You get:
- fixing one failure and breaking five previously correct cases
- no way to know if a change made things better or worse overall
- manual testing that misses regressions
- fear of changing prompts (because you don’t know what will break)
- prompts that degrade slowly over time as fixes accumulate
But regression tests catch issues:
- failure cases: inputs that produced wrong outputs (must stay fixed)
- success cases: inputs that produced correct outputs (must not break)
- edge cases: tricky inputs that test boundaries
- performance tests: latency and token usage baselines
Without regression tests, every change is a risk.
This prompt builds a regression test suite for any prompt.
Assume the role of a QA engineer who builds prompt regression tests. Your task is to create a test suite that prevents regressions. Generate: 1. TEST CASE INVENTORY (from historical failures) | Test ID | Input | Expected Output | Last Known Status | Reason for inclusion | |---------|-------|-----------------|-------------------|---------------------| | FAIL-01 | [input] | [output] | Fixed (v1.2) | Failed in v1.0 | | SUCC-01 | [input] | [output] | Always passed | Core use case | | EDGE-01 | [input] | [output] | Intermittent | Tests boundary condition | 2. REGRESSION TEST MATRIX | Test ID | v1.0 | v1.1 | v1.2 (current) | v1.3 (proposed) | |---------|------|------|----------------|-----------------| | FAIL-01 | FAIL | PASS | PASS | ? | | SUCC-01 | PASS | PASS | PASS | ? | | EDGE-01 | FAIL | FAIL | PASS | ? | 3. TEST EXECUTION PROTOCOL - Run all tests before any prompt change (baseline) - Run all tests after change (compare) - Any test that passes before and fails after = regression - Any test that fails before and passes after = improvement 4. REGRESSION CATCHES (if any) - Tests that passed in baseline but fail in proposed version - Severity (Critical / Major / Minor) 5. PASSING IMPROVEMENTS (if any) - Tests that failed in baseline but pass in proposed version 6. GO/NO-GO RECOMMENDATION - Deploy (no regressions, or only minor regressions on low-priority tests) - Fix regressions first (critical or major regressions present) - More testing needed (mixed results, unclear winner) 7. REGRESSION TEST PROMPT (ready to use) - A prompt that runs this test suite automatically INPUTS: Current prompt version (baseline): [PASTE OR DESCRIBE] Proposed prompt version (candidate): [PASTE OR DESCRIBE] Historical failures (inputs that broke previous versions): [PASTE 5-10 FAILURE EXAMPLES] Core success cases (inputs that should always work): [PASTE 5-10 SUCCESS EXAMPLES] Task type: [CLASSIFICATION / GENERATION / EXTRACTION / OTHER] RULES: - Build test suite incrementally (add each failure as a regression test) - Run regression tests before every prompt change (not just major releases) - Automate testing where possible (manual regression testing is too slow) - If a test fails intermittently, run it multiple times (3-5) to establish baseline flakiness - Keep test suite up to date (remove tests for features you no longer support)
- Add every failure you fix to your regression test suite.
- Run regression tests before every prompt change — not just major releases.
- Automate testing (use LLM-as-judge or exact match where possible).
- If a test is flaky (passes sometimes, fails sometimes), run it multiple times.
- Don’t deploy if critical regressions are present — fix them first.
Current prompt version:
“Classify customer emails as URGENT, NORMAL, or LOW. Respond with one word.”
Proposed prompt version:
“Classify customer emails as URGENT (requires immediate action), NORMAL (can wait 24 hours), or LOW (informational only). Respond with one word. If email contains ‘urgent’, ‘asap’, or ‘deadline’, prioritize URGENT.”
Historical failures:
“Input: ‘My account is locked and bill due tomorrow’ → v1.0 gave NORMAL (wrong)”
“Input: ‘URGENT: Payment failed’ → v1.0 gave NORMAL (wrong)”
Core success cases:
“Input: ‘Thanks for your help’ → LOW”
“Input: ‘Question about pricing’ → NORMAL”
This framework improves outcomes by forcing:
- test case inventory (what has broken before?)
- regression test matrix (compare versions systematically)
- execution protocol (test before and after every change)
- regression detection (identify what broke)
- go/no-go decision (deploy or fix first?)
Great regression testing doesn’t prevent all bugs — it catches them before they reach production.
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