Category

Artificial Intelligence

Artificial intelligence in everyday work is almost always less spectacular than the way it gets described, and far more useful than it seems to anyone who tried it once and got a wrong answer delivered in a confident tone. Here we talk about how it is actually used inside a software product: where it is worth putting, where deterministic rules are cheaper and more reliable, and how to build a system that says it does not know something instead of inventing it. That is the central problem of any serious AI application, and it is solved with architecture — declared sources, verified data, explicit limits — not with the right prompt. You will find material on content generation governed by a company knowledge base, on agents that carry out real operations rather than merely answering, and on what these features actually cost: a company evaluating AI needs to know how much it consumes, not only what it promises. The point of view is that of someone who builds these systems and then maintains them over time, with the problems that surface in the second year rather than at the demo.