Reference
AI Glossary
Plain-English definitions of AI terms you'll actually encounter. No PhD required. 49 terms and growing.
A
Adapter
Think of a massive language model as a fully built Lego castle. An adapter is a small plug‑in block you snap onto the existing walls to give the castl...
Agent
An AI system that can take actions autonomously — reading files, calling APIs, running code, making decisions — not just generating text. Agents do wo...
Agentic Workflow
A process where AI operates with autonomy: planning steps, using tools, evaluating results, and iterating without human intervention at each step. The...
API(Application Programming Interface)
A structured way for software to talk to other software. When you send a prompt to Claude through code instead of a chat window, you're using an API.
Attention
The mechanism that lets AI focus on relevant parts of the input when generating output. It's why AI can connect "the cat sat on the mat" to a question...
C
Chain of Thought
A prompting technique where you ask AI to reason step by step instead of jumping to the answer. It improves accuracy on complex tasks by forcing the m...
Chunking
Splitting documents into smaller pieces for storage in a vector database. Chunk size is a critical design choice: too big and you retrieve irrelevant ...
Completion
The text that an AI model generates in response to a prompt. You send a prompt; you get back a completion.
Context Engineering
The practice of carefully curating what information you feed to AI — not just how you ask, but what data you include. More strategic than prompt engin...
Context Window
The maximum amount of text an AI can "see" at once — both your input and its output combined. Think of it as the model's working memory. Bigger window...
F
Few-Shot
A prompting technique where you provide 2-5 examples of the desired input/output format before asking AI to process new input. Dramatically improves c...
Fine-Tuning
Training an existing AI model on your own specific data to make it better at a particular task. Like teaching a general-purpose chef to specialize in ...
G
Grounding
Anchoring AI responses in real data (retrieved documents, search results, database records) rather than relying on training data alone. RAG is the mos...
Guardrails
Rules and constraints you set to keep AI output safe, on-topic, and within boundaries. "Do NOT modify existing tests" is a guardrail. They prevent AI ...
H
Hallucination
When AI generates information that sounds confident but is factually wrong. It doesn't "know" it's making things up — it's pattern-matching, not fact-...
Human-in-the-Loop
A pattern where sensitive AI actions (send email, delete files, deploy code) require human approval before execution. The agent proposes, the human ap...
I
Inference
The process of running a trained AI model to generate output. When you send a prompt and get a response, that's inference. Training teaches the model;...
Instruction Tuning
Instruction tuning is like giving a student a cheat sheet of how to answer different types of questions before the exam. You train a language model on...
L
Latency
The time between sending a prompt and receiving the first token of the response. Lower latency means faster responses. Affected by model size, server ...
LLM(Large Language Model)
A massive AI model trained on enormous amounts of text data. Claude, GPT, and Gemini are all LLMs. "Large" refers to the billions of parameters (adjus...
M
MCP(Model Context Protocol)
An open protocol that lets AI models connect to external tools and data sources in a standardized way. Like USB for AI — one protocol, many tools. Cre...
MCP Server
A lightweight program that exposes tools to AI via the Model Context Protocol. One MCP server for Gmail means every AI app can send/read email. Build ...
Model Drift
Model drift happens when a model's performance slides downhill because the real‑world data it encounters gradually differs from the data it was traine...
Model Registry
A model registry is like a library catalog for your AI models. It records each model version, its training data, performance metrics, and who approved...
Multimodal
An AI that can process multiple types of input — text, images, audio, video — not just words. A multimodal model can look at a photo and describe what...
P
Parameters
The adjustable numbers inside a neural network that the model learns during training. More parameters generally means more capability, but also more c...
pRAG(Personal RAG)
A RAG system built on your own knowledge base — blog posts, talks, documents, investor memos — so an AI can answer questions grounded in your actual e...
Prompt
The input you give to an AI model — the question, instruction, or context that tells it what to do. Better prompts get better outputs. This is the ski...
Prompt Engineering
The art and science of crafting prompts that get the best results from AI. Includes techniques like role prompting, chain-of-thought, few-shot example...
Prompt Injection
A security attack where malicious instructions are hidden in data that AI processes. Like SQL injection, but for AI prompts. Important to understand i...
R
RAG(Retrieval-Augmented Generation)
A technique that gives AI access to external data (documents, databases) at query time. Instead of relying only on training data, the model retrieves ...
Rate Limit
A cap on how many API requests you can make in a given time period. Prevents abuse and ensures fair access. If you hit one, you need to slow down or u...
RLHF(Reinforcement Learning from Human Feedback)
A training technique where humans rate AI outputs, and the model learns to produce responses humans prefer. It's why modern AI feels more helpful and ...
S
SDK(Software Development Kit)
A collection of tools, libraries, and documentation that makes it easier to build with an API. The Anthropic SDK lets you use Claude in your Python or...
Skill
A multi-step workflow an agent knows how to execute by chaining tools together. "Deploy a website" is a skill (read files → build → deploy → verify). ...
Subagent
A secondary AI agent spawned by a primary agent to handle a specific subtask. Like delegating work to a team member. Multiple subagents can run in par...
System Prompt
Hidden instructions given to an AI that set its behavior, personality, and rules before the user starts chatting. It's the difference between "generic...
T
Temperature
A setting that controls how random or creative AI output is. Low temperature (0.0-0.3) = deterministic and focused. High temperature (0.7-1.0) = more ...
Token
The basic unit AI uses to process text. A token is roughly 3/4 of a word. "Hamburger" is 3 tokens. Tokens determine cost (you pay per token) and fit w...
Tokenization
The process of splitting text into tokens — the fundamental units an LLM processes. Different models use different tokenizers, so the same text can pr...
Tool Use
The ability of AI to call external functions — search the web, read files, run code, access APIs. This is what separates agents from chatbots. Without...
Transformer
The neural network architecture behind all modern LLMs. Introduced in the 2017 paper "Attention Is All You Need." Uses attention mechanisms to process...
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