Overhaul model system with multi-stage training, variants, benchmarks, and eval

Replace the single-stage training + flat capability score with a realistic AI
development pipeline: pre-training with Chinchilla scaling laws, SFT with
specializations, alignment with safety/capability tradeoffs (RLHF/DPO/Constitutional),
model families with distillation/fine-tuning/quantization variants, named benchmark
suite with compute-costing eval jobs, and segment-specific market quality.

Phases 1-6 of the model rework plan: new types, engine rewrite, save migration,
training events/risk system, concurrent training, variant creation, benchmark
evaluation with leaderboard, and market integration.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

packages/game-engine/src/data/achievements.ts

@@ -13,7 +13,7 @@ export const ACHIEVEMENT_DEFINITIONS: AchievementDefinition[] = [
     name: 'Hello World',
     description: 'Train your first AI model.',
     icon: 'Brain',
-    condition: { field: 'models.trainedModels.length', operator: 'gte', value: 1 },
+    condition: { field: 'models.baseModels.length', operator: 'gte', value: 1 },
   },
   {
     id: 'first-deploy',