Glossary
Key terms explained in plain language.
Agent Orchestration
An operating approach that coordinates multiple AI agents and tools under shared routing and control policies
Agentic Coding
A development style where AI agents handle multi-step coding tasks beyond simple code completion
AGI (Artificial General Intelligence)
A hypothetical AI system capable of performing any intellectual task a human can
AI Agent
An autonomous AI system that can plan, use tools, and take actions to achieve goals
AMR (Autonomous Mobile Robot)
A mobile robot that plans and adjusts its own routes using sensor-based environmental awareness
Anticipatory UI
An interface pattern that predicts likely next actions from user context before explicit commands
Attention
A mechanism that allows AI models to focus on the most relevant parts of the input when producing output
AX (AI Transformation)
An organizational shift that embeds AI into workflows, decision-making, and service operations
Chunk
A text segment created by splitting long documents into meaningful units for retrieval and generation
Claude Code
Anthropic's terminal-based CLI coding agent for autonomous development tasks
Claude Opus
Claude's top-tier model family optimized for deep multi-step reasoning and high-stakes analysis
Claude Sonnet
Claude's practical model family optimized for speed, cost efficiency, and strong day-to-day quality
Co-work
A collaboration pattern where humans and AI split roles to complete work together
Cobot (Collaborative Robot)
A safety-focused industrial robot designed to work in shared spaces with human operators
Context Window
The maximum number of tokens a model can process in a single request
Cursor
An AI-first IDE built on VS Code that supports multi-file editing and agentic coding workflows
DeepSeek
An AI model/research organization known for open-source LLM releases and strong cost-performance pressure on closed API markets
Diffusion Model
A generative AI model that creates data by learning to gradually remove noise from random static
Edge AI
Running AI models directly on local devices instead of in the cloud
Embedding
A way to represent words and concepts as numerical vectors
Fine-tuning
The process of further training a pre-trained AI model on a specific dataset to specialize its capabilities
Gemini
Google DeepMind's multimodal generative AI model family
GitHub Copilot Agent
A GitHub-integrated coding agent that executes multi-step tasks in issue and pull request workflows
GPT (Generative Pre-trained Transformer)
A family of large language models by OpenAI that generate text by predicting the next token
Hallucination
When an AI model generates plausible-sounding but factually incorrect or fabricated information
Human-in-the-loop
An operating principle where humans review or approve AI actions at critical decision points
Intent-based UX
A UX pattern where users express goals and the system assembles the execution flow
LLM (Large Language Model)
A massive AI model trained on vast amounts of text data
LoRA (Low-Rank Adaptation)
An efficient fine-tuning technique that adapts large AI models using a small number of trainable parameters
Lost in the Middle
A long-context failure mode where mid-document information is underused compared with beginning or end segments
MLOps
A set of practices for deploying, monitoring, and maintaining machine learning models in production
MoE (Mixture of Experts)
A model architecture that activates only selected experts per input to improve cost-performance efficiency
Multimodal
AI systems that can understand and generate multiple types of data like text, images, and audio
Physical AI
AI systems that perceive the real world through sensors and execute tasks through physical action
Prompt
The input text or instruction given to an AI model to guide its response
RAG (Retrieval-Augmented Generation)
A technique that enhances LLM responses by retrieving relevant external information before generating an answer
Rate Limiting
A control method that caps API request volume over a time window to protect stability and cost
RLHF (Reinforcement Learning from Human Feedback)
A training method that aligns AI behavior with human preferences using human evaluators
SaaS (Software as a Service)
A delivery model where software is provided as a cloud subscription instead of local installation
Sovereign AI
An AI operating strategy where an organization or nation keeps direct control over data, models, and infrastructure
Token
The smallest unit of text that AI processes
Transformer
A neural network architecture that revolutionized AI by processing sequences with self-attention mechanisms
Vector Database
A specialized database designed to store and search high-dimensional vector embeddings efficiently
Vertex AI
Google Cloud's unified platform for enterprise machine learning and generative AI
Vibe Coding
A rapid development style that uses AI coding assistants in short generate-run-fix loops
VPC Service Controls
A Google Cloud security feature that enforces data perimeters around managed services
Zero-shot / Few-shot Learning
Techniques that allow AI models to handle new tasks with little or no example data
Zero-UI
An interaction model that minimizes screen controls and relies on voice, gesture, or sensor input