Why workflow orchestration?
AI applications often need more than an LLM call. A production workflow may need a chat interface, authentication, business APIs, databases, communication tools, logging and a fallback path.
A practical workflow
A useful architecture can separate the incoming chat request, conversation context, cache lookup, retrieval, model invocation and response delivery. n8n can orchestrate these steps while keeping integrations visible and manageable.
Where AI tools fit
ChatGPT and Claude AI can be used as model capabilities inside the workflow. The workflow should control what context is provided, which tools can be called and how the final response is returned.
Key lesson
Treat the LLM as one component of a larger application. Clear workflow boundaries, observability and safe data handling are as important as prompt quality.