Choosing the right model and prompt is crucial for crafting effective AI features, and Braintrust provides a developer-friendly platform to systematically test these combinations at scale. The platform transforms traditional testing methods, which can be slow and unreliable, into rigorous experiments by allowing developers to compare accuracy, cost, and latency across model/prompt combinations. It offers a unified approach where datasets, prompts, models, and scorers are versioned and shareable, enabling seamless switching between different LLM providers. Braintrust's tools include automated scoring, an intuitive experiments UI, and real-time iteration capabilities, ensuring that developers can prototype, test, and refine their AI workflows efficiently. An example highlighted in the text demonstrates how Braintrust was used to select the most cost-effective and accurate model for a support bot by comparing different AI models and prompts, ultimately improving AI workflows with data-driven decisions.