Day 1: Cracking Open the Code of Agentic AI

Course: Agentic AI Engineering Crash Course
Lectures Completed: 6/150
Mood: Mind = Blown

✨ Key Learnings

• Got hands-on with n8n, a powerful no-code workflow tool — feels like Zapier with a turbo engine.

• Explored Cursor AI, a code editor powered by AI — it's like having an LLM pair-programmer who doesn't sleep.

• Used UV Program Manager to manage runtime environments and tasks cleanly.

• Learned how to import and structure agents from repositories — packages, folders, and all that orchestration jazz.

🏡 My First Project: Smart Home Automation Agent

I created an automation where:

• A chat messenger sends commands to an AI agent running GPT-4.

• That agent controls a Philips Hue smart light bulb.

• Result: One message. One AI. Lights on/off. It felt like Tony Stark whispering to J.A.R.V.I.S.

🔄 The workflow was so smooth — like wiring thoughts to actions with code.

💻 Setting Up the Agentic Environment

Inside Cursor AI, I set up the dev environment with:

• Python 3.12

• PyLabs: A lab-based setup to tinker with OpenAI, DeepSeek, Ollama, and Gemini APIs.

• Integrated API keys and configured local agents to access large-scale models directly.

It’s wild how easy it is to spin up LLMs from different providers and pipe them into a single control layer.

🤯 Coolest Thing I Saw Today

An agent that asks itself questions and answers itself — full self-reflective AI loops. Literally a conversation with itself to solve a problem.
Like a monk... but powered by transformers.

📓 Reflections

Today felt like unlocking a secret level in AI engineering. From agent setup to real-world automation, I’ve only scratched the surface.
Only 6 lecture down, 144 to go — but I’m already seeing the future here.

Tomorrow's goal: Dive deeper into multi-agent communication and dynamic workflows.

“This is just the beginning...”

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Written by Sri Ram Vishal
Agent-in-Training | Full Stack Developer | Maker of the Future