When people think about artificial intelligence, they often focus mainly on the models themselves. They talk about LLMs, embeddings, RAG, inference, fine-tuning and the quality of generated responses. These are all important areas, but in real-world projects another, less visible yet critical topic appears very quickly: infrastructure. An AI model has to run somewhere. If […]
Most companies are implementing AI the wrong way Many organizations start with a simple scenario — employees use tools like ChatGPT, data is sent to external services, the first automations appear, and the company expects quick efficiency gains. The real problems appear later. AI starts processing documents, customer data, emails, financial information, infrastructure configurations, or
A few years ago, IT infrastructure was still managed mostly by hand. Administrators logged into servers, installed packages, adjusted configurations, and hoped that every environment would remain consistent. The problem is that manually managed infrastructure quickly becomes difficult to maintain, error-prone, and heavily dependent on the knowledge of specific individuals. That is why more and
