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Glossary

Vocabulary, defined.

Plain-English definitions of the AI terms operators actually need. We define what we mean so the audit conversation moves faster.

AI employee
An autonomous AI agent trained on your specific business processes that owns a closed loop end-to-end and is integrated into the channels your team already uses.
Closed loop
A workflow where AI handles the full cycle — input, decision, action, learning — without human intervention except at hard rule-based escalation points.
Open loop
A workflow where AI assists a human at one step but the human is still in the path on every transaction. AI as typing assistant, not operator.
Queryable company
A company where every artifact (meetings, emails, WhatsApp threads, CRM, Stripe data) is accessible to the agent, allowing it to take initiative across systems instead of being tool-limited.
Memory layer
The substrate where company-specific data lives so an AI agent can learn the patterns of your business and improve over cycles. Notion, Obsidian, Google Drive, or markdown all qualify.
Voice mirroring
Training an AI agent on your team's actual past communications (sent emails, Slack threads) so its outputs sound like you, not like a generic chatbot.
AEO (Answer Engine Optimization)
Optimizing content to be cited by LLMs (ChatGPT, Claude, Gemini) when users ask questions. The AI-era replacement for keyword-stuffing SEO.
Agentic AI
AI systems that take actions in the world — calling APIs, sending emails, updating systems — not just generating text.

Skip the vocabulary lesson. Audit your stack.