feat: Implement Study Interview Mode as default study creation method

Study Interview Mode is now the DEFAULT for all study creation requests.
This intelligent Q&A system guides users through optimization setup with:

- 7-phase interview flow: introspection → objectives → constraints → design_variables → validation → review → complete
- Material-aware validation with 12 materials and fuzzy name matching
- Anti-pattern detection for 12 common mistakes (mass-no-constraint, stress-over-yield, etc.)
- Auto extractor mapping E1-E24 based on goal keywords
- State persistence with JSON serialization and backup rotation
- StudyBlueprint generation with full validation

Triggers: "create a study", "new study", "optimize this", any study creation intent
Skip with: "skip interview", "quick setup", "manual config"

Components:
- StudyInterviewEngine: Main orchestrator
- QuestionEngine: Conditional logic evaluation
- EngineeringValidator: MaterialsDatabase + AntiPatternDetector
- InterviewPresenter: Markdown formatting for Claude
- StudyBlueprint: Validated configuration output
- InterviewState: Persistent state management

All 129 tests passing.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

knowledge_base/lac/session_insights/success_pattern.jsonl

@@ -7,3 +7,5 @@
 {"timestamp": "2025-12-28T12:28:04.706624", "category": "success_pattern", "context": "Implemented L-BFGS gradient optimizer for surrogate polish phase", "insight": "L-BFGS on trained MLP surrogates provides 100-1000x faster convergence than derivative-free methods (TPE, CMA-ES) for local refinement. Key: use multi-start from top FEA candidates, not random initialization. Integration: GradientOptimizer class in optimization_engine/gradient_optimizer.py.", "confidence": 0.9, "tags": ["optimization", "lbfgs", "surrogate", "gradient", "polish"]}
 {"timestamp": "2025-12-29T09:30:00", "category": "success_pattern", "context": "V6 pure TPE outperformed V5 surrogate+L-BFGS by 22%", "insight": "SIMPLE BEATS COMPLEX: V6 Pure TPE achieved WS=225.41 vs V5's WS=290.18 (22.3% better). Key insight: surrogates fail when gradient methods descend to OOD regions. Fix: EnsembleSurrogate with (1) N=5 MLPs for disagreement-based uncertainty, (2) OODDetector with KNN+z-score, (3) acquisition_score balancing exploitation+exploration, (4) trust-region L-BFGS that stays in training distribution. Never trust point predictions - always require uncertainty bounds. Protocol: SYS_16_SELF_AWARE_TURBO.md. Code: optimization_engine/surrogates/ensemble_surrogate.py", "confidence": 1.0, "tags": ["ensemble", "uncertainty", "ood", "surrogate", "v6", "tpe", "self-aware"]}
 {"timestamp": "2025-12-29T09:47:47.612485", "category": "success_pattern", "context": "Disk space optimization for FEA studies", "insight": "Per-trial FEA files are ~150MB but only OP2+JSON (~70MB) are essential. PRT/FEM/SIM/DAT are copies of master files and can be deleted after study completion. Archive to dalidou server for long-term storage.", "confidence": 0.95, "tags": ["disk_optimization", "archival", "study_management", "dalidou"], "related_files": ["optimization_engine/utils/study_archiver.py", "docs/protocols/operations/OP_07_DISK_OPTIMIZATION.md"]}
+{"timestamp": "2026-01-02T14:30:00", "category": "success_pattern", "context": "Study Interview Mode implementation and routing update", "insight": "STUDY CREATION DEFAULT: Interview Mode is now the DEFAULT for all study creation requests. Triggers: create a study, new study, set up study, optimize this, minimize mass - any study creation intent. Benefits: (1) Material-aware validation checks stress vs yield, (2) Anti-pattern detection warns about mass-no-constraint, (3) Auto extractor mapping E1-E10, (4) State persistence for interrupted sessions, (5) Blueprint generation with full validation. Skip with: skip interview, quick setup, manual config. Implementation: optimization_engine/interview/ with StudyInterviewEngine, QuestionEngine, EngineeringValidator, StudyBlueprint. All 129 tests passing.", "confidence": 1.0, "tags": ["interview_mode", "study_creation", "default", "validation", "anti_pattern", "materials"], "related_files": [".claude/skills/modules/study-interview-mode.md", "docs/protocols/operations/OP_01_CREATE_STUDY.md", "optimization_engine/interview/study_interview.py"]}
+{"timestamp": "2026-01-02T14:45:00", "category": "success_pattern", "context": "Study Interview Mode implementation complete", "insight": "INTERVIEW MODE DEFAULT: Study creation now uses Interview Mode by default for all study creation requests. This is a major usability improvement. Triggers: create a study, new study, set up, optimize this - any study creation intent. Key features: (1) Material-aware validation with 12 materials and fuzzy name matching, (2) Anti-pattern detection for 12 common mistakes, (3) Auto extractor mapping E1-E24, (4) 7-phase interview flow, (5) State persistence for interrupted sessions, (6) Blueprint validation before generation. Skip with: skip interview, quick setup, manual. Implementation in optimization_engine/interview/ with 129 tests passing. Full documentation in: .claude/skills/modules/study-interview-mode.md, docs/protocols/operations/OP_01_CREATE_STUDY.md", "confidence": 1.0, "tags": ["interview_mode", "study_creation", "default", "usability", "materials", "anti_pattern", "validation"], "related_files": [".claude/skills/modules/study-interview-mode.md", "docs/protocols/operations/OP_01_CREATE_STUDY.md", "optimization_engine/interview/"]}