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This guide focuses on Eval for Fine-Tunes for production systems, with practical trade-offs for reliability, security, and cost.
Offline loss is necessary; insufficient. Blind A/B on real developer tickets tells you if cycle time or defect rate moved. If not, keep the teacher. Day 49 pre-registers metrics and blinding.
⚡ TL;DR: Sample real tickets; two arms behind the router; raters blinded; primary metric time-to-merge or escaped defects. Either offline general-pack or online A/B can veto.
python
experiment = {
"n_tickets": 120,
"arms": ["teacher", "student_v3"],
"blinding": True,
"primary": "time_to_merge_hours",
"secondary": ["ci_fail_rate", "revert_rate", "rater_preference"],
"min_detectable_effect_hours": 0.5,
}
text
Router assigns arm server-side; UI chrome identical. Break blind only after metrics lock. Ship only if primary beats MDE, general pack within budget (Day 45), and license scan clean (Day 48).
❌ Ship because BLEU vs teacher improved
Eval for Fine-Tunes: production guidance
- [ ] Pre-registered metrics
- [ ] Sample size / MDE documented
- [ ] Blinding procedure
- [ ] Stop/rollback criteria
- [ ] Results archived with model hashes
- [ ] Decision recorded even when “no ship”
Series navigation
← Day 48 · Day 50 → Last updated September 11, 2026 Related: Evaluating AI Coding Tools: Blind A/B Tests on Real Tickets; Day 41: When Fine-Tunes Beat Prompting; SageMaker JumpStart vs Bedrock: When Fine-Tunes Beat Prompting.Watch: 100 Days of AI on YouTube
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