The AI Testing Playbook, developed by Forte Group's Quality Engineering Practice, provides a practical framework for building quality into LLM-enabled products — from defining what "good" looks like to continuously evaluating performance in production.
Designed for engineering and QA leaders already shipping or preparing to ship AI-enabled features, the playbook shows how to move beyond subjective, "looks good" testing and build a repeatable AI quality program.
In this whitepaper, you will learn:
- How to test non-deterministic AI systems when the same input doesn't always produce the same output.
- The six phases of the AI-enabled feature lifecycle, from feature definition and prompt design through production monitoring.
- How to build an effective evaluation set covering representative, edge, adversarial, and refusal scenarios.
- How to establish pre-production quality gates and make AI evaluation part of your CI/CD process.
- How to monitor AI quality in production using observability and continuous evaluation.
- How to close the quality loop by turning real production failures into new regression tests.
