Prompt Optimization — AI Improved Code Correctness Gate

Context

User feedback: "The AI improved code comes back wrong when run on Programmers."

Regression where optimizedCode generated by the ai-analysis service is judged incorrect by the scoring platform.

8 Diagnosed Defects (P0~P3)

Infrastructure Investigation Result (Separate — Outside Scope)

No problemTitle/problemDescription columns in Submission entity + not included in saga publisher payload → ai-analysis worker always called with empty strings. Structural defect where problem context itself is not delivered to LLM. This sprint only strengthens prompt-side guards; infrastructure fix carried to Sprint 143+ seed.

Decisions

Scope: Wave A+B (Option b — Standard Volume)

• Wave A (P0): SYSTEM_PROMPT/SQL_SYSTEM_PROMPT absolute behavioral equivalence rules + _build_platform_context instruction strengthening
• Wave B (P1): Add JSON schema optimizedCodeMeta + claude_client self-verification fallback
• Wave C (P2): Carried to Sprint 143+ — weight rebalancing risks score distribution regression + loss of comparison baseline with existing data

Rationale: Wave A only (P0) is undetectable if LLM ignores it. Self-verification field (P1) violation detection + safe fallback guarantees ROI. Decided after confirming 0 frontend compatibility changes.

Wave A — Behavioral Equivalence Absolute Rules

Added [Top Priority Rules] section before SYSTEM_PROMPT/SQL_SYSTEM_PROMPT response rules:

• Absolute prohibition on changing function signature / input-output format / result column names and order
• Permitted changes are internal implementation only
• Explicitly states scoring failure on violation + "if unsure, return original" safety net

_build_platform_context instruction strengthening:

• PROGRAMMERS: Function signature preservation instruction (SQL branch added in Sprint 142 R3)
• BOJ: Standard I/O format preservation instruction (Python API hardcoding removed in Sprint 142 R1 → language-neutralized)

Wave B — Self-Verification Metadata + Safe Fallback

JSON schema optimizedCodeMeta added:

{
  "signaturePreserved": true/false,  // not included for SQL
  "behaviorEquivalent": true/false,
  "changes": ["summary of changes"]
}

In claude_client._parse_response:

1. _is_explicit_false helper for strict boolean verification (Sprint 142 R1 P2 fix)
2. Only explicit false or "false" string triggers fallback
3. On fallback: optimized_code = None + parsed["optimizedCode"] = None applied simultaneously (Sprint 142 R2 P1 fix — frontend parseFeedback prioritizes optimizedCode in feedback JSON, so both must be cleared)

Score ↔ Self-Verification Separation Policy (Sprint 142 R4 P1 fix)

correctness rubric:

• ❌ "Evaluate both submitted code and optimizedCode" (draft — causes user score penalty if LLM suggests incorrect improved code)
• ✅ "Evaluate submitted code only, optimizedCode handled separately by self-verification meta"

Core principle: Separation of responsibilities between scoring (evaluating user code) and verification (LLM self-verification meta). Guarantees users are not penalized for LLM mistakes.

SQL Signature Gate Removal (Sprint 142 R4 P2 fix)

SQL has no concept of signature → Remove signaturePreserved from optimizedCodeMeta schema in SQL_SYSTEM_PROMPT. _is_explicit_false(None)=False so missing values auto-pass → only behaviorEquivalent is effectively verified.

PROGRAMMERS + SQL Branch (Sprint 142 R3 P2 fix)

AddProblemModal supports PROGRAMMERS + sql combination (real use case). _build_platform_context(source_platform, language) signature change:

• PROGRAMMERS + sql → result column name/order/sort preservation rules
• PROGRAMMERS + other → function signature preservation rules
• BOJ → SQL not supported, single message

Patterns (Reusable)

Critic Multiple Round Repeated Verification Pattern

Total 5 rounds · P0 0 · P1 2 · P2 4 all resolved.

Observation: Defect patterns difficult to catch with single-round verification (e.g., feedback JSON serialization and frontend exposure, SQL/algorithm branch conflicts, score stability regressions) are discovered through repeated rounds. Value of repeated verification.

LLM Self-Verification Metadata Pattern

When LLM output reliability cannot be enforced from code:

1. Add self-verification fields to JSON schema (boolean + change summary)
2. Code triggers fallback only on explicit false (blocks string boolean bypass)
3. Missing/None/type mismatch does not trigger fallback (backward compatible)
4. Rejected outputs removed from all serialization paths

Score ↔ Self-Verification Separation Principle

In LLM output scoring systems:

• Score: Evaluates user artifacts only
• Self-verification: Verifies reliability of LLM's own output
• Combining both responsibilities in one field transfers LLM mistakes to user penalties

Verification Results

• CI: Quality/Test AI Analysis/E2E/Coverage Gate all pass (5 PR pushes all GREEN)
• 36 new tests added (test_prompt 18 + test_claude_client 18)
• 100% backward compatible with existing tests (0 regressions)
• Critic 5 rounds P0/P1/P2 all resolved
• Branch discipline ✅: new branch + PR + Squash merge — 8 consecutive sprints compliant