Define the new internet.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
2,337 definitions
Memory Grounding Check is a ai quality control that verifies that generated answers are backed by available sources for persistent or session-level AI state. It uses citation checks, retrieval evidence, and contradiction detection so teams can reduce unsupported claims while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Memory Grounding Check when the assistant reused earlier project context, so the team could reduce unsupported claims before the agent workflow reached production.”
Memory Model Router is a ai selection service that chooses the best model or provider for a task for persistent or session-level AI state. It uses cost, latency, capability, policy, and fallback signals so teams can match work to the right model while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Memory Model Router when the assistant reused earlier project context, so the team could match work to the right model before the agent workflow reached production.”
Memory Tool Permission is a ai access control that decides which tools an AI workflow may call for persistent or session-level AI state. It uses operation allowlists, user intent checks, and protected-action gates so teams can block unsafe automation while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Memory Tool Permission when the assistant reused earlier project context, so the team could block unsafe automation before the agent workflow reached production.”
Memory Context Contract is a ai interface contract that defines what context may be passed into a model call for persistent or session-level AI state. It uses schemas, redaction rules, source labels, and token budgets so teams can keep model inputs relevant and safe while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Memory Context Contract when the assistant reused earlier project context, so the team could keep model inputs relevant and safe before the agent workflow reached production.”
Memory Instruction Boundary is a ai policy boundary that separates durable system instructions from user-provided content for persistent or session-level AI state. It uses role labels, precedence rules, and prompt assembly checks so teams can avoid instruction confusion while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Memory Instruction Boundary when the assistant reused earlier project context, so the team could avoid instruction confusion before the agent workflow reached production.”
Tool Call Citation Builder is a ai attribution helper that formats source links and evidence for an AI answer for model-triggered calls into software systems. It uses canonical URLs, source titles, and quote limits so teams can make generated answers citeable while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Tool Call Citation Builder when the assistant requested a protected operation, so the team could make generated answers citeable before the agent workflow reached production.”
Tool Call Human Approval is a ai control step that requires a person to approve sensitive or high-impact actions for model-triggered calls into software systems. It uses risk scoring, review UI, and audit logs so teams can keep protected decisions accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Tool Call Human Approval when the assistant requested a protected operation, so the team could keep protected decisions accountable before the agent workflow reached production.”
Tool Call Response Schema is a ai output contract that requires model output to match a known structure for model-triggered calls into software systems. It uses JSON schemas, validators, retries, and error reporting so teams can make responses machine-readable while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Tool Call Response Schema when the assistant requested a protected operation, so the team could make responses machine-readable before the agent workflow reached production.”
Tool Call Fallback Path is a ai resilience pattern that keeps an AI feature useful when a provider or tool is unavailable for model-triggered calls into software systems. It uses degraded states, deterministic responses, and operator notices so teams can avoid fake AI success while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Tool Call Fallback Path when the assistant requested a protected operation, so the team could avoid fake AI success before the agent workflow reached production.”
Tool Call Agent Trace is a ai observability record that captures the steps an AI workflow took for model-triggered calls into software systems. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.
“The AI platform team used Tool Call Agent Trace when the assistant requested a protected operation, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”