W&B Models is the system of record for the entire model development lifecycle. This guide explores how to monitor training, tune hyperparameters, track artifacts and lineage for reproducibility, and automate MLOps workflows like evaluation and deployment using a central platform.
Engineers building AI agents face a combinatorial explosion of configuration choices (prompts, models, parameters), leading to guesswork and suboptimal results. This talk introduces a structured, data-driven approach using multi-objective optimization to systematically explore this vast design space. Learn how the Traigent SDK helps engineers efficiently identify optimal tradeoffs between cost, latency, and accuracy, yielding significant quality improvements and cost reductions without manual trial-and-error.