The code is the structure, the LLM is the glue at the joints. There’s a widespread misconception about automations “powered by artificial intelligence”: People picture a model you give an order to, which then carries out a complex operation from start to finish all on its own. It’s a seductive image, and almost always wrong….
Read MoreModel selection, infrastructure sizing, vertical fine-tuning and MCP server integration. All explained without the fluff. Why Run AI on Your Own Infrastructure? Let’s be honest: over the past two years, LLMs have evolved from a tool perceived as experimental and reserved for researchers into something companies use every day for concrete, practical tasks. And with…
Read MoreHi! Today I’d like to discuss a bit a quite hot topic in this world newly full of LLMs, namely MCP Servers! We’ll first see what MCP is and why it was created, moving then to a short hands-on with NetEye and in particular, the Elastic Stack feature module. Wait, what? MCP? What are we…
Read MoreIntroduction: What is MCP? The Model Context Protocol is an emerging open standard that defines how large language models and AI agents interact with external tools, services, and data sources. Instead of every AI provider building its own proprietary “tool calling” system, MCP provides a common protocol (typically over JSON-RPC) to expose capabilities such as…
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