How to Build Your First AI, GenAI & Agentic AI Project
Every tutorial on the internet right now starts with a ten-paragraph essay defining what an LLM is, as if you haven't been forced to use GitHub Copilot or ChatGPT for the last two years. Let's skip that.
The problem isn't understanding what Generative AI is anymore. The problem is that when you sit down to actually build something beyond a wrapper that sends "Hello" to the OpenAI API, the terminology gets murky fast. What makes something "GenAI"? When does an app cross the line into being an "Agent"?
We are going to build a small local CLI tool that takes a messy, unstructured text file of raw server logs, generates a summary using an LLM, and then—here's the agentic part—automatically writes and executes a cleanup script based on what it found.
No LangChain abstractions that hide what's actually happening. Just Python, the raw openai library (pointing to whatever model you have), and standard subprocess calls.
