What if the way AI agents interact with tools and resources could be as seamless as browsing the web? Imagine a world where developers no longer wrestle with custom-built adapters or fragmented ...

Imagine you’ve trained or fine‑tuned a chatbot or an LLM, and it can chat comfortably without any serious hiccups. You feed it a prompt and it responds. However, it’s stuck in a bubble: It only knows ...

Imagine a world where your AI tools don’t just work for you but work with each other—seamlessly, intelligently, and without the frustration of endless custom integrations. This isn’t a distant dream; ...

The past ten years have seen incredible advancements in the realm of Artificial Intelligence, but paradoxically, some of the most overt shortcomings of AI are still based not on intelligence but on ...

The Model Context Protocol (MCP) for agentic AI has gained much traction since being introduced by Anthropic last November, and now it has a C# SDK. The MCP is a standard for integrating large ...

As the development of AI tools accelerates, organizations are under increasing pressure to move models from prototype to production securely and with scalability. Behind the scenes, managing AI models ...

Making inherently probabilistic and isolated large language models (LLMs) work in a context-aware, deterministic way to take real-world decisions and actions has proven to be a hard problem. As we ...

AI agents and agentic workflows are the current buzzwords among developers and technical decision makers. While they certainly deserve the community's and ecosystem's attention, there is less emphasis ...

While the current AI boom was sparked by the launch of OpenAI’s ChatGPT in late 2022, it wasn’t until late 2024 that its true power could be recognized, when Anthropic unveiled the Model Context ...

At this year's Build conference, Microsoft unveiled a major expansion of its agent-based AI platform, highlighting new tools to securely build, customize and orchestrate intelligent agents across ...