{"id":7049466,"date":"2026-08-27T22:04:58","date_gmt":"2026-08-27T22:04:58","guid":{"rendered":"https:\/\/som2nypost.com\/analytics\/10-most-important-agentic-ai-concepts-explained-simply\/"},"modified":"2026-08-27T22:04:58","modified_gmt":"2026-08-27T22:04:58","slug":"10-most-important-agentic-ai-concepts-explained-simply","status":"publish","type":"post","link":"https:\/\/som2nypost.com\/?p=7049466","title":{"rendered":"10 Most Important Agentic AI Concepts Explained Simply"},"content":{"rendered":"


\n<\/p>\n

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AI agents are everywhere right now. You hear terms like tool calling, agent loops, MCP, guardrails<\/strong> thrown around as if its common language\u2026 it isn\u2019t! But that is about to change.<\/p>\n

Agentic AI isn\u2019t nearly as complicated as it sounds once you\u00a0understand the few core ideas that actually matter<\/mark>.<\/p>\n

Here are 10 agentic AI concepts<\/u> that everyone should know about, ranked by what people are searching for and using daily.<\/p>\n

If you feel that the concepts are a bit tough to go through, considering reading basic AI concepts<\/a> before moving on to this one. <\/p>\n

1. AI Agents<\/h2>\n

A chatbot answers<\/strong>. Think ChatGPT<\/a>, Claude<\/a>, Gemini<\/a>\u2026 at least how they were back in the days.<\/p>\n

\n
\"AI<\/figure>\n<\/div>\n

An AI agent works toward a goal<\/strong>.<\/p>\n

\n
\"An<\/figure>\n<\/div>\n

An AI agent is a system that uses an AI model to decide what actions to take, interact with external tools or systems, observe the results, and continue working through a task.<\/p>\n

For example, imagine telling an AI:<\/p>\n

\u201cFind three flights to London under \u20b960,000, compare them, and draft the best itinerary.\u201d<\/em><\/p>\n

A chatbot can tell you how to search for flights.<\/em><\/p>\n

An agent can:<\/p>\n

    \n
  1. Search flight websites<\/li>\n
  2. Collect available options<\/li>\n
  3. Filter them by price<\/li>\n
  4. Compare departure and arrival times<\/li>\n
  5. Check baggage rules<\/li>\n
  6. Prepare an itinerary<\/li>\n<\/ol>\n

    \n The important difference is that the agent isn\u2019t simply generating the answer in one shot. It is executing a process<\/b>.\n<\/p>\n

    2. The Agent Loop<\/h2>\n

    The most important idea behind agentic AI in general, is the agent loop<\/strong>.<\/p>\n

    An agent doesn\u2019t know the complete solution before it starts. It takes an action, sees outcome, and then decides what to do next based on the outcome.<\/p>\n

    \n
    \"Four<\/figure>\n<\/div>\n

    Suppose an agent is asked:<\/p>\n

    \u201cFind the latest quarterly revenue for OpenAI.\u201d<\/em><\/p>\n

    It will:<\/p>\n

      \n
    1. Search the web<\/li>\n
    2. Find earning reports for OpenAI<\/li>\n
    3. Open the relevant document<\/li>\n
    4. Search for revenue<\/li>\n
    5. Verify the number against another source<\/li>\n
    6. Return the answer<\/li>\n<\/ol>\n

      If the first website doesn\u2019t contain the information, the agent can change its approach. That ability to observe intermediate results and adapt<\/strong> is what makes the loop different from a simple predetermined prompt chain.<\/p>\n

      \n
      \"Agent<\/figure>\n<\/div>\n

      An AI chatbot by itself cannot send an email, query your company\u2019s database, or browse your website.<\/p>\n

      Tools give agents those capabilities.<\/em><\/strong><\/p>\n

      A tool is simply an external function that an agent can call when it needs to perform a specific action.<\/p>\n

      Examples include:<\/p>\n