Evaluations

Five hard earned lessons about Evals — Ankur Goyal, Braintrust

Five hard earned lessons about Evals — Ankur Goyal, Braintrust

Building successful AI applications requires a sophisticated engineering approach that goes beyond prompt engineering. This involves creating intentionally engineered evaluations (evals) that reflect user feedback, focusing on "context engineering" to optimize tool definitions and outputs, and maintaining a flexible, model-agnostic architecture to adapt to the rapidly evolving AI landscape.

Practical tactics to build reliable AI apps — Dmitry Kuchin, Multinear

Practical tactics to build reliable AI apps — Dmitry Kuchin, Multinear

Moving an AI PoC from 50% to 100% reliability requires a new development paradigm. This talk introduces a practical, evaluations-first approach, reverse-engineering tests from real-world user scenarios and business outcomes to build a robust benchmark, prevent regressions, and enable confident optimization.