Gen AI vs AI Agents vs Agentic AI: Key Differences Explained

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Generative AI (Gen AI)

  • Creates text, code, or images using prompts
  • No memory or reasoning capabilities
  • Best for content creation

AI Agents

  • Executes predefined workflows
  • Limited autonomy and reasoning
  • Uses basic tools for task completion

Agentic AI

  • Autonomous problem-solving with deep reasoning
  • Coordinates multiple agents for complex tasks
  • Adapts without human intervention

Comparison Insights

  • Creativity: Gen AI
  • Execution: AI Agents
  • Autonomy: Agentic AI

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You Should Know:

AI Implementation with Linux & Python

1. Run Generative AI Locally (Linux)

git clone https://github.com/oobabooga/text-generation-webui 
cd text-generation-webui 
pip install -r requirements.txt 
./start_linux.sh --model=gpt-4 

2. Build a Simple AI Agent (Python)

from langchain.agents import load_tools, initialize_agent 
from langchain.llms import OpenAI

llm = OpenAI(temperature=0) 
tools = load_tools(["serpapi"], llm=llm) 
agent = initialize_agent(tools, llm, agent="zero-shot-react-description") 
agent.run("What’s the latest news on AI?") 

3. Deploy Agentic AI with Docker

docker pull huggingface/transformers 
docker run -it -p 5000:5000 huggingface/transformers python agentic_ai_server.py 

4. Monitor AI Performance (Linux Commands)

nvidia-smi  Check GPU usage 
htop  Monitor CPU/Memory 
journalctl -u docker --no-pager -n 50  Check Docker logs 

5. Automate AI Workflows (Cron Jobs)

crontab -e 
/30     /usr/bin/python3 /path/to/ai_agent.py >> /var/log/ai.log 

What Undercode Say:

AI is evolving rapidly, and understanding the differences between Gen AI, AI Agents, and Agentic AI is crucial for implementation. Linux and Python remain key tools for deploying AI solutions, whether for automation, content generation, or autonomous decision-making.

Expected Output:

  • Gen AI: Text/Image Output
  • AI Agents: Task Completion Logs
  • Agentic AI: Multi-Agent Coordination Reports

Prediction:

By 2025, Agentic AI will dominate enterprise automation, reducing human intervention in complex workflows by 40%. Organizations leveraging AI with strong DevOps practices (Docker, Kubernetes, CI/CD) will lead the adoption curve.

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IT/Security Reporter URL:

Reported By: Naresh Kumari – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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