I want to share my experience in the cloud, AI, and agents development areas.
A structured experiment using ChatGPT and Codex in VS Code to generate a reproducible open-source Docling preprocessing pipeline with strict engineering constraints.
This post outlines the process of creating a deployable function in Jupyter Notebook using watsonx.ai, which is then exposed via a REST API. It emphasizes the separation of development in projects and runtime in deployment spaces, detailing steps from environment setup to function deployment and usage of the API endpoint.
This blog post details the author's exploration of IBM Bob while building an MCP server for Astra DB. It emphasizes learning through experimentation in Code Mode, focusing on automation and iterative development. The author shares insights on prompt creation, workflow challenges, and the importance of documentation throughout the process, ultimately achieving a functional server setup.
The post discusses how the current focus on fast, outcome-driven innovation in the GenAI landscape risks sidelining invention, which nurtures genuine new possibilities. It emphasizes that while innovation thrives in KPI-oriented settings, invention often struggles for justification. The author calls for a deliberate balance to preserve the space for invention in future developments.
The post discusses automating local testing of IBM watsonx Orchestrate with Ollama models using a Bash script. The script simplifies the setup process, ensuring proper connections and configurations. It initiates services, confirms model accessibility, reducing typical setup errors.
The this post describes a Bash automation script for setting up the IBM watsonx Orchestrate Development Edition. The script automates tasks like resetting the environment, starting the server, and configuring credentials, allowing for a more efficient workflow. It addresses common setup issues, ensuring a repeatable and successful process.
In this post, I share my initial experiences with IBM Bob, an AI SDLC tool. By discuss setting it up with VS Code, its configurable modes, and key features. I show some details using IBM Bob to build a RAG system, highlighting its impressive support for planning, coding, and documentation, enhancing workflow efficiency. Introduction First... Continue Reading →
The post explains why traditional Retrieval-Augmented Generation (RAG) approaches no longer scale and how modern architectures, including GraphRAG, address these limitations. It highlights why data quality, metadata, and disciplined system design matter more than models or frameworks, and provides a practical foundation for building robust RAG systems, illustrated with IBM technologies but applicable far beyond them.
This post is about setup to utilize Granite 4 models in Ollama for VS Code with watsonx Code Assistant. The process includes inspecting available models, uninstalling old versions, installing new models, and configuring them for effective use. The experience emphasizes exploration and learning in a private, efficient AI development environment.
The Model Context Protocol (MCP) is being increasingly utilized in AI applications, particularly with the watsonx Orchestrate ADK. This setup allows users to develop and manage agents and tools through a seamless integration of the MCP server and the Development Edition, enhancing user interaction and functionality in coding environments.
Thomas Suedbroecker's Blog 