Worked on enhancing reliability and configurability in automated workflows across the langchain-ai/langchain and pydantic/pydantic-ai repositories. Addressed a Pydantic serialization issue in the OpenAI integration, preventing value errors when handling structured outputs by refining response handling and adding regression tests. Introduced a feature allowing per-tool retry configuration to take precedence over agent-level settings, enabling more granular control and reducing incomplete tool-call failures. Focused on backend development using Python, with an emphasis on robust API integration and comprehensive unit testing. The work improved the stability and resilience of agent processing, reducing production risk and supporting maintainable, test-driven development practices.