W&B's core product is experiment tracking: a few lines of code in your training script log loss curves, learning rates, GPU utilization, sample outputs, and any custom metrics to a dashboard. You can compare hundreds of training runs side-by-side, filter by hyperparameters, and identify which configurations worked best. The key insight was making this frictionless — wandb.init() and wandb.log() are all most users need.
W&B expanded into adjacent tools: Sweeps (automated hyperparameter search), Artifacts (dataset and model versioning), Tables (interactive data exploration), and Reports (shareable experiment analyses). Their Weave product targets LLM application development specifically, with tools for prompt evaluation, LLM pipeline tracing, and output quality monitoring. The platform covers the full ML lifecycle from experiment to production monitoring.