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AI & Search

AI Agent

Agentic AI | Autonomous Agent

Portrait of Lukas Horvath, co-founder of Roelu Studio
Lukas HorvathCo-founder

What is AI Agent?

An AI agent is a system built on top of a large language model that can take multi-step actions in the real world, not just generate text. It uses tools — APIs, browsers, code execution, internal systems — to complete tasks like booking a flight, drafting a report from live data, or qualifying inbound leads. Agentic AI differs from a chatbot in that it can plan, act, observe the result, and adjust. By 2026, autonomous agents are embedded inside most serious AI products.

Why it matters

Chatbots answered questions. AI agents do work. The shift matters because the operational value moves from 'helpful intern' to 'extra headcount that runs 24/7.' Marketing teams use agents to research accounts, write personalized outbound, build reports, and triage inbound. Sales teams use them to schedule, summarize calls, and update CRM. Done well, an agent eliminates a category of busywork. Done badly, it confidently sends a wrong email to a real customer. The difference is in the guardrails, the prompts, and which tools the agent is actually allowed to use.

How it works

An agent runs in a loop. It takes a goal, picks a tool to use, executes it, reads the result, and decides what to do next. The LLM is the brain. The tools — web search, calendar, email, internal APIs — are the hands. Modern agents are built with frameworks like LangGraph, OpenAI's Agents SDK, or Claude's agent loop, and they often talk to external systems through MCP. A good agent has clear scope, a small set of well-defined tools, and human approval steps for anything risky. Without those, you get a confident system doing the wrong thing at scale.

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