Concepts
The vocabulary, defined.
One canonical definition per concept — the terms 95% works in, stated precisely enough to be quoted.
What is an AI-native organization?
An AI-native organization is one that doesn't add AI as a tool but runs on it: people, AI, and knowledge operate in one environment, and every AI action carries identity, ownership, and a record. AI-native is not a feature of the org chart — it is how the company executes.
Read the definitionWhat is an AI worker?
An AI worker is an AI agent that has been given identity, memory, permissions, and an audit record — an employee, not a tool. Where a bare agent executes tasks, an AI worker holds a role: it is hired for a scope, remembers every prior interaction, acts only within its permissions, and answers for everything it does.
Read the definitionWhat is the AI Accountability Ledger?
The AI Accountability Ledger is the append-only record of every AI action across an organization: what ran, in which department, under whose ownership — and whether it should have. Actions without an owner are surfaced; actions that shouldn't have run can be reversed. It is how growth answers for itself.
Read the definitionWhat is code-mode execution?
Code-mode execution is an approach where AI agents write code against a curated SDK inside an isolated sandbox instead of making dozens of brittle tool calls. One reviewed program replaces many round-trips — cutting token overhead while every run is permissioned, isolated, and sealed in a tamper-evident audit record.
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