Comparison
Canary deploymentvsShadow deployment
Canary deployment
the new prompt goes to two percent of traffic first, and you watch quality and cost before letting the rest through.
Rolling a prompt or model change to a small traffic slice first, watching quality and cost metrics, then widening. Treat prompts as deployable artefacts with the same ceremony as code, because they break things the same way.
Full entry →Shadow deployment
you run the candidate on live traffic without showing anyone its answers, and compare the logs afterwards.
Running a candidate (new model, new prompt) on live traffic without serving its output, logging results for offline comparison against the incumbent. The lowest-risk way to test a change against reality before it faces a user.
Full entry →