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OdaloV
OdaloV

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Agentic-AI :Simple tools to autonomous partners

If you have been following AI development,then you've seen the shift, from ChatGPT answering questions to Devin writing entire codebases. From simple chatbots to systems that plan, execute, and adapt.

What Makes an AI Agentic?

Agentic AI is about ,agency,the capacity to act independently toward goals. While a traditional AI model generates text based on patterns, an AI agent:

  1. Sets and pursues goals
  2. Breaks problems into steps
  3. Uses tools to interact with the world
  4. Learns from feedback
  5. Adapts its approach when stuck

It's like moving from a calculator;executes commands, to a mathematician;solves problems using tools and reasoning.

The Fundamental Loop: Perception → Reasoning → Action

The simplest theoretical model of an AI agent is the Perception-Reasoning-Action cycle:
In practice with LLMs, this becomes the ReAct pattern (Reason + Act):

    python

    # How an AI agent thinks and acts
    def agent_loop(objective, tools, memory):
    while not objective.achieved():
    # 1. PERCEPTION: Look around
    observation = perceive_environment()

    # 2. REASONING: Think about next step
    thought = llm_reason(objective, observation, memory)

    # 3. ACTION: Do something with tools
    action = choose_action(thought, tools)
    result = execute_action(action)

    # 4. UPDATE: Learn and continue
    memory.update(thought, action, result)

return "Task completed"
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Breaking It Down with Fast Food

Let's say you're craving KFC and tell an AI agent: "Get me KFC for dinner"

Old-School AI (Traditional Chatbot)

Would give you instructions:

Go to the KFC website or use Glovo

Agentic AI (Autonomous Assistant)

Actually does it for you. Here's how it thinks:

Agent's Thought Process:

  1. PERCEIVES:

    Checks your current location

    Remembers you ordered KFC last Tuesday

    Notes you usually ask for extra ketchup

  2. REASONS :

    They want KFC. Let me check where they are

    Found 3 KFCs nearby. Which one has the shortest wait time?

    They like the Zinger Burger based on last order.

    Should check for any discounts or offers

  3. ACTS :

    Searches for nearby KFC locations

    Checks opening hours and current wait times

    Compares prices and specials

    Places the order via API

    Tracks the delivery in real-time

  4. UPDATES :

    Noted: they want extra ketchup. Remember for next time.

The bottom line: The agent doesn't just talk about KFC ,it gets you the actual chicken.

Why This Matters
Agentic AI represents a fundamental shift:

You give goals, not step-by-step instructions

AI handles complex multi-step processes

Systems improve through experience

One agent replaces what used to take multiple tools

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