# Daily Workflow Walkthrough — Learn by Doing ## Before We Begin **Question:** How do you currently use your development tools throughout a typical day? Where do you spend the most time — writing code, reviewing, debugging, or learning? **Checkpoint:** The user can describe their current workflow and identify at least one area where AI assistance could help. --- ## Step 1: Morning Setup and Stats **Task:** Open your terminal and run `/teach:stats` to check your current XP and belt. Then run `/teach list` to see available modules. Note which modules you've completed and which are recommended next. **Question:** Why might checking your learning progress at the start of the day be useful? How does it connect to deliberate practice? **Checkpoint:** The user has run both commands and can describe their current progress. --- ## Step 2: Reviewing Code with AI **Task:** Find a recent PR or code change (yours or a teammate's). Ask your AI assistant to review it, focusing on error handling and edge cases. Compare the AI's feedback to what you would have caught yourself. **Question:** What did the AI catch that you might have missed? What did it miss that you noticed? When should you trust AI feedback vs. apply your own judgment? **Checkpoint:** The user can articulate the strengths and limitations of AI-assisted code review. --- ## Step 3: Debugging with AI Assistance **Task:** Think of a recent bug you encountered (or use a hypothetical one). Describe it to your AI assistant with context: the error message, the expected behavior, and the actual behavior. Walk through the debugging process together. **Question:** How did providing context change the quality of the AI's suggestions? What's the minimum context needed for useful debugging help? **Checkpoint:** The user understands that AI debugging quality depends heavily on the context provided. --- ## Step 4: Learning During the Day **Task:** Choose a module from `/teach list` that relates to something you're working on this week. Start the walkthrough and complete at least 2 steps. Notice how the Socratic method asks you to think before giving answers. **Question:** How is learning through guided questions different from reading documentation? Which approach helps you retain more? **Checkpoint:** The user has started a module and can explain the value of active recall over passive reading. --- ## Step 5: Building a Feature with AI **Task:** Pick a small feature or improvement in your project. Use your AI assistant to help plan it: describe what you want, ask it to outline the approach, then implement it yourself (with AI help for specific questions). Track how you divide the work. **Question:** What parts of the feature were faster with AI help? What parts required your own expertise and judgment? Where's the line between productive AI use and over-reliance? **Checkpoint:** The user can describe a healthy division of labor between themselves and AI tools. --- ## Step 6: End-of-Day Reflection **Task:** Review what you accomplished today. Run `/teach:stats` again and compare to the morning. Write a brief note (mental or written) about: one thing AI helped with, one thing you did better yourself, and one thing you want to learn tomorrow. **Question:** How would you design your ideal daily workflow that balances AI assistance, independent work, and continuous learning? **Checkpoint:** The user can articulate a personal workflow that integrates AI tools without depending on them.