Term explanation
A concept presentation introduces a new idea, product concept, or strategic direction to an audience for evaluation or feedback. It is typically used in early stages of a project — before a full proposal is developed — to test reactions, align stakeholders, or secure initial approval. A good concept presentation clearly communicates the core idea, explains the problem it solves, and outlines the key assumptions, without yet committing to a full implementation plan.
LIZ AI helps structure complex concept presentations from your documents and data. The Smart Presentation Composer translates your ideas into a clear, narrative-driven slide structure — ready to present.
Learn more →Process questions ask participants to explain how something works, how a decision was made, or how a result was reached — rather than simply what the answer is. They focus on reasoning, methodology, and the steps taken to arrive at an outcome. In training, coaching, and facilitated workshops, process questions help participants reflect on their thinking and deepen their understanding. They are more cognitively demanding than recall questions and are effective for developing critical thinking and problem-solving skills.
Learn morePresentation automation refers to the use of software to automatically create, update, or distribute presentations based on predefined rules, templates, or live data. It eliminates repetitive manual tasks such as copy-pasting figures into slides, reformatting decks for different audiences, or applying brand updates across hundreds of files. Common use cases include automated management reports, investor updates, and sales decks that always reflect the latest numbers.
Learn moreLeading questions are phrased in a way that suggests or implies a preferred answer, subtly guiding the respondent toward a specific response. For example, 'Don't you think this approach is more efficient?' nudges toward agreement. In presentations and sales contexts, leading questions can be used deliberately to build consensus or steer a conversation. However, they can also introduce bias in research and surveys, making it important to recognize and manage their influence on responses.
Learn moreA 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.
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