Term explanation
A multi-agent system is a setup in which several autonomous AI agents work together, each handling a specific part of a larger task. The agents can communicate, divide work, and combine their outputs to achieve goals that would be difficult for a single model. Typically, an orchestrator agent coordinates the workflow while specialist agents execute defined subtasks. In enterprise contexts, multi-agent systems allow complex workflows — such as researching a topic, drafting content, checking compliance, and distributing a presentation — to be fully automated.
The architecture behind LIZ AI is built on multi-agent principles: specialized agents handle data retrieval, content composition, brand compliance, and distribution — working in concert to deliver complete, production-ready presentations.
Learn more →The Notes Page view in PowerPoint shows a smaller version of the slide with a small area for notes underneath. In the presentation every slide has it's own space for notes. During the presentation the notes do not appear on screen. They are just visible in the presentation mode.
Learn moreChain of thought is an AI reasoning technique in which a model explicitly works through intermediate steps before arriving at a final answer. By laying out its reasoning step by step, the model produces more accurate and reliable outputs — especially for complex, multi-part problems. In agentic AI systems, chain-of-thought reasoning is used to plan workflows and make decisions at each stage of an agent loop. For enterprise applications, it increases transparency and makes AI behavior easier to audit.
Learn moreA .pot file is a legacy PowerPoint template format used to define reusable styles, layouts, and formatting for presentations. Like its successor .potx, it allows teams to create multiple presentations that share the same visual identity without starting from scratch each time. The .pot format was replaced by .potx in Office 2007, which introduced an open XML-based structure for improved compatibility.
Learn moreMicrolearning delivers educational content in short, focused segments — typically between 3 and 10 minutes. Rather than completing a lengthy course, learners engage with bite-sized units that cover a single concept or skill. Microlearning is effective for knowledge reinforcement, mobile training, and just-in-time learning. It fits naturally into busy workdays and is widely used in corporate onboarding, compliance training, and professional development programs.
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