Should This Code Deploy? Letting AI Decide

💥 The Problem

Ever pushed a minor config update… and waited ages for approval?

Meanwhile, someone drops a risky Friday deploy — and it sails right through.

What if your pipeline could tell the difference?

🛠️ What I Built

A smart CI/CD pipeline that runs 100% locally, powered by a local AI model.
No OpenAI. No cloud. Just GitHub Actions, Python, and Mistral via Ollama.

✅ Stack:

• GitHub Actions – triggers the pipeline

• Python script – extracts the commit message and sends it to AI

• Mistral LLM (via Ollama) – runs locally and gives a risk score

⚙️ How It Works

1️⃣ Push some code → GitHub Actions kicks in
2️⃣ It grabs the latest commit message
3️⃣ That message is sent to your local Mistral LLM
4️⃣ The AI evaluates risk and classifies the commit as:

• 🟢 Low Risk → Auto-deploy

• 🟡 Medium Risk → Pause + Notify

• 🔴 High Risk → Block the deploy

All based on the commit message — no hardcoded rules, just natural language understanding.

💡 Why This Matters

Push a typo fix? It flies through.
Push something shady on a Friday? It gets flagged.

AI becomes your teammate in the pipeline — not just another fancy tool.

📥 Want the Code?

Subscribe and you’ll get instant access in the welcome email:
👉 learnwithdevopsengineer.beehiiv.com

Or just reply to this post — I’ll send it over personally.

🎥 See It in Action

👉 Watch the full demo on YouTube