I Made This @ MoMo: A 3-layer vibe-product-building approach

B3 Awesome -

Everyone is talking about GPT-5 models these days, calling it a "Claude killer." It seems that technical influencers are some of the most aggressive narrators in the industry. Whenever a new release is discussed, the features highlighted should ideally be game-changers. Remember the hype surrounding new social networks that were dubbed "Facebook killers" in the past? 🧐

After months of refining my AI development process, alongside Claude Code, I have established a procedure that maximizes the capabilities of the Anthropic AI-powered CLI tool. This not only offered vibe-coding but also empowered me, as a Product Manager, to build products similarly to real-world product development, which includes:

  • Well-planned product requirements
  • Clear process control
  • Specialized execution management
  • Consistent task coordination
  • Quality assurance integration

I call it my 3-layer vibe-product-building approach:

First Layer: This involves defining a strict, repeatable workflow that standardizes the steps necessary for process compliance and consistent execution. Essentially, I instruct Claude Code to create the Product Requirement Document (PRD), generate the backlogs, define the development stack, write the technical documentation, and conduct grooming sessions. Sound familiar? Yes, I’m tired of waiting for Kiro, the vibe-coding IDE, so I borrowed the concept. Fortunately, it has proven to be very effective.

Second Layer: This layer leverages specialized AI agents, thanks to Claude Code’s sub-agents, for each execution of the workflow. It benefits from the specialized expertise, automated decision-making, and scalable capabilities of these sub-agents, which can develop new sub-agents based on the specifications from the first layer. Imagine having a team of experts join your scrum team for just $20 each, hiring the right one for every task—all made possible through the magic of AI.

Third Layer: Here, I focus on sprint planning for direct task execution from structured artifacts. Again, I apply a pure Kiro methodology without adding external complexity. There’s no need for Claude Flow or Task Master; Claude Code sub-agents tackle one task at a time and utilize Claude Code’s native to-do feature. This ensures clear deliverables, visible progress tracking, and high-quality integration.

A powerful AI model cannot deliver the benefits of scaling across teams and projects, maintaining quality without sacrificing speed, reducing decision fatigue through automation, or ensuring knowledge transfer through effective documentation. Not Claude, Gemini, or GPT can achieve this. A well-designed setup can.

To date, there is no AI-powered CLI tool that can set things up as effectively as Claude Code. So, welcome aboard GPT-5; let’s meet in Claude Code. I hope the Claude Code Router serves you well.