My Cheatsheets

🔁 Core Workflow Flow

[1] Describe what you want
[2] Approve/refine AI suggestion
[3] Confirm canvas updates
[4] Save/track decisions
[5] Repeat in modular steps

🛠️ Your Role (What You Handle)

# ✅ 1. Start with Intent

• Always give clear goal or desired outcome, not just “write code.”
• Ex: “I want a simple REST API to track books” or “Let’s plan a React Native screen for hunt details.”

# 🗂️ 2. Approve Canvas Target

• AI will propose what canvas it wants to update.
• You must confirm it’s the right one before changes are made.
• Be explicit: “Yes, update the hunt_editor canvas.”

# 📓 3. Log Key Decisions (or ask AI to write it for you)

• If a name, library, structure, or behavior is chosen, log the why.
• Use a Decisions.md, README.md, or whatever doc format fits.

# 🧱 4. Keep It Modular

• Ask for one feature, function, or module at a time.
• Avoid requesting giant full-app dumps unless you’re just prototyping.

# 📌 5. Request Summaries

• After any major change or code output:

  • Ask: “Give me a summary of what you just did”
  • Ex: files affected, rationale, what to test

💡 Good Prompts to Keep Handy

• “Start with a plan in markdown.”
• “Write a Decisions.md entry for that choice.”
• “Let’s do this one module at a time.”
• “What do we need to build this feature?”
• “Summarize changes in bullet points.”
• “What canvas are you planning to update?”
• “Implement it, then do a reviewer pass: invariants, edge cases, top 5 failure modes.”
• “State assumptions first. If assumptions are wrong, stop and ask.”
• “Write tests that would fail if your logic is wrong (not just happy-path).”
• “If an API/library detail is uncertain, flag it and give 2 alternatives.”
• “Pause after interfaces, then after core logic, then after error handling.”

🚧 Caution Zones