Google Launches Stax to Simplify AI Testing

Google has introduced Stax, a new developer tool designed to take the guesswork out of testing large language models (LLMs). The platform combines the research strength of DeepMind with the practical innovation of Google Labs, aiming to move beyond the subjective “vibe testing” approach that many developers currently rely on.

Traditional software testing is straightforward, but AI models produce non-deterministic outputs, meaning the same input can generate different results. This makes conventional unit testing ineffective and often leaves developers experimenting endlessly with prompts. Stax is built to address this gap.

The tool enables developers to upload datasets—such as CSV files—or create test cases directly in the platform. It comes with prebuilt autoraters that automatically assess outputs for accuracy, coherence, and conciseness. Developers can also design custom evaluators, tailoring criteria such as ensuring a chatbot is concise, safeguarding sensitive data, or enforcing specific formatting rules.

By offering structured evaluation and clear metrics, Stax helps teams measure performance trends, compare models, and iterate more efficiently.

Example applications include training support chatbots to stay professional, refining summarization tools to exclude sensitive data, or aligning AI assistants with brand-specific styles.

Ultimately, Stax provides a repeatable and reliable testing framework, allowing AI products to be deployed with confidence and precision rather than intuition.