Glossary

Short definitions for every term used in the workshop.

Agentic coding

A style of software development where an AI agent plans, edits, runs, and verifies code in a loop, with the human reviewing and steering rather than typing every line. The agent uses tools (file edits, shell, tests) and decides when each is needed. Contrasts with vibe coding, where the human prompts and the AI replies one shot at a time.

Antigravity

Google's AI IDE for agentic development. Built around an autonomous coding agent that can plan, edit files, run commands, and use MCP tools. Used as the primary editor in this workshop.

Cloud Run

Google Cloud's serverless container platform. You give it a container image and a port; it gives you a public HTTPS URL that scales from zero. Pay per request, no machines to manage. Used to host the workshop site.

Context (in AI/LLM sense)

Everything an LLM sees on a single turn: the user prompt, the system prompt, prior messages, tool results, and any files or documents pasted in. The model has nothing else to work with — anything outside the context is invisible to it. The art of working with LLMs is largely the art of choosing what goes into the context.

Context7

An MCP server that fetches up-to-date library documentation on demand. Lets an AI client query current API docs for libraries and frameworks instead of relying on its training data, which is often months or years out of date.

Gem / Gemini Gem

A reusable Gemini configuration with a fixed system prompt and optional grounding. Think of it as a saved chatbot persona you can call repeatedly. The workshop uses a Gem to interview students and produce persona.json.

Gemini

Google's family of multimodal foundation models, plus the consumer chat product at gemini.google.com. In this workshop "Gemini" usually means the model family available through Vertex AI or the Gemini app.

Hallucination

When an LLM produces output that sounds confident and plausible but is factually wrong — a fake API, a non-existent function, a made-up citation. Hallucinations are the main reason agentic coding still needs a human reviewer.

MCP (Model Context Protocol)

An open protocol for connecting AI clients to external tools and data sources. An MCP server exposes tools and resources; an MCP client (Claude Desktop, Antigravity, custom agents) calls them. The standard way to extend a coding agent with custom capabilities.See also: Build an MCP server

Model

In this workshop, a specific LLM you can call by name — e.g. gemini-2.5-flash or gemini-2.5-pro. Models differ in speed, cost, context window, and quality. Names drift; the model you used last quarter may be deprecated this quarter.

Persona JSON

The workshop's data file. A structured JSON document with your skills, projects, experience, and bio, produced by interviewing yourself with the Gemini Gem in step 3. Becomes the source of truth for the site's content and (in the bonus tracks) for the MCP server and chatbot.

Plugin

A bundle of skills, MCP servers, and config that extends a coding agent. In Antigravity / Superpowers, plugins are the unit of distribution — install one plugin and you get the skills and tools that come with it.

Prompt

The text you give an LLM to elicit a response. Includes the system prompt (instructions for the model's role) and the user prompt (the actual question or task). Prompt engineering is the practice of writing prompts that produce reliable output.

Skill (Superpowers/Antigravity sense)

A documented, triggerable capability the agent loads on demand. A skill bundles instructions, examples, and sometimes scripts. The agent picks skills based on the user's intent and runs them with full context. Different from a tool: skills tell the agent how to think; tools let it do things.

Stitch

Google's AI design tool for sketching app and site layouts from a prompt. Used in step 2 to produce the visual direction for your career site before any code is written.See also: Design with Stitch

Subagent

A second AI agent invoked by the primary agent for a focused task in a clean context. Subagents are how the orchestrator delegates: "go review this PR", "go run the tests and report". They isolate context so the parent doesn't get polluted with intermediate noise.

Superpowers

The agentic coding framework used in this workshop. Provides a skill priority system, a library of skills (TDD, planning, code review, debugging, etc.), subagent orchestration, and conventions for how a coding agent should behave. Built to run inside Claude Code and Antigravity.

TDD

Test-driven development. Write a failing test, write the minimum code to make it pass, refactor, repeat. In agentic coding TDD is doubly useful: tests are how the agent knows it's done, and how you keep it honest about whether code actually works.

Vertex AI

Google Cloud's managed platform for ML and generative AI. The way to call Gemini from a Google Cloud project with proper IAM, billing, and quotas. Used in the bonus chatbot step.See also: Add a chatbot

Vibe coding

Coined by Andrej Karpathy. Coding by prompting an LLM, accepting whatever it spits out, and shipping if it seems to work. Fast, fun, and fragile. The starting point most people experience before moving to agentic coding with structure, tests, and review.