AI & AEO

Semantic Chunking

Quick Definition

Semantic chunking is how AI retrieval systems break long content into smaller, semantically coherent passages that can be retrieved and cited independently.

In context

Pages structured with clear H2/H3 sections, focused paragraphs, and one-idea-per-block layouts get cleaner semantic chunks. Wall-of-text content gets chunked arbitrarily and loses ranking power in retrieval-augmented generation systems.

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Related terms

LLM (Large Language Model)

An LLM is a deep-learning model trained on vast text data, capable of generating human-like language. Examples: GPT-4, Claude, Gemini, Llama.

Generative Search

Generative search uses large language models to compose answers from multiple sources rather than simply linking to ranking pages.

AEO Optimization Tactics

AEO optimization tactics include clear structured answers, FAQ schema, comprehensive topical coverage, citation-friendly formatting, and strong entity signals.

Synthesized Answer

A synthesized answer is the unified response an AI engine produces by combining information from multiple cited sources into a single coherent reply.

Perplexity AI

Perplexity is a search engine that uses LLMs to generate answers with inline citations to source pages.

AI Overviews Optimization

AI Overviews optimization tactics aim to be cited as a source in Google's AI-generated answer boxes.

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