🎯 See ProofMap In 5 Minutes

Follow the full journey from objective to resolved prompt package — the core story of qualifying a challenger runtime against your baseline. No sign-up needed.

1

Define What "Good" Means

Create an objective with clear success criteria, guardrails, and a target runtime matrix. Know exactly what your prompt must achieve before you test it — no vague "it looks fine" judgments.

  • Success criteria bound to specific outcomes
  • Guardrails that block unsafe or incorrect responses
  • Target runtimes mapped to your production models
ActiveObjective
Code Review Agent
Success Criteria8 criteria
Guardrails3 guardrails
Target Runtimes2 runtimes
Target Runtimes
Production GPT-4oOpenAI / gpt-4oBaseline
Candidate Claude 3.5Anthropic / claude-3-5-sonnetChallenger
2

Set Baseline & Challenger Runtimes

Your baseline is the runtime currently in production. The challenger is the new model you want to qualify — maybe it's cheaper, faster, or newer. ProofMap compares them side-by-side against the same test suite.

  • Baseline: your current production model (truth source)
  • Challenger: the model you're evaluating for promotion
  • Same prompt, same criteria, two runtimes — evidence-driven comparison
3

Run Evaluation With Evidence

ProofMap runs deterministic and evaluator-assisted tests against both runtimes in parallel. Every criterion is scored — you get structured pass/fail evidence, not guesswork or cherry-picked demos.

  • Deterministic checks for exact-match criteria
  • Evaluator-assisted scoring for qualitative criteria
  • Per-criterion pass/fail with linked evidence
  • Side-by-side comparison: baseline vs challenger
PassedEvaluation Result
GuardrailsAll passed
Smoke Suite8/8 passed
Full Matrix12/14 passed
🕐
Cost Delta−34% vs baseline
🛡️ ActiveResolved Prompt Package
Code Review Agent
Runtime:Production GPT-4oBaseline
Mapping Source Path
Target-specificActiveWinning
Cohort-levelCandidate
Shared defaultNo mapping
4

Resolve With Confidence

The resolved prompt package is the "wow moment." For any objective and target runtime, ProofMap tells you exactly which prompt to use — backed by qualification proof, transparent mapping hierarchy, and full evaluation evidence.

  • Shows the winning prompt revision and its qualification status
  • Transparent mapping hierarchy: target-specific → cohort → default
  • Copy or export the resolved package for deployment
  • Includes fallback mappings for partially qualified runtimes

What Makes ProofMap Different

Decision PointManual EvaluationProofMap
Compare baseline to challengerManually run both models, track results in a spreadsheet, guess at significance.Automated runs compare every criterion in parallel. Evidence links back to run reports.
Decide whether to switchDebate in Slack or a meeting. No shared evidence.Clear recommendation: Switch / Stay / Fallback — backed by pass-rate data and cost delta.
Create fallback mappingManually route tasks to different models. No audit trail.System creates a target-specific fallback mapping for partial qualification.
Retrieve the right promptHope the same prompt works across models.Resolved prompt package: the approved mapping per target, backed by evidence.

Ready to qualify your own prompts?

Create a free account, define your first objective, and run a baseline-versus-challenger evaluation in under 15 minutes.

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