How to build deep research agents using Temporal and Braintrust

What this post added

This post details the implementation of a multi-agent system for deep research agents using Temporal Workflows and Activities. It showcases how Temporal's Durable Execution addresses common failure modes in LLM-based pipelines, such as API timeouts and partial failures, by mapping agents to Activities with appropriate retry semantics and timeout configurations. The post also describes the use of Pydantic models for structured data contracts between agents and the integration of Braintrust for end-to-end observability and evaluation of the research pipeline.