Task Decomposition
Task decomposition is the process by which an AI agent breaks down a complex, high-level goal into a sequence of smaller, manageable subtasks. The agent identifies dependencies between steps, determines what tools or data each step requires, and decides which subtasks can run in parallel. Task decomposition is a fundamental capability of Agentic AI systems and is central to how an agent loop executes multi-step workflows reliably.
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Massive Open Online Course (MOOC)
Massive open online courses (MOOCs) are large-scale online courses accessible to anyone with an internet connection, often free of charge. MOOCs are delivered through platforms such as Coursera, edX, or Udemy and can attract thousands of learners simultaneously. They typically combine video lectures, readings, quizzes, and discussion forums. MOOCs have democratized access to university-level education and professional skill development worldwide.
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AI Agent
An AI agent is a software system that perceives its environment, reasons over context, and autonomously takes actions to achieve a defined goal — without requiring a human to trigger each individual step. Unlike a chatbot that responds to a single prompt, an AI agent plans, executes multi-step tasks, uses tools, and adapts based on the results it observes. AI agents can operate independently or as part of larger multi-agent systems, and are increasingly embedded in enterprise software to automate complex workflows across departments.
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WWTBAM
Who Wants to Be a Millionaire (WWTBAM) is a popular television quiz format that has been widely adapted as a game-based learning tool in presentations, training sessions, and classroom settings. Participants answer multiple-choice questions with progressively higher stakes, using lifelines for help. Its competitive, high-stakes structure creates engagement and tests knowledge retention in a memorable, entertaining way. Many presentation tools support WWTBAM-style quiz templates directly.
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