Parallel block run concurrently. Their outputs are aggregated in the configured step order and passed to the next step in the workflow.

Example
parallel_workflow.py
Handling Session State Data in Parallel Steps
Custom Python functions can accept arun_context parameter and update run_context.session_state.
Parallel branches share that session-state dictionary. Coordinate writes to the same keys, or assign separate keys to each branch, to avoid races.
