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Agentic AI explained simply

Team Rokodo
3 min
-
13.02.2026
What is agentic AI?

Agentic AI is a way to design AI so it becomes more autonomous and useful. Instead of only answering questions, an agentic AI can reason about a request, plan steps to reach a goal, use external tools (APIs, web search, software), and collaborate with other AIs.

Three types of workflows

1) Classic automation (no AI)

Fixed rules written in advance (e.g., a robot copying data between spreadsheets).

2) Non-agentic AI

Generates an answer but has no real autonomy (e.g., a language model listing books).

3) Agentic (AI agent)

Thinks, chooses a strategy, uses the right tools, and verifies results (e.g., deciding to search online before answering a factual question).

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Four common “patterns”
  • Reflection: self-checks and improves its own output.
  • Tool use: connects to APIs, search engines, databases, scripts.
  • Planning: breaks a complex task into logical sub-tasks (sequential or parallel).
  • Multi-agent: several specialized agents collaborate (coding, testing, documentation).

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    Concrete applications
  • RAG: agents retrieve and organize information before writing a clear answer.
  • Software development: assistants that write code, create apps, or generate tests.
  • Multimedia creation: turning research into pages, text into video, etc.
  • Healthcare: automating certain clinical or administrative tasks.
  • Customer service: natural-language support agents.
  • Web navigation: agents that fill forms, book travel, or click through flows.

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    In short

    Agentic AI moves from an AI that “responds” to an AI that acts—by reasoning, planning, using tools, and collaborating.