What is AI Agent?
Turkish: AI Agent (Yapay Zeka Ajanı)
An AI agent is a software component that uses an LLM, tools, and data sources to plan steps and complete a defined goal.
What is AI Agent?
An AI agent is different from simply asking a model a question. It breaks a goal into smaller steps, chooses the right tool, checks the result, and decides whether another step is needed.
For example, a support agent can classify a customer request, check order status through an ERP or shipping API, retrieve the refund policy from a knowledge base, and draft a suggested answer for a human representative. In this setup, the LLM handles language understanding and planning, while tool calls connect the agent to real systems.
How It Works
A typical agent loop has four parts: interpret the goal, create a plan, call a tool, and use the observation to choose the next action. Tools can include an API, database query, file search, calendar action, or internal automation.
In production, memory, authorization, and audit logs matter. The design should define which data the agent may access, which actions it may perform automatically, and which steps require human approval.
Business Use
AI agents can support quote preparation, support triage, sales call summaries, document review, internal search, and operations tracking. When combined with RAG, the agent can ground answers in company documents instead of relying only on model knowledge.
The strongest implementations start with narrow, measurable tasks. Rather than giving an agent broad authority, teams need well-defined tools, clear failure handling, and traceable decision steps.
Related Terms
Agentic AI is an AI approach where systems plan tasks, use tools, and adjust their next steps instead of producing a single reply.
AI WorkflowAn AI workflow connects model calls, data steps, business rules, and human reviews into a repeatable automated process.
ChatbotA chatbot is a conversational interface that answers user requests through scripted flows, retrieval, or AI-generated responses.
HyperautomationHyperautomation combines RPA, AI, process mining, and integrations to automate end-to-end business processes across multiple systems.
LLM (Large Language Model)An LLM is a model trained on large text datasets that can understand and generate natural language, forming the basis of tools like ChatGPT.
Model Context Protocol (MCP)Model Context Protocol lets AI applications connect to tools, files, and external systems through a shared context interface.
Prompt EngineeringPrompt engineering designs instructions, context, examples, and constraints so language models produce more useful, consistent, and reviewable output.
RAG (Retrieval-Augmented Generation)RAG is an AI architecture where a language model retrieves relevant passages from documents or databases before generating an answer.