Durable RAG and agents: MongoDB and Temporal doing it better together

This post details how Temporal's Durable Execution is applied to a RAG knowledge base and research agent architecture. It highlights the use of Temporal Workflows for reliable data ingestion, including chunking, embedding, and indexing into MongoDB Atlas. It also explains how Temporal orchestrates the agent's reasoning loop, ensuring state is preserved across fallible external calls to models, tools, and databases. The post emphasizes the benefits of Durable Execution in eliminating the need for systems like Kafka for buffering and enabling seamless infrastructure maintenance for long-running jobs.