Apurva Gandhi enhanced the All-Hands-AI/agent-sdk by introducing a shared response identifier, llm_response_id, to all LLM-generated events, focusing on improving observability and traceability in event-driven workflows. Working primarily in Python and leveraging backend and API development skills, Apurva extended the OpenHands SDK’s event models to support this new identifier. This technical approach enabled grouping of related actions and tracing results from parallel function calls originating from the same LLM response, addressing challenges in debugging and analytics. The work provided more reliable orchestration and faster issue diagnosis for LLM pipelines, demonstrating thoughtful depth in event tracking architecture.