Give your work
a home.
You do not need to become a developer. You do need a place for the things you make to live.
When an idea becomes something real
At first, AI often feels like a better search box. Ask a question. Get an answer. Move on. But eventually you will want to make something useful: a small tool, a classroom resource, an automated report, a website, or a workflow that gives you an hour back every week.
That is the moment your work needs a home. For me, that home is GitHub.
Git and GitHub, without the mystery
Think of Git as a careful record of your project's history. GitHub is the remote home where that history can be stored, shared, and recovered. You do not need to memorize every command. You only need to understand the flow.
Stage
Choose the specific changes that belong in your next saved version.
Commit
Save a named snapshot in the project's local history.
Push
Send your saved snapshots to GitHub.
Fetch & pull
Check for remote changes, then bring them into your local project when you are ready.
Where the LLM comes in
Once you understand this picture, an AI assistant can handle much of the detail. It can initialize a project, create a private repository, add ignore rules, stage files, create a commit, and push it to GitHub through GitHub CLI.
“Create a private GitHub repository for this project. Add an appropriate ignore file. Show me what will be committed before committing it. Commit the initial version, push it to main, and give me the repository link.”
You still own the important decisions
- Is this project public or private?
- Which files are safe to include?
- Does the summary actually match what changed?
- Is it ready to share or deploy?
- Did the final result work?
The AI can be the detailed knowledge worker. You remain the person responsible for the purpose, the boundaries, and the final call.
Choose the right kind of AI.
Not “which company wins?” but “what kind of work am I trying to do?”
Return to the learning path ↗