How we taught agents to use good retrieval - Hanna Lichtenberg, Mixedbread AI

Mixedbread AI addresses the "Oracle Gap" – the disparity between LLM reasoning and retrieval capabilities – by developing agents trained to use advanced search tools effectively. They demonstrate how current LLMs generate poor queries due to training biases and introduce a sophisticated agent harness with diverse search tools and a unique training regimen, including supervised fine-tuning and reinforcement learning with custom rewards, to teach agents to form precise semantic queries. This approach significantly improves performance on benchmarks like Oblique Congress and Snowflake's Match QA, closing the gap between theoretical perfect retrieval and real-world agent performance.