Many of us are using ChatGPT and co. now for a few years. These LLMs are very interesting and fascinating and we can use them for many interesting tasks, the next big thing being agents. But one thing I always wanted to try is building my own language model, all trained on my local machine.… Continue reading Building my own language model: Part 1
ACP Hello World
To complete the picture, in this blog post we are going to build a hello world ACP application. As with the A2A demonstration, we will also create a simple server and client application to demonstrate the basic programming model with ACP. ACP does a good job in their getting quickstart guide: https://github.com/i-am-bee/acp Server This is… Continue reading ACP Hello World
A2A Hello World
Let’s explore how A2A works in practice. In this blog post I’m demonstrating the basic usage of A2A, without using any AI. 🙂 Please note, this is a purely technical view, the challenges to build agents are not necessarily technical in nature, nonetheless I hope this post helps to get a basic understanding of A2A.… Continue reading A2A Hello World
MCP, ACP, A2A
Here is a quick overview of the various protocols we hear and read so much recently in the AI space. I don’t intend to go into the details, just a very brief and human readable, objective view. MCP Let’s start with MCP (Model Context Protocol), which I covered in one of my recent blog posts.… Continue reading MCP, ACP, A2A
Exploring Agentic AI: MCP with BeeAI
The next step of understanding how to build a proper agentic system is to explore how an agent can be extended with tools. Tools are, in my view, the most powerful extension of an LLM as it logically allows it to interact with the world: get additional context, take action. See my older blog post… Continue reading Exploring Agentic AI: MCP with BeeAI
Exploring Agentic AI: Agent Composition with BeeAI
In this blog post, we’re going to explore a new framework from IBM named BeeAI, which is set to solve a very important problem for me: agent composition. I’ve been using relatively simple agents for a while now. They’re incredibly handy for repetitive tasks, coding assistance, marketing, or testing. Sometimes it feels like using a… Continue reading Exploring Agentic AI: Agent Composition with BeeAI
Exploring Agentic AI: hello world with Semantic Kernel
In my last post we explored how we can build a very simple agentic application using CrewAI. Personally, I like to build these hello world applications to understand better how the frameworks function. In this post we will go through the same procedure, but this time we are going to use Java and Microsoft’s Semantic… Continue reading Exploring Agentic AI: hello world with Semantic Kernel
Exploring Agentic AI: hello world
Recently, I found myself pondering how best to demystify agentic systems and demonstrate their potential. The first challenge? Choosing the right programming language. As someone who has worked extensively with Java, it was tempting to use it here. However, Python’s rich ecosystem of AI frameworks made it the better choice for this exercise. For this… Continue reading Exploring Agentic AI: hello world
Exploring Agentic AI: From Assistants to Action Takers
In the world of AI, we’ve seen a fascinating evolution. Most likely, you’ve already heard the term agentic AI buzzing around. What started with conversational assistants like ChatGPT has now grown into something far more capable and transformative. But before diving into the details, let’s break it down. What is an Agent? At its core,… Continue reading Exploring Agentic AI: From Assistants to Action Takers
Fine-Tuning Large Language Models with LoRA: A Practical Guide
Large language models (LLMs) are very popular these days. Most likely you have used tools such as ChatGPT or Claude. They are great, for many different tasks. But what they are not good at is working with your own, private data. Wouldn’t it be great if you could chat with a large language model about… Continue reading Fine-Tuning Large Language Models with LoRA: A Practical Guide