What are Topics in Braintrust and how do they work? (2026)

Braintrust Topics provides AI teams with an automated and scalable method for reviewing production traces by classifying logs based on user intent, sentiment, and issues, ultimately clustering similar traces for more efficient analysis. This approach addresses the challenge of manually reviewing the vast number of logs generated by AI agents, which can reach tens of thousands per week. By automating trace classification, Braintrust Topics enables teams to quickly identify recurring problems, build evaluation datasets from real production traffic, and prioritize which patterns need further review or scoring. The system operates through a daily pipeline encompassing preprocessing, facet summarization, clustering, and classification stages, with built-in facets focusing on Task, Sentiment, and Issues. Custom facets can also be created for more domain-specific inquiries. Braintrust Topics integrates into the broader Braintrust evaluation workflow, enhancing trace observability and providing actionable insights from production data. It is available across different plan tiers, with specific conditions for enabling and utilizing its features, making it a valuable tool for teams aiming to improve AI agent performance and user experience.