Building AI Workflows Is Easy. Making Them Reliable Is Systems Engineering

Building the first version of an AI workflow is usually easy. Connect an LLM to a few tools. Add some instructions. Let the model decide what to do next. Run the demo. It works. The problem starts later, when that workflow becomes part of a real process. Suddenly the important questions are not about the prompt anymore. They are about reliability. What happens when a tool fails ? What happens when the model retries the wrong thing ? What happens when the workflow changes state but the ag...