Skills you walk away with

Whatever you choose to make, these are the skills we’ll practice together. Use the checklist to see what you can do on your own.

1. Set up your AI workspace

   Learn how to give the tools enough structure without burying them in instructions.

   • Organize projects and give AI useful background, personal preferences, and written instructions.
   • Know where your files live and point each project at the right folder.
   • Choose the right model for the task and use a second model when comparison is useful.
   • Separate personal and business work, and learn how to handle credentials and sensitive information safely.
   • Use the command line and a GitHub repository when the project actually warrants them.

2. Build something useful

   Turn a real problem into a result you can use again.

   • Choose a project and narrow it to a useful first version.
   • Turn a rough idea or voice-memo ramble into a clear brief.
   • Build a first working version, then improve it with guidance.
   • Add workflows, automations, hosting, or design work only when they make the project more useful.

3. Make the work trustworthy

   Know how to check the result, repair it, and recognize its limits.

   • Verify important outputs and have agents review one another when the stakes justify it.
   • Recover when the work gets stuck, the context gets messy, or the first approach fails.
   • Know when AI is likely to be wrong and when the task belongs with an expert.
   • Ask the AI what it can reach, and push back when it says something can’t be done.

4. Work at a higher level

   Turn one successful project into a way of working you can carry forward.

   • Create reusable skills, and know when a skill is unnecessary or should be discarded.
   • Give several AI agents separate jobs and bring their work together.
   • Manage usage limits and computer performance, work from your phone, and apply what you learned to a second project.