Keep the AI in a read-only environment to explore your codebase and verify the plan as you execute it.
Plan as you go with the goal in mind without making assumptions about a rigid roadmap.
Always validate the bijection against the real-world requirements.
Turn the live spec into a simple checklist of atomic implementation steps.
The backlog will grow and shrink as you learn the domain. It is a live artifact.
Set up a persistent context while you learn.
Create a .md file to store project rules that the AI cannot guess.
Benefits 🎯
You learn about the domain faster because the AI can serve as an encyclopedic mentor.
You stay proudly accountable for the architecture.
You eliminate boilerplate while maintaining system stability.
You close the Human 30% gap by focusing on system coordination.
Context 🧠
These tools are high-velocity coders, but they are very innocent.
They perform best when you instruct with a clear mission and modular instructions.
This "waterfall in 15 minutes" way favors you and the AI to be on the same page before you trigger the first code diff.
Prompt Reference 📝
Bad Prompt:
Build me a task management app with React and Node.
Create a behavior specification and a Gantt project
Good Prompt:
You are a Senior Software Engineer. I want to build a task app.
Ask me 10 clarifying questions about the architecture, security,
and data model.
After I answer, help me draft a spec.md.
Let's build it together with TDD and contract tests.
