coding agent
An AI coding agent is a tool-using AI system that can inspect, modify, and validate software within a repository.
AI Terminology
Search clear AI terminology definitions, acronyms, related concepts and the reviewed videos that explain them.
Showing 1–20 of 1071 terms
Clear filtersagent skill
An AI agent skill is a reusable package of instructions, resources, and tool guidance for performing a bounded kind of work.
multi-agent system
MASA multi-agent system contains multiple AI agents that interact, coordinate, divide work, or influence one another while pursuing tasks.
benchmark
A benchmark is a standardized task or collection of tests used to compare AI systems under defined conditions.
agent permission boundary
An agent permission boundary limits the information, tools and actions an AI agent can use during a task.
frontier model
A frontier AI model is among the most capable general-purpose models available at a given time.
open-weight AI model
An open-weight AI model makes its learned parameter values available for others to download, inspect or run under a stated license.
human-in-the-loop AI
HITLHuman-in-the-loop AI keeps a person involved in reviewing, correcting, approving, or guiding an AI system's work.
workflow automation
Workflow automation uses software or AI to complete a connected sequence of routine steps with less manual effort.
agent
An AI agent is a system that observes context, decides what to do, and takes actions through tools to pursue a goal.
computer use
Computer use is an AI capability that interprets a graphical interface and operates software through actions such as clicking, typing, and selecting.
agent evaluation
Agent evaluation measures how well an AI agent performs intended tasks across defined, repeatable conditions.
agent observability
AI agent observability makes an agent's state, actions, tool use, failures, resource use, and outcomes visible enough to understand and operate it.
model routing
AI model routing sends each request to a model chosen for that request's complexity, cost, speed, privacy, or other requirements.
agent orchestration
Agent orchestration coordinates AI agents, tools, people, tasks, state, and control flow so a larger workflow reaches a verified outcome.
context engineering
Context engineering designs the information, instructions, memory, and tool state an AI receives so it can perform a task reliably.
feedback loop
An AI feedback loop occurs when AI outputs or their consequences become inputs that influence later model or agent behavior.
evaluation
Evaluation is the systematic process of testing and judging an AI system against defined tasks, evidence, and success criteria.
human-AI collaboration
Human-AI collaboration combines human judgment and accountability with AI speed, generation, analysis, and tool use in a shared workflow.
repository context
Repository context is the relevant source, configuration, history, documentation, dependencies, and worktree state needed to understand a software task.