Plan Before You Prompt: The AI-First Product Loop

Why Planning Beats Typing

For decades, the bottleneck in software was turning decisions into code. AI has largely removed that bottleneck. Teams can now ship multiple features in the time it once took to build one, but only if their planning improves alongside their tooling.

The difference between vibe coding and building a real product is planning. Vibe coding asks the model to invent the plan. Strong teams define the plan first, then use AI to execute it. Most failed AI projects can be traced back to poor planning rather than poor implementation.

The Five-Step Loop

The workflow consists of five steps:

1. Define the vision.
2. Create the requirements.
3. Build the roadmap.
4. Execute with AI.
5. Release, measure, and learn.

The final step loops back into the first. Production learnings inform the next vision, creating a continuous cycle of improvement.

For planning, use a frontier reasoning model such as Claude, GPT, or Gemini. For execution, use an agentic coding tool like Claude Code, Codex, or Cursor.

Cadence: A Working Example

Throughout the lesson, Derek uses a fictional product called Cadence, an AI-powered task manager that turns messy thoughts into prioritized action items.

The example is simple enough to understand quickly but complex enough to demonstrate real AI product challenges. Success is measured by a single outcome: whether users actually complete more of their planned tasks.

From Vision to PRD to Roadmap

The vision document defines why the product exists. The PRD defines what will be built. The roadmap defines when work happens.

Instead of asking AI to write these documents from scratch, have it interview you. Use prompts that force the model to ask questions, challenge assumptions, and clarify vague ideas.

The roadmap should prioritize work by risk and value, organized into Now, Next, and Later. Keep all planning artifacts in a version-controlled context file that AI can reference throughout development. Accurate context compounds; stale context creates problems.

Prompting Like a Tech Lead

Treat AI as an engineer, not a search engine. Your role is to provide direction.

Strong prompts contain four elements:

• Intent
• Context
• Rules
• Acceptance criteria

The most valuable habit is asking for a plan before asking for code. Review the plan, approve it, then move into implementation.

The operating rhythm is simple: plan, review, test, and refine. Small changes are easier to validate than large rewrites, and every line of generated code should still be reviewed by a human.