Agent Evaluation & Prompt Management

Automated Evaluation & Quality Gates

Every new version of an agent runs through an automated evaluation harness before it reaches production. Responses are scored against a golden dataset across accuracy, faithfulness, and task-completion metrics. Releases that fall below configurable thresholds are blocked automatically — keeping regressions out of your production environment.

Continuous Production Monitoring

Once live, every agent response against real customer traffic is monitored in real time. The monitoring framework is fully configurable — define any metric that matters for your use case and set your own thresholds for alerting. Examples include:

+ any custom metric — tone, safety, hallucination rate, tool-call success rate, and more.

User Feedback Collection

Automated metrics tell you how an agent is performing — but the users experiencing those responses tell you why. This accelerator provides built-in mechanisms to collect thumbs-up/down ratings, free-text corrections, and structured feedback directly alongside agent responses. This signal feeds back into evaluation and retraining pipelines automatically.

Golden Dataset Guidelines

The quality of your evaluation is only as good as the data you evaluate against. This accelerator includes opinionated guidelines and tooling for building a golden dataset that is:

• Representative — covers the full distribution of real user inputs, including edge cases.
• Labelled — each input has a verified expected output or rubric for scoring.
• Versioned — evolves alongside the agent so evaluations remain meaningful over time.
• Augmented — seeded with adversarial and synthetic examples to stress-test failure modes.

Prompt Management

Prompts are too important to be buried in code. This accelerator externalizes all prompts into a managed store, keeping them out of your codebase and making them editable without a deployment. Every change is versioned, so you can track what changed, roll back instantly, and compare how prompt variations affect agent behaviour over time.