I want to share my experience in the cloud, AI, and agents development areas.
This post discusses a local setup utilizing IBM Bob to generate an agent for watsonx Orchestrate, specifically with tools from the Galaxium Travels MCP server. It explains the architecture, customization of Bob, and integration with various components, providing both learning and practical implementation value for developers.
This blog post explores the paradox of AI's growth potential versus the increasing trend toward data protectionism. It highlights how AI tools are hindered by data access limitations, posing risks to innovation. The observation implies that as data becomes more valuable, organizations may withhold it, undermining the openness that has historically fueled AI development.
The article explores the potential for using the Model Context Protocol (MCP) as a primary backend interface instead of traditional REST APIs in AI-enabled applications. Through the Galaxium Travels experiment, it examines the advantages and disadvantages of an MCP-first architecture, advocating for its use to reduce duplication and complexity while acknowledging REST's established role in many ecosystems.
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.
This blog post outlines a practical example of setting up a custom component in Langflow to connect with an external weather API and import it into the watsonx Orchestrate Development Edition. The process emphasizes learning through experimentation rather than achieving a flawless solution, highlighting the potential of Langflow and watsonx Orchestrate for AI development.
This post explores how Generative AI and Agentic AI emphasize trustworthiness over absolute determinism. As AI's role in enterprises evolves, organizations must focus on building reliable systems that operate under risk, balancing innovation with accountability. A personal perspective.
The post discusses integrating Knowledge Graphs with Retrieval-Augmented Generation (RAG), specifically using Neo4j and LangGraph. It outlines an example setup where extracted document data forms a structured graph for querying. The system enables natural question-and-answer interactions through AI, enhancing information retrieval with graph relationships and embeddings.
The blog post outlines the process of setting up the Agent Developer Kit (ADK) to build and run AI agents locally using WatsonX Orchestrate Developer Edition. It involves setting up prerequisites, installing the necessary software, and loading an example agent—optional integration with Langfuse for observability.
Thomas Suedbroecker's Blog 