Chain of Thought

Chain of Thought

Term explanation

Definition and meaning

Chain 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.

LIZ AI applies chain-of-thought reasoning when composing or updating presentations: it thinks through the relevant context, data, and brand requirements step by step before generating slide content — producing more accurate, coherent results than single-pass generation.

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Other glossary terms

Tutorials

A tutorial is a structured learning resource that guides a learner step by step through a process, concept, or skill. Tutorials can take many forms — written guides, video walkthroughs, interactive modules, or one-on-one coaching sessions. Unlike formal courses, tutorials tend to be focused on practical application, helping learners achieve a specific outcome quickly. They are widely used in software onboarding, technical training, and skill development platforms.

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Chain of Thought

Chain 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 more

Concept Presentation

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.

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Generative Engine Optimization (GEO)

Generative engine optimization (GEO) is the practice of structuring content and digital presence to improve visibility in responses generated by AI systems — such as ChatGPT, Perplexity, Google Gemini, or Claude — rather than solely optimizing for traditional search engine rankings. Where SEO aims to rank on a results page, GEO aims to be cited inside an AI-generated answer. As AI-generated responses now account for over 60% of all search interactions, GEO has become critical alongside classical prompt engineering strategies for any organization that wants to remain visible in AI-driven search.

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