DSPy From First Principles 17: From Experiment to Production

Fri, 28 Aug 2026 11:20:00 +0100

From Experiment to Production

Chapter 16 gave us a candidate that can be evaluated without obvious leakage.

That still does not mean:

optimizer.compile(...)
        ↓
production

The lifecycle is closer to:

1. Offline win is insufficient

A candidate may beat an aggregate metric and still be unacceptable:

2. CoCoder’s promotion boundary

CoCoder stores separate records:

ProgramEvaluationCaseResultDTO
ProgramEvaluationDTO
ProgramComparisonDTO
ProgramPromotionDTO

The docs summarize the invariant:

optimizer proposes
CoCoder evaluates
CoCoder compares
operator/system policy promotes

Promotion requires a persisted comparison, a promote recommendation unless there is an explicit override, the comparison baseline still being the single active version, the target still being a candidate, and optimizer lineage—when present—matching that active baseline.

Deployment on Programmer.ie

DSPy From First Principles 17: From Experiment to Production

From Experiment to Production

1. Offline win is insufficient

2. CoCoder’s promotion boundary