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AI agent glossary
Plain-language definitions for agents, governance, memory, and company OS patterns — from the team building Neuro OS.
Foundations
What are AI guardrails?
AI guardrails are runtime policies that constrain what a model or agent can output or do — blocking unsafe content, PII leaks, prompt inject…
What is an embedding?
An embedding is a dense vector representation of text, image, or other data — numbers that capture semantic meaning so similar concepts sit …
What is a context window?
A context window is the maximum amount of text (tokens) a model can consider in one request — prompt, retrieved documents, tool results, and…
What is a heartbeat agent?
A heartbeat agent wakes on a schedule or event and runs defined work without a human prompt — daily briefs, inbox sweeps, weekly reports. He…
What are long-horizon agents?
Long-horizon agents pursue goals that span hours, days, or weeks — planning, executing, checkpointing, and resuming across sessions. They ne…
What is a multi-agent system?
A multi-agent system coordinates several specialized agents — research, write, review, send — with routing, shared context, and governance. …
What is a one-person company?
A one-person company is a business where a single founder operates with AI agents filling operational roles — marketing, support, finance, e…
What is a skill marketplace?
A skill marketplace is a catalog of pluggable capabilities agents install — SEO audits, unit economics, compliance checks. A skill packages …
What is a vector database?
A vector database stores embeddings and retrieves nearest neighbors by semantic similarity — the retrieval layer behind RAG, agent memory, a…
Agentic AI explained
Agentic AI systems plan, execute, and self-correct across multi-step tasks using tools, memory, and reasoning loops — taking actions in the …
What is agentic commerce?
Agentic commerce is shopping and checkout mediated by AI agents — discovering products, comparing offers, and purchasing on behalf of users …
What is agent evaluation?
Agent evaluation measures whether an agent role performs acceptably — with test cases, rubrics, regression runs, and production sampling — b…
Agent operations
What is agent accountability?
Agent accountability ensures every agent action is traceable, auditable, and owned — logged with role identity, inputs, decision, outcome, a…
What is an agent communication protocol?
An agent communication protocol defines how roles hand off work — message shape, required context, status fields, and escalation paths — so …
What is agent context sharing?
Agent context sharing is how roles access the same business truth — customer record, sprint goal, brand skill — without copying secrets into…
What is agent cost optimization?
Agent cost optimization balances model choice, context size, heartbeat frequency, and tool calls so roles deliver accepted work per dollar —…
What is agent cross-training?
Agent cross-training shares skills, eval sets, and connector patterns across roles so improvements compound — fixing support triage helps on…
What is agent failure recovery?
Agent failure recovery is how roles resume after tool errors, model timeouts, bad outputs, or human rejection — with checkpoints, retries, f…
What is the agent lifecycle?
The agent lifecycle covers design → eval → deploy → operate → improve → retire for each role — like software, not a one-time prompt. Skills …
What is agent on-call?
Agent on-call is the human + automation rotation when agent workloads need live response — incident triage, Ask queue backlog, connector out…
What is agent output verification?
Agent output verification checks work products against rubrics — schema, citations, brand, numeric sanity — before or after human review. It…
What is agent oversight?
Agent oversight is the human management layer for AI roles — owners, review queues, metrics, autonomy levels, and periodic audits — ensuring…
What is agent parallel execution?
Agent parallel execution runs multiple subtasks or roles concurrently — research ten accounts, score ten tickets — with concurrency limits, …
What is an agent retrospective?
An agent retrospective reviews a period of agent operations — what shipped, what failed, correction categories, spend, and skill changes — t…