The Glossary
200 terms across 17 areas. The shared technical vocabulary that AI coding assistants like Claude Code, Cursor, and Replit Agents expect you to know — written for people building with AI without a traditional software engineering background.
AI & Prompt Engineering
21How AI models work and how to get better answers out of them
Architecture
14How big systems are designed to stay fast, reliable, and easy to grow
Automation & Scripting
9How to make computers do repetitive work for you with scripts and scheduled tasks
Backend & APIs
15How apps talk to servers and store information behind the scenes
Data & Transformation
9How raw data gets cleaned, reshaped, and turned into something useful
Debugging & Error Handling
9How to describe, reproduce, and communicate bugs so they get fixed fast
Design with MCP
8Driving AI design tools through MCP — Figma, Stitch, Penpot, and the design-to-code workflow
DevOps & Deployment
14How software gets packaged, launched, and kept running in the real world
Frontend & Responsive Design
14How webpages adapt to phones, tablets, and screens of every size
Git & Collaboration
14How teams keep track of changes and work on the same project at once
GTM & Business Tools
10The SaaS platforms, data tools, and business concepts that GTM engineers automate every day
MCP for Productivity
8Driving productivity tools through MCP — Gmail, Calendar, Drive, Slack, Notion, and Linear — to triage, schedule, and chain real work
Programming Basics
4The core building blocks of code: variables, functions, parameters, and more
Prompt Engineering Basics
8How to write clear, specific instructions that get better results from AI coding tools
React & Frontend
15How modern websites and apps are built from reusable building blocks
Security
14Common attacks on websites and the everyday defenses that stop them
Testing & Quality
14How teams make sure software works, and keeps working, as it changes