"One page, the whole vocabulary. Once these feel familiar, Spring AI docs and tutorials read like plain English."
Level: Reference · Time: ~browse · Prerequisites: none
Learning Objectives
By the end of this module, you will be able to:
- Recognize the key terms used across this track
- Explain each in simple language
- Use this page as a quick reference
Try this: Skim the tables now, then come back whenever a term trips you up mid-project. Reading the plain-meaning column out loud is a fast way to lock a concept in — most of these will click after you've built with them once.
Java & Spring
The foundation everything else rests on — the language that runs on the JVM, the Spring Boot framework that wires your app together, and the Maven tooling you met back in Modules 1–3.
| Term | Plain meaning |
|---|---|
| JVM | The engine that runs compiled Java on any OS |
| Class / method | A blueprint / an action it can perform |
| Spring Boot | Framework that removes Java setup boilerplate |
| Bean | An object Spring creates and manages for you |
| Dependency injection | You ask for objects; Spring provides them |
| Annotation | An @ label telling Spring how to treat code |
Maven / pom.xml | Build tool / file listing your dependencies |
application.yaml | Config file (model names, endpoints, keys) |
Spring AI Core
The handful of Spring AI types you'll touch in almost every project. If a class name in the code samples looks unfamiliar, this is the first table to check.
| Term | Plain meaning |
|---|---|
| Spring AI | Building blocks for adding AI to Spring apps |
| ChatModel | The low-level connection to an AI model |
| ChatClient | The friendly, fluent API you use most |
| Advisor | A plug-in that wraps each call (memory, RAG) |
| PromptTemplate | A reusable prompt with {variable} slots |
| Starter | A dependency that auto-configures a provider |
.entity(Type.class) | Parse the reply into a typed Java object |
AI & Prompting
Vocabulary that applies to any AI model, not just Spring AI. Knowing these words makes provider documentation and blog posts far easier to follow.
| Term | Plain meaning |
|---|---|
| Token | A small chunk of text (~¾ word) the model processes |
| Context window | How much text the model can consider at once |
| Prompt engineering | Designing input to get better output |
| Zero-shot / few-shot | No examples / a few examples in the prompt |
| Chain of thought | Asking the model to reason step by step |
| Hallucination | A confident but false answer |
| Stateless / stateful | Forgets each turn / remembers the conversation |
Memory & RAG
Terms for giving a model a memory and grounding it in your own documents — the ideas behind Modules 5 and 8–10.
| Term | Plain meaning |
|---|---|
| ChatMemory | Stores conversation history |
| MessageWindowChatMemory | Keeps the last N messages (sliding window) |
| Conversation ID | Keeps each user's chat separate |
| RAG | Retrieve your docs, then answer from them |
| Chunk | A small piece of a split document |
| Embedding | Text turned into meaning-capturing numbers |
| Vector store | Database of embeddings for similarity search |
| Cosine similarity | Score of how "aligned" two meaning-vectors are |
| QuestionAnswerAdvisor | One-line RAG built into ChatClient |
Tools, MCP & Agents
The language of action — letting a model call your code, reach external systems over MCP, and coordinate multi-step work, as covered in Modules 11–14.
| Term | Plain meaning |
|---|---|
| Tool | A function the model can call to act |
@Tool / @ToolParam | Annotations that define an in-app tool |
| ReAct | Reason → Act → Observe → repeat loop |
| Tool chaining | The model calls several tools in one turn |
| MCP | Open standard to connect AI to external tools |
@McpTool | Exposes a tool on an MCP server |
| ToolCallbackProvider | Client helper that discovers/calls MCP tools |
| Agentic workflow | Multiple orchestrated LLM calls |
| Chain / Routing / Evaluator-Optimizer | Three of the five agentic patterns |
Key Takeaway: These terms span the whole track — Java and Spring basics, Spring AI's core (ChatClient, advisors, templates), prompting, memory, RAG, tools, MCP, and agentic patterns. Bookmark this page as your quick reference while you build.
Further Learning
Part of "Spring AI for Beginners." Terms adapted from Microsoft's open Spring AI curriculum (MIT License).