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Integrate Vellum and ZenML for MLOps

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: AI Fluency Index Evaluator with LangGraph and OpenAI o4-mini

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Linked challenge
AI Fluency Index Evaluator with LangGraph and OpenAI o4-mini

Prompt source

Original prompt text with formatting preserved for inspection.

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Describe how Vellum could be integrated to monitor the `BehaviorAnalyst`'s accuracy in identifying fluency behaviors and the `FluencyCoach`'s effectiveness. Outline a ZenML pipeline that automates the deployment of updated agent logic (e.g., fine-tuned Llama 4 Maverick models) based on performance metrics tracked in Vellum.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Preserve the rubric, target behavior, and pass-fail criteria as the baseline for evaluation.

Tune next

Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.

Verify after

Make sure the prompt catches regressions instead of just mirroring the happy-path examples.