artificial general intelligence
A machine that can do anything that people can do, better than people.
The artificial general intelligence can do anything better than people.
agent operating model
The technical and organizational model for building, approving, monitoring, supporting, escalating, and improving agents after launch.
The agent operating model assigned support ownership before rollout.
adoption blocker
Anything that keeps users or sponsors from using the deployment in normal work: trust, data quality, UX friction, unclear ownership, policy, incentives, or a missing integration. Usually not accuracy.
The adoption blocker was not accuracy; it was that users had to copy the answer into another system.
system of record
The authoritative system for a type of business data. Matters for write-back: the FDE needs to know which system wins when there's a conflict.
The CRM was the system of record for account status.
ontology-backed workflow
A workflow built on a governed object model so actions, permissions, and context align with the customer's actual business entities — not arbitrary database rows.
The ontology-backed workflow let the agent update an asset, not just a row in a table.
operator
Generally, an agent (human or machine) that "runs" (monitors and delivers using) any other thing or system.
Some people ran printed presses in the 1900s so people could get their newspapers, and some software agents ran slide deck creation in the 2020s so people could get their presentation material; both kinds entities were an operator in their own way.
sub-agent
A smaller specialized agent or model role used inside a larger agent workflow to handle a specific task.
The sub-agent handled policy lookup while the main agent drafted the answer.
adoption workflow
A workflow design that makes the new capability part of normal work instead of an optional side tool users have to remember to visit.
The adoption workflow put the AI summary inside the ticket review screen.
deployment pattern
A repeatable way to get a class of customer use cases into production — architecture, rollout, common blockers, support model — documented after the third similar launch.
The FDE documented the deployment pattern after the third similar launch.
enterprise AI deployment
Deploying AI into an enterprise environment with production controls: SSO, permissions, audit, data governance, monitoring, support, and change management all required.
The enterprise AI deployment needed security review before users could upload customer data.