
Michał Koruszowic developed and enhanced AI and data science workflows across IBM/watsonx-ai-samples and deepsense-ai/ragbits, focusing on model deployment, real-time streaming, and secure, maintainable infrastructure. He delivered ONNX model conversion notebooks and documentation, enabling seamless export from frameworks like scikit-learn and LightGBM, and improved deployment guidance using Python and Jupyter. In the langgraph-react-agent template, he implemented real-time streaming for dynamic AI responses. For deepsense-ai/ragbits, Michał strengthened FastAPI dependency management, refactored chat UI components with React and JavaScript, and improved CI/CD pipelines, addressing security vulnerabilities and streamlining release processes for more robust, production-ready deployments.
March 2026 monthly wrap-up for deepsense-ai/ragbits: Delivered user-facing UI/auth enhancements, hardened security posture through dependency management, and streamlined CI/CD/release workflows to accelerate and stabilize deployments. Focused on business value, maintainability, and release quality.
March 2026 monthly wrap-up for deepsense-ai/ragbits: Delivered user-facing UI/auth enhancements, hardened security posture through dependency management, and streamlined CI/CD/release workflows to accelerate and stabilize deployments. Focused on business value, maintainability, and release quality.
February 2026 monthly summary for deepsense-ai/ragbits. Key accomplishment: Dependency-management improvement for FastAPI by extending installation with standard extras to ensure all required packages are installed for optimal functionality.
February 2026 monthly summary for deepsense-ai/ragbits. Key accomplishment: Dependency-management improvement for FastAPI by extending installation with standard extras to ensure all required packages are installed for optimal functionality.
February 2025 monthly summary for IBM/watsonx-ai-samples focusing on feature delivery that enhances ONNX deployment workflows. Delivered end-to-end ONNX model conversion notebooks for LightGBM, CatBoost, and scikit-learn, unified and standardized existing notebooks for consistency, and updated HTML representations and deployment guidance to streamline ONNX-based scikit-learn workflows (installation, training, conversion, deployment) in watsonx.ai Runtime. No major bugs fixed this month; emphasis was on documentation and notebook improvements to boost developer productivity and deployment reliability.
February 2025 monthly summary for IBM/watsonx-ai-samples focusing on feature delivery that enhances ONNX deployment workflows. Delivered end-to-end ONNX model conversion notebooks for LightGBM, CatBoost, and scikit-learn, unified and standardized existing notebooks for consistency, and updated HTML representations and deployment guidance to streamline ONNX-based scikit-learn workflows (installation, training, conversion, deployment) in watsonx.ai Runtime. No major bugs fixed this month; emphasis was on documentation and notebook improvements to boost developer productivity and deployment reliability.
December 2024 focused on delivering business value through real-time streaming capabilities in the langgraph-react-agent template within IBM/watsonx-ai-samples. Implemented streaming support to enable dynamic AI responses and improved user experience, with a stable integration ready for broader adoption. No major bugs fixed this month; stabilization and iteration around streaming were prioritized to accelerate time-to-value for downstream applications.
December 2024 focused on delivering business value through real-time streaming capabilities in the langgraph-react-agent template within IBM/watsonx-ai-samples. Implemented streaming support to enable dynamic AI responses and improved user experience, with a stable integration ready for broader adoption. No major bugs fixed this month; stabilization and iteration around streaming were prioritized to accelerate time-to-value for downstream applications.
Month: 2024-11 — Highlights for IBM/watsonx-ai-samples: Delivered documentation updates for ONNX model conversion (TensorFlow/Keras) to reflect changes, with improved download and conversion steps and added Keras support. Commit ac40cbebf572e551bc66c322ebf5534dc8f26a4f documents alignment with notebook changes and ensures consistency across developer guides.
Month: 2024-11 — Highlights for IBM/watsonx-ai-samples: Delivered documentation updates for ONNX model conversion (TensorFlow/Keras) to reflect changes, with improved download and conversion steps and added Keras support. Commit ac40cbebf572e551bc66c322ebf5534dc8f26a4f documents alignment with notebook changes and ensures consistency across developer guides.

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