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AI agents are autonomous or semi-autonomous systems that make decisions, pursue goals, and perform actions.
An AI agent, also called agentic AI, is an artificial intelligence program that can make decisions, pursue goals, and take actions with limited direct human control. Unlike tool-like AI systems designed for narrow, single-step tasks, AI agents can typically interact with their environment, use external tools, and autonomously complete multi-step tasks. There is no universally accepted definition, but goal-directed autonomy and the ability to act are central concepts. AI agents are often controlled by large language models and supported by components such as memory, planning logic, tool interfaces, execution state, permissions, and orchestration software. An agent harness connects the model to resources such as databases, files, browsers, APIs, and command-line tools while managing context and constraints. Agents may operate individually or as coordinated multi-agent systems, using workflows such as prompt chaining, routing, parallelization, sequential processing, and planner-critic loops.
AI agents are autonomous or semi-autonomous systems that make decisions, pursue goals, and perform actions.
Common characteristics include goal-directed behavior, external tool use, environmental interaction, and multi-step task execution.
Large language models frequently drive an agent's control flow, while memory, planning, tool interfaces, and execution management provide supporting capabilities.
An agent harness or scaffold connects the AI model to software, data, hardware, and online services while controlling permissions, context, and operational constraints.
Agent orchestration coordinates multiple agents or workflow stages to produce more coherent and effective results than isolated agents working independently.
An artificial intelligence program that can independently make decisions, pursue goals, and take actions.
AI designed to operate with a degree of autonomy by planning and carrying out actions toward specified goals.
The ability of an agent to select and perform actions intended to achieve a desired objective.
The software layer surrounding an AI model that manages prompts, context, memory, tools, execution state, permissions, and constraints.
Software, services, databases, browsers, APIs, or other resources that an agent can access to complete tasks.
The coordination of multiple AI agents or task stages to achieve a coherent overall result.
The ability to plan and complete a sequence of related actions rather than responding with a single isolated output.
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