Agent Loop
The agent loop is the core operating cycle of an autonomous AI agent. It runs continuously through four phases: Perception (gathering information), Reasoning (planning the next step), Action (executing — such as calling a tool or generating content), and Observation (evaluating the result). The loop repeats until the task is complete or the agent requires human input. This is the mechanism behind Agentic AI systems — it is what allows agents to handle complex, multi-step tasks that a single prompt-and-response model could not.
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Recall Questions
Recall questions ask participants to retrieve and state information they have previously learned or been told. They test memory and knowledge retention rather than understanding or analysis. In training sessions and educational presentations, recall questions at the end of a segment can reinforce key points and check how much the audience has absorbed. While they don't assess deeper comprehension, they are an efficient tool for checking baseline knowledge and reinforcing core facts.
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Slide Sorter view
The Slide Sorter view in PowerPoint shows thumbnails of all your slides in horizontal rows.The view is useful for applying global changes to several slides at once. Also it's useful for deleting and rearranging slides.
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Autonomous Agent
An autonomous agent is an AI system that independently pursues goals, makes decisions, and executes tasks over time — without requiring continuous human direction. What distinguishes an autonomous agent from a simple automation script is its ability to reason, adapt to new information, and handle unexpected situations. Autonomous agents track progress toward a goal across multiple steps and sessions, making them suitable for complex enterprise workflows such as automated reporting, content updates, and communication management.
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