AI Agents Glossary
Your practical reference for AI agent terminology. Use this glossary to align teams on definitions, architecture choices, and implementation patterns.
How to Use This Glossary
If you are evaluating tools, start with foundational terms before diving into framework comparisons. If you are building production workflows, prioritize terms tied to architecture and reliability decisions.
- Start with definitions to align language across product, engineering, and operations.
- Use linked tutorials to translate terms into implementation steps.
- Use linked comparisons and reviews to map concepts to platform tradeoffs.
- Use related terms to build a structured learning path instead of isolated reading.
Suggested Learning Paths
Beginner Path
Read AI Agents, Agentic AI, and Tool Calling, then continue with Build Your First AI Agent.
Architecture Path
Focus on AI Agent Memory, AI Agent Orchestration, and AI Agent Guardrails, then review AI Agent Architecture.
Platform Decision Path
Read Multi-Agent Systems and LLM Agents, then compare options in Best AI Agent Platforms.
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What Is Agent-as-a-Service (AaaS)?
Agent-as-a-Service (AaaS) is a deployment model where pre-built AI agents are delivered as managed cloud services, letting organizations access age...
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What Is Agentic AI?
A practical guide to agentic AI, including its decision loop, autonomy boundaries, orchestration patterns, and production implementation criteria.
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What Is AI Agent Evaluation?
A practical guide to AI agent evaluation — how to measure agent quality across task completion rate, accuracy, latency, and cost.
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What Is AI Agent Hallucination?
A clear explanation of AI agent hallucination — why hallucinations are especially dangerous in agents, grounding techniques, using RAG as mitigatio...
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What Is AI Agent Memory?
A practical explanation of AI agent memory, including short-term state, long-term memory stores, retrieval design, and quality control patterns.
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What Is AI Agent Orchestration?
Understand AI agent orchestration, including workflow control, task routing, state transitions, and reliability patterns for production systems.
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What Is AI Agent Planning?
A practical guide to AI agent planning — how agents decompose goals into subtasks, the difference between plan-and-execute and ReAct approaches, Tr...
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What Is an Agentic Workflow?
An agentic workflow is an automated process where an AI agent makes decisions, uses tools, and adapts its actions at runtime rather than following...
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What Is an AI Agent Framework?
A clear explanation of AI agent frameworks — what software libraries like LangChain, CrewAI, AutoGen, and LangGraph provide, the difference between...
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What Is Chain-of-Thought Reasoning?
A clear explanation of chain-of-thought prompting — how it improves AI agent accuracy through step-by-step reasoning, the difference between zero-s...
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What Is Fine-Tuning for AI Agents?
A clear explanation of fine-tuning for AI agents — when to fine-tune versus using RAG or prompt engineering, data requirements, RLHF versus SFT, co...
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What Is Function Calling in AI?
A complete explanation of function calling in AI — how LLMs invoke structured tools via JSON schema, the difference between OpenAI function calling...
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Frequently Asked Questions
Who should use this AI agents glossary?
This glossary is built for operators, product managers, developers, and business teams who need practical definitions tied to implementation decisions, not just dictionary-style summaries.
How should I read glossary terms if I am new to AI agents?
Start with foundational terms such as AI Agents, Agentic AI, and Tool Calling, then move to architecture topics like Memory, Orchestration, and Guardrails before comparing specific frameworks.
Are glossary pages connected to tutorials and comparisons?
Yes. Every glossary term includes internal links to related tutorials, comparisons, reviews, and templates so you can move from concept to implementation quickly.
How often are glossary terms updated?
Glossary entries are reviewed as platform patterns evolve, especially for orchestration, retrieval, memory, and governance topics where implementation standards change quickly.