A workflow where content is edited directly in the context of the live page layout rather than in a separate form view. This improves editorial speed and reduces context switching.

AGENTS.md is a project instruction file that gives AI coding agents task context, workflow rules, and constraints so agent behavior aligns with team standards.

Subagents are narrowly scoped AI assistants that can be invoked by a primary agent to perform specific subtasks more efficiently.

Hooks are automation points tied to lifecycle events that let teams enforce checks, trigger scripts, or modify behavior around agent actions.

Slash Commands are user-invoked commands that start with a slash and execute predefined workflows, tools, or agent behaviors.

Approval Modes are policy settings that control which operations an agent can run automatically and which require explicit human approval.

Non-interactive Mode executes agent workflows in a command-driven context without live chat interactions, useful for automation and pipelines.

Agent Memory is persisted context that allows an AI agent to remember preferences, facts, and workflow state across sessions.

A broad category covering any workflow where AI tools—from inline autocomplete to autonomous agents—collaborate with developers. The human retains control over architecture and review while AI handles repetitive patterns, boilerplate, and first drafts. AI-assisted development spans a spectrum from single-line suggestions to full feature generation, and is closely related to vibe coding, code completion, and agentic coding.

A canvas agent is an AI assistant that edits, refines, and structures a website directly on the design canvas while keeping the work editable.

In AI-assisted website creation, canvas agent helps teams move faster without losing control of structure, content, performance, or editable design details.

An external agent is an AI tool outside Framer that connects to a project to inspect, update, or automate site work through an agent bridge.

In external AI agent workflows, external agent helps teams move faster without losing control of structure, content, performance, or editable design details.

An agent bridge is the connection layer that lets an outside AI tool access a Framer project, including pages, components, and CMS content.

In external AI agent workflows, agent bridge helps teams move faster without losing control of structure, content, performance, or editable design details.

An agent skill is an installed capability or command that lets an AI agent perform project-specific actions, such as connecting to Framer or editing a site.

In external AI agent workflows, agent skill helps teams move faster without losing control of structure, content, performance, or editable design details.

An agent handoff is the transfer of context, files, or tasks from one AI agent to another so work can continue without losing project intent.

An agent handoff keeps a workflow moving when a task needs a different tool, model, or specialist. In Framer, this can mean passing site context from a design-focused agent to a coding or CMS-focused agent while preserving the user’s goals and constraints.

Agent permissions define what an AI agent is allowed to read, edit, create, publish, or automate inside a project.

Agent permissions help teams control risk when using AI. A project may allow an agent to edit CMS content, inspect pages, or create branches, while reserving publishing, production changes, or destructive edits for human approval.

An agent audit trail is a record of AI-assisted changes, decisions, and updates that helps teams review what happened in a project.

An agent audit trail makes AI work accountable. It can include changed content, branch activity, review notes, or publishing history so teams can understand what was edited and roll back or refine work when needed.

An agent branch is a separate working version of a project where AI-made changes can be reviewed before they affect the main site.

An agent branch protects the live project by isolating AI edits. Teams can preview the result, compare changes, request revisions, and merge only when the work is ready.

An agent trigger is an event or command that starts an automated AI action, such as updating content or checking a project.

Agent triggers can be manual, scheduled, or connected to outside systems. In a website workflow, a trigger might start a content import, run a QA pass, or ask an agent to update CMS entries after source data changes.

Agent QA is the use of an AI agent to find and help fix issues such as broken links, duplicate content, missing metadata, or inconsistent layout.

Agent QA supports quality assurance by scanning project content and structure for problems. It is most useful when paired with human review, especially before merging a branch or publishing a site.

An agent-orchestrated workflow coordinates multiple AI actions, tools, or agents to complete a larger project task.

Agent-orchestrated workflows are useful for multi-step site work such as scanning pages, creating CMS entries, adding links, reviewing changes, and preparing a branch for approval. The orchestration keeps each action aligned with the overall goal.