/sql`'s zero-overhead string compilation strategy vs Kysely's AST-based approach and Drizzle's ORM abstraction layer.
+
 ---
 
 ## Installation
@@ -140,25 +157,6 @@ db.close();
 
 ---
 
-## Benchmarks
-
-Full results at **[github.com/coderbuzz/benchmarks](https://github.com/coderbuzz/benchmarks)**.
-
-SQL query compilation throughput on Apple M-series, Bun runtime. Higher is better.
-
-| Scenario | @coderbuzz/sql | Kysely | Factor vs Kysely | Drizzle ORM | Factor vs Drizzle |
-|---|---|---|---|---|---|
-| SELECT simple | **1,700,391 ops/s** | 561,869 | **3.0x** | 34,239 | **49.7x** |
-| SELECT JOIN (2 tables) | **2,208,322 ops/s** | 310,690 | **7.1x** | 16,801 | **131.4x** |
-| INSERT single row | **2,954,261 ops/s** | 393,159 | **7.5x** | 55,085 | **53.6x** |
-| INSERT batch 100 rows | **134,187 ops/s** | 17,634 | **7.6x** | 914 | **146.8x** |
-| CTE (WITH clause) | **831,703 ops/s** | 224,893 | **3.7x** | 12,222 | **68.0x** |
-| 10 nested WHERE conditions | **656,309 ops/s** | 117,064 | **5.6x** | 12,692 | **51.7x** |
-
-`@coderbuzz/sql` is 3-7x faster than Kysely and 50-147x faster than Drizzle ORM across every query type. The gap widens with query complexity (batch, JOIN, conditions) due to `@coderbuzz/sql`'s zero-overhead string compilation strategy vs Kysely's AST-based approach and Drizzle's ORM abstraction layer.
-
----
-
 ## Core Concepts
 
 | Concept | What it does |