Building a persistent conversational AI chatbot with Temporal

This post details the application of Temporal's Durable Execution to build a persistent, infinitely scalable conversational AI chatbot. It contrasts this approach with traditional stateless architectures, highlighting how treating each conversation as a Temporal Workflow overcomes limitations like session loss, limited scalability, and fragile error handling. The post outlines functional and non-functional requirements for such a chatbot, presents a traditional design with its drawbacks, and then illustrates a Temporal-based design where each conversation is a Workflow. It emphasizes how this enables stateless application proxies, resilient workflows that automatically resume after failures, maintainable modular design through Activities interacting with LLMs and tools, rich context management by passing conversation history to the LLM, and transparent state inspection. The implementation walkthrough focuses on the `ChatbotService.java` class responsible for processing user messages and interacting with Workflows.