A brief summary of what I have learnt

This is an exert of From AI Skeptic to Constant Collaborator: What I Learned Vibe Coding.

Practical Workflows

Through trial and error, I developed specific patterns to manage AI’s weaknesses:

1. The Planning Folder Pattern Keep numbered specs (1-initial-feature.md, 2-pay-by-discard.md, etc.) that document feature discussions. These become persistent context across sessions.

2. The Todo Accountability System Break specs into granular checkbox lists. Use them to hold the AI accountable during implementation.

3. The Git Save-Scumming Strategy Commit frequently. AI will overwrite working solutions without memory of what worked before.

4. The Role-Based AI Selection

  • ChatGPT: Brainstorming, exploration, asking “what’s wrong with this design?”
  • Claude: Implementation, code review, pair programming
  • Copilot/Codex: Ticket-style work where you hand off and come back later

5. The Discipline Override Set hard rules to counter AI’s momentum:

  • Force refactor cycles
  • Write tests even when AI makes it feel unnecessary
  • Question every tangent: “Is this the MVP?”

Minimum Viable Prompt Literacy

I have no idea what a “perfect prompt” looks like. But I know one rule that consistently works:

No matter what you ask the AI to make, the last sentence should be: “Ask me questions.”

Get the AI to ask you questions. Ask it “what am I missing?” type questions. This back-and-forth is where the real value emerges, not in the first response, but in the dialogue.