Most AI agent frameworks force you to write code for every decision point, branching path, and error handler. This works for simple chains, but production agents need complex orchestration that's hard to reason about in code alone. Visual workflow builders solve this by letting you design agent behavior as a graph -- drag, drop, connect, and deploy. The Problem with Code-Only Agent Frameworks Consider a customer support agent that needs to: Classify the incoming ticket Route to the right specialist agent based on category Pull relevant knowledge from a vector store Generate a response draft Get human approval if the confidence score is low Send the response and log it to the CRM In a code-only framework, this is hundreds of lines of boilerplate: state management, conditional routing, error handling, retry logic, and callback chains. When requirements change (and they always do), refactoring the flow is tedious and error-prone.…