perf(ai-moderation): speed up analysis queue (ramai + sepi)

- Parallelize per-user reputation/profile fetches in textBatchProcessor
  (was a serial ~2N DB/Redis round-trip loop per sub-batch; now Promise.all
  over unique users). Cuts per-batch latency, biggest win on small/quiet
  batches.
- Make the LLM concurrency semaphore dynamic (cached per config value) instead
  of frozen at import time, so AI_LLM_MAX_CONCURRENT is tunable without code
  change and reflects current config.
- Bump AI_LLM_MAX_CONCURRENT default 5 -> 8 (gemini-flash-lite is cheap; helps
  throughput when busy).
- Lower AI_ANALYSIS_DEBOUNCE_MS 500 -> 250 (snappier first-message analysis
  when quiet).
- Lower AI_ANALYSIS_RECOVERY_INTERVAL_MS 15000 -> 10000 (stuck/errored
  messages re-analyze sooner).

tsc, biome, vitest (129) all clean.

services/discord-gateway/src/shared/config/index.ts

@@ -177,7 +177,7 @@ export const configSchema = z
     QDRANT_URL: z.string().optional(),
     QDRANT_COLLECTION: z.string().default("gmw_text_moderation"),
     QDRANT_API_KEY: z.string().optional(),
-    AI_LLM_MAX_CONCURRENT: z.coerce.number().int().positive().default(5),
+    AI_LLM_MAX_CONCURRENT: z.coerce.number().int().positive().default(8),
     AI_LLM_IMAGE_MAX_DIMENSION: z.coerce
       .number()
       .int()
@@ -226,11 +226,11 @@ export const configSchema = z
       .default(5),
 
     // ── AI Analysis Timing ──────────────────────────────────────────────
-    AI_ANALYSIS_DEBOUNCE_MS: z.coerce.number().positive().default(500),
+    AI_ANALYSIS_DEBOUNCE_MS: z.coerce.number().positive().default(250),
     AI_ANALYSIS_RECOVERY_INTERVAL_MS: z.coerce
       .number()
       .positive()
-      .default(15000),
+      .default(10000),
     AI_ANALYSIS_ERROR_COOLDOWN_MS: z.coerce.number().positive().default(30000),
 
     // ── AI Analysis Batch ───────────────────────────────────────────────