### Answer
The issue you're describing—where the agent returns to previous nodes unexpectedly—has several potential causes and solutions:
## Common Causes
**Split Node Behavior**: When using split nodes after global nodes, the agent may loop back to the global node instead of proceeding forward [(1) ](
) . This happens because the split node can inadvertently redirect flow back to the global node .
**Unclear Transition Conditions**: The LLM may not understand when to move to the next step [(2) ](
) . Without explicit triggers, the agent can get stuck or return to previous nodes .
**Global Node Configuration**: Global nodes can be triggered at any point in the conversation, which may cause unexpected returns to earlier parts of the flow [(1) ](
) .
## Solutions to Try
**Review Transition Conditions**: Ensure your transition conditions precisely match your intended triggers [(3) ](
) . Consider breaking down complex conditions into multiple simpler ones .
**Add Transition Finetune Examples**: Provide examples to help the model understand your expectations . This can improve transition reliability .
**Make Node Instructions More Specific**: If nodes contain multiple instructions, split them into separate nodes . For example, if collecting name, phone, and address, create three separate nodes instead of one .
**Check Global Node Setup**: If using global nodes with split nodes, be aware that this combination can cause looping behavior [(1) ](
) . Consider restructuring your flow to avoid this pattern .
**Adjust Transi