AB-410 key terms

A software component that combines a language model with instructions, knowledge, and tools to interpret a request, decide what to do next, and carry out multi-step tasks with limited human supervision.

An agent that plans and executes steps toward a goal without a person approving each action, typically started by an event or schedule rather than by a live chat message.

An agent built to interact with people in natural language through a chat or voice interface, responding turn by turn and often handling questions, routing, and simple transactions.

The written guidance that tells an agent who it is, what it should and should not do, and how it should respond. It shapes behavior on every turn of a conversation.

A connected store of content such as documents, websites, or business records that an agent can search to answer questions beyond what the underlying model already knows.

Supplying an agent with retrieved, verifiable content at answer time so its response is anchored in approved sources instead of relying only on what the model memorized during training.

A pattern in which the system first searches an index for relevant passages, then passes those passages to the language model so it can compose an answer based on them.

Agent responses composed by a language model from retrieved sources at runtime, as opposed to replies that were scripted in advance for a fixed conversation path.

A defined conversation path in a low-code agent builder, made of trigger phrases, questions, conditions, and messages, used for scenarios that need predictable authored behavior.

An example utterance or keyword that tells an agent which authored topic a user's message most likely matches, so the correct conversation path starts.

The underlying goal or meaning behind a user's message, which an agent tries to identify so it can choose the right topic, action, or answer.

A capability an agent can invoke to do something beyond talking, such as creating a record, sending a message, or calling an API. It is usually described to the model with a name and inputs.

A prebuilt adapter that lets Power Platform components talk to an external service, wrapping its API and authentication so agents and flows can read or write data.

An automated or scheduled workflow that runs steps across services. Agents call flows to perform business operations that are too complex or too sensitive for a single action.

Transferring a conversation from an agent to a human representative or another system when the agent cannot help, when confidence is low, or when policy requires a person.

The deliberate routing of a request to a higher tier of support or authority, such as a person, a queue, or a supervisor, after the agent recognizes the limits of its ability.

The default behavior when an agent cannot match a request to a topic or produce a confident answer, such as asking for clarification or offering to transfer the user.

A design in which a coordinating agent breaks a request into subtasks, delegates them to specialized agents, and then combines their results into a single response for the user.

A separate agent that a parent agent can call as a skill, letting different teams build and own narrow capabilities that are reused across many experiences and channels.

A surface where an agent is published and reachable, such as a website, Teams, a contact-center platform, or a messaging app. Each channel can affect formatting, identity, and authentication.

The process of verifying who a user or calling system is before an agent grants access. It determines whether personal data and privileged actions are available in a conversation.

A control pattern in which a person reviews, approves, or corrects an agent's proposed action before it takes effect, used for high-impact or irreversible steps.

Microsoft's low-code authoring tool for building, testing, and publishing agents that combine topics, generative answers, knowledge sources, actions, and channels.

Microsoft's assistant embedded in Microsoft 365 apps that uses organizational content the signed-in user already has permission to see in order to draft, summarize, and answer questions.

Microsoft's cloud data platform beneath Power Platform, storing business data in secured tables that agents, apps, and flows can query and update as part of a solution.

Choosing which language model an agent uses for a given task, balancing answer quality, response latency, running cost, and data-handling requirements.

An attack in which malicious text inside content the agent reads, such as a document, email, or web page, tries to override its instructions or trigger unintended actions.

Automated screening of agent inputs and outputs to block harmful, unsafe, or disallowed material, usually configured with severity thresholds for each category of content.

A set of principles and practices covering fairness, reliability, privacy, inclusiveness, transparency, and accountability that is applied to how AI systems are designed, evaluated, and operated.

Adversarial testing in which people deliberately try to make an agent fail, leak data, or produce harmful output, so weaknesses are found before real users find them.

A fixed collection of representative questions, edge cases, and expected answers used to measure an agent's accuracy and to catch regressions after any change.

The repeatable process of scoring agent responses against defined criteria such as accuracy, groundedness, tone, and safety, so that changes can be compared on evidence rather than impression.

Usage and performance data an agent emits, such as session counts, resolution rate, latency, and error rates, used to monitor health and demonstrate business value.

The stored record of messages exchanged in a session, used for quality review, debugging, and compliance. It often contains personal data and therefore needs retention and access rules.

A container in Power Platform that holds apps, flows, agents, and data. It is used to separate development, testing, and production and to scope security and policies.

A package that carries Power Platform components such as agents, flows, tables, and connection references from one environment to another as a single versioned unit.

The discipline of moving a solution through development, test, and production using version control, automated deployment, and controlled releases rather than manual edits.

Rules that classify connectors as business, non-business, or blocked, preventing an agent or flow from moving data between categories that should not be mixed.

Granting an agent, user, or service only the permissions needed for its specific job, which limits the damage if credentials are misused or an action is manipulated.

A non-human identity with its own credentials and permissions, used so an agent or automated flow can call services without depending on an individual person's account.