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How to use Cook with AI.

Use the library like a developer workspace: build the fundamentals, pick one serious AI coding tool, ship one app, then reach for tutorials when you need a specific workflow.

How to use it

A simple rhythm

  1. 01 Start with AI Fundamentals Build the shared mental model first: agents, context, plans, review, and verification.
  2. 02 Pick your daily tool Choose Cursor, Codex, or Claude Code based on how you already like to work.
  3. 03 Build one app Use one real project to practice the full loop from plan to implementation to cleanup.
  4. 04 Use tutorials as needed Pull in focused tutorials when a specific workflow, tool, or deployment question appears.
  5. 05 Share in Discord Post what you are building and get feedback from the community.
Remember

You do not need to optimize the path. Pick a tool, build something, and adjust as you go.

The simple version

Start with AI Fundamentals. That guide gives you the shared vocabulary for working with agents without outsourcing your engineering judgment: context, plans, verification, diffs, commits, and review.

Then pick one core tool and stay with it long enough to build a real project. If you already live in an editor, start with Cursor. If you like a dedicated agent app or CLI, start with Codex or Claude Code.

Build one complete app.

Do not bounce between tools for a week. Choose one small app idea with real constraints, plan the first slice, and build it with the tool you picked. The learning happens when you review what the agent produced and make it fit the product you actually want.

After that, use the tutorials as reference material. Need local AI? Open the local AI tutorials. Need code review, specs, Git workflows, server work, or design help? Jump into that category when the need is real.

Keep the loop tight.

For every session, write down what you want, let the agent work in a small slice, inspect the diff, run the app, and commit the result. That loop matters more than the specific model or editor you start with.

Use Discord when you get stuck or want another pair of eyes on a workflow. Bring real code, real product decisions, and real tradeoffs. That is where the material becomes practical.