AI를 학습하는 동안 토끼구멍

I was supposed to stop at LangGraph.

That was the plan.

Instead, the rabbit hole decided otherwise.

Some of the things I unexpectedly picked up while chasing Agentic AI:

⚙️ Docker

• Multi-stage Dockerfiles
• Docker Compose
• Volumes
• Building images from my own projects instead of just pulling them
• Finally understanding why “works on my machine” isn’t enough

🤖 GitHub Actions

• Automated builds and tests
• CI/CD pipelines
• Branch protection rules
• Secrets management
• Automatic Docker image publishing
• Realizing how satisfying it is when pushing code triggers everything for you

🌿 Git & Engineering Practices

• Conventional commits
• Pull requests even for solo projects
• Trunk Based Development
• Small, rapid merges instead of week-long branches
• Keeping main always deployable

🚀 Deployment

• Actually shipping things instead of leaving them in localhost prison

And somehow, while trying to learn AI, I ended up appreciating software engineering just as much.

Still left:

• LlamaIndex
• Cloud
• Terraform

Apparently the roadmap had other plans.

Curious what unexpected rabbit holes everyone else fell into while learning AI.