Weights & Biases (W&B) is the leading AI developer platform for experiment tracking, model management, and LLM application observability. Used by over 1,000 enterprise organizations and top AI research labs worldwide, W&B provides a unified system of record for the entire AI development lifecycle. The platform consists of two core products: W&B Models for training, fine-tuning, and managing AI models with comprehensive experiment tracking, hyperparameter sweeps, and artifact versioning; and W&B Weave, a lightweight code-first toolkit for building, evaluating, and monitoring LLM-powered applications and autonomous agents. Weave enables developers to trace multi-step agent reasoning, debug hallucinations, and evaluate production performance with a simple Python decorator (@weave.op()). It automatically logs calls to OpenAI, Anthropic, and other LLM providers, recording inputs, outputs, metadata, token usage, and costs in a unified dashboard. W&B also offers hosted inference with a playground for comparing different LLMs and settings side by side. The platform integrates deeply with popular ML frameworks including PyTorch, TensorFlow, Hugging Face, and LangChain, and supports deployment in multi-tenant cloud, single-tenant cloud, or customer VPC environments. W&B has become the standard MLOps tool in both industry and academia, with free Pro licenses available for academic research.