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Tooling

Power agents with full context of your experiments and traces with W&B MCP server

Power agents with full context of your experiments and traces with W&B MCP server

The W&B Model Context Protocol (MCP) is a hosted endpoint that enables AI agents to intelligently interact with all Weights & Biases data, including runs, traces, evaluations, and reports. It features discovery tools for smart queries, automated analysis for comparing experiments and identifying regressions, and seamless integration with IDEs, coding agents, and chat interfaces like Mistral AI for streamlined ML workflows and on-the-go reporting.

Fighting AI with AI — Lawrence Jones, Incident

Fighting AI with AI — Lawrence Jones, Incident

Lawrence Jones from Incident.io explains why their team needed AI to debug their complex AI SRE product. He details three powerful patterns: a CLI for agents to manage large evaluation files, serializing debug UIs into downloadable file systems for agent-based tracing, and multi-agent pipelines for fleet-scale failure analysis.

You can't just one shot it — Mehedi Hassan, Granola

You can't just one shot it — Mehedi Hassan, Granola

A product engineer from Granola shares a candid account of the challenges in moving AI features from the playground to production. This talk covers the pitfalls of "one-shot" solutions like web search and generic prompts, and details Granola's strategy of building custom internal tracing and development tooling to create a tight, effective feedback loop for iteration.