I want to share my experience in the cloud, AI, and agents development areas.
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.
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.
This cheat sheet provides a two-step guide for adding users to your watsonx project in IBM Cloud.
Today I want to focus on a interesting question I got: "Why does IBM call something a code pattern and not just sample?" The question was related to my last blog. Here is my personal point of view First, there is no existing definition of the word pattern in combination with usage of the word code. Based on... Continue Reading →
Why should I blog about this topic? You can just “google” and find the resources by your own. I write this blog post, because I want to share briefly my experience with you and I hope you can save time, when you get started with IBM Cloud development. This blog post is about following major IBM Cloud information... Continue Reading →
Thomas Suedbroecker's Blog 