AI terms, clearly explained
Brief explanations of the AI terms you encounter. What they mean and, above all, why they matter for your business.
AI agent
An AI agent is software that can pursue a goal by planning steps, using tools and integrations, and performing actions within agreed boundaries. While a simple chatbot mainly answers questions, an agent can also prepare or carry out work.
Read the explanation →Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) means adapting your content so that AI answer engines such as ChatGPT, Gemini and Perplexity mention and cite your brand when someone asks a question. SEO helps your site become visible in Google; GEO gets you into the AI's answer itself.
Read the explanation →Harness
A harness is the software around a language model that provides tools, supplies context, keeps track of what happened and limits execution. The model comes up with the next step; the harness determines what that step can be in practice and what actually happens afterwards.
Read the explanation →Human-in-the-loop
Human-in-the-loop means an AI agent stops at predefined points and lets a person decide before it continues. Such a point is necessary when the risk, impact, uncertainty or limited reversibility of an action calls for it.
Read the explanation →Judgement model
A judgement model (in Dutch: beslissingsmodel) is an AI model that chooses from predefined answers, such as a category, a score or a yes/no, and returns a confidence score with each choice. It is much faster and cheaper than a large language model, but it can only choose; it leaves writing to other systems.
Read the explanation →Microsoft Copilot Studio
Microsoft Copilot Studio is a low-code environment where organisations build AI agents and workflows, connect them to their own knowledge and systems, and make them available in the channels where people work. It is intended for an organisational agent built around a clearly defined process.
Read the explanation →State (in AI agents)
In an AI agent working in a business process, state is the recorded current situation. This includes the process status, pending steps, previous results and approvals. A model cannot observe that situation itself and may fill in a plausible outcome when information is missing.
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