Fundamentals
→ The “What is it?” Layer
These terms define the basic building blocks of LLMs and how they “see” information.
- Artificial Intelligence (AI)
- Large Language Model (LLM)
- Token
- Context Window
- Embedding
- Inference
- Hallucination
- Prompt
Prompting Techniques
→ The “How do I do it?” Layer
These are the methodologies you teach your readers to improve their results.
- Zero-Shot Prompting
- Few-Shot Prompting
- Chain-of-Thought (CoT)
- Tree-of-Thought (ToT)
- Role-Based Prompting (Persona Prompting)
- Prompt Chaining
- Prompt Template (Structured Prompting)
- Multimodal Prompting
- Negative Prompting
Architecture & Technical
→ The “Under the Hood” Layer
These terms help advanced users understand why models perform the way they do.
- Transformer Architecture
- Attention Mechanism (Self-Attention)
- System Prompt (Pre-Prompt)
- Temperature
- Top-P (Nucleus Sampling)
- Logits
- Fine-Tuning
- RLHF (Reinforcement Learning from Human Feedback)
- Retrieval-Augmented Generation (RAG)
- Vector Database
Advanced Concepts
→ The “Future-Proof” Layer
These terms keep your Encyclopedia relevant for 2026 and beyond.
- Agentic AI (AI Agents)
- Prompt Injection (Security)
- Prompt Optimization
- Structured Output (JSON/Schema)
- Model Distillation
- Context Caching
- Synthetic Data
- Prompt Versioning
- Generative Engine Optimization (GEO)
1. Fundamentals (The “What is it?” Layer)
These terms define the basic building blocks of LLMs and how they “see” information.
-
Artificial Intelligence (AI)
-
Large Language Model (LLM)
-
Token
-
Context Window
-
Embedding
-
Inference
-
Hallucination
-
Prompt
2. Prompting Techniques (The “How do I do it?” Layer)
These are the methodologies you teach your readers to improve their results.
-
Zero-Shot Prompting
-
Few-Shot Prompting
-
Chain-of-Thought (CoT)
-
Tree-of-Thought (ToT)
-
Role-Based Prompting (Persona Prompting)
-
Prompt Chaining
-
Prompt Template (Structured Prompting)
-
Multimodal Prompting
-
Negative Prompting
3. Architecture & Technical (The “Under the Hood” Layer)
These terms help advanced users understand why models perform the way they do.
-
Transformer Architecture
-
Attention Mechanism (Self-Attention)
-
System Prompt (Pre-Prompt)
-
Temperature
-
Top-P (Nucleus Sampling)
-
Logits
-
Fine-Tuning
-
RLHF (Reinforcement Learning from Human Feedback)
-
Retrieval-Augmented Generation (RAG)
-
Vector Database
4. Advanced Concepts (The “Future-Proof” Layer)
These terms keep your Encyclopedia relevant for 2026 and beyond.
-
Agentic AI (AI Agents)
-
Prompt Injection (Security)
-
Prompt Optimization
-
Structured Output (JSON/Schema)
-
Model Distillation
-
Context Caching
-
Synthetic Data
-
Prompt Versioning
-
Generative Engine Optimization (GEO)
Pro-Tip: How to plan your “Hierarchy”
Since you are using CPT UI, don’t just dump all of these as “posts.” Use your Taxonomies to group them.
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Example Hierarchy:
-
Category: Fundamentals
-
Entry: Token
-
Entry: Context Window
-
Entry: Temperature
-
-
Category: Prompting Techniques
-
Entry: Chain-of-Thought
-
Entry: Zero-Shot Prompting
-
-
By organizing your terms into these categories, your Encyclopedia will look like a structured textbook. When you are writing an entry for “Chain-of-Thought,” you can easily link back to “Fundamentals > Context Window” or “Fundamentals > Token,” which creates that “Wikipedia-style” network of internal links that Google loves.
Are you planning to write the definitions for these yourself, or would you like a template for how to structure the “Definition” page of an entry so that it stays consistent across the whole encyclopedia?
The Encyclopedia Entry Template
You can save this as a “Pattern” or “Reusable Block” in your WordPress editor to ensure you never have to rebuild the structure from scratch.
Question? Answer.
[H2: References] [List of external sources with hyperlinked titles] [H2: Further Reading] [List of internal links to related Encyclopedia entries]Why this structure works for your SEO:
The “Definition Paragraph”: This is your best chance to capture the “Featured Snippet” (Position Zero) in Google. Google loves concise, high-quality answers at the very top of a page.
The “Technical Overview” (H2): This satisfies the “Expertise” part of E-E-A-T. By adding depth here, you prevent the page from being too thin, which is a common reason encyclopedia sites fail to rank.
“Practical Application” (H2): This is where you separate yourself from a dictionary. By adding “How-to” context, you satisfy the user’s need for utility, which keeps them on the page longer.
“Relationship to Other Concepts” (H2): This is the secret to building “Topical Authority.” By explicitly mentioning other terms (e.g., relating Temperature to Tokens), you create semantic relevance for the search engine, proving your site is a deep, interconnected knowledge hub.
“FAQ” (H2): Using the WordPress FAQ block here ensures the schema is generated automatically, helping you dominate search results with an expanded footprint.

