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Have you ever wondered why your results are messy while everyone else is using AI coding?Today’s introduction goes beyond simply ‘writing code’; it contains the key takeaway to making AI manage like a competent development team lead.Especially if you’ve wasted time verifying code that has correct syntax but twisted logic or isn’t 100% perfect, this post will be a real lifesaver.I will tear down in detail how ‘bkit’, a tool that boosts Claude Code‘s potential by 200%, and the PDCA cycle utilizing it can completely change your work method.

The Secret Weapon to Maximize Claude Code Performance: Perfect Analysis of bkit and PDCA Process

1. The Reality and Limitations of Vibecoding: Why Does My AI Make Mistakes?

Have you heard of ‘Vibecoding’, which is hot among developers these days? It’s a brave new world where you just talk to the AI and it creates code in 5 minutes, but the moment you try to apply it to actual work, you hit a wall.

The biggest problem is the ‘swamp of verification’.An ironic situation occurs where I have to spend 1 hour inspecting code that AI wrote in 10 minutes.It’s grammatically perfect, but often business logic is missing, or the AI forgets the details I requested.

This is because when we give work to AI, we throw it “too roughly, without a system”.Just as results are messy when you speak vaguely to a person, AI is the same.To get the best efficiency within a limited context window (memory capacity), you must hand the AI the ‘order and method of working (manual)’.

2. Enter the AI Trainer: What is bkit?

That’s why bkit appeared.Simply put, think of it as a plugin that implants rules into Claude Code, saying “You only work according to this manual from now on.”

It defines the systematic process we use when coding in the form of a markdown document and makes the AI follow it.Installation is also very simple. Just copy a few lines of commands from the GitHub repository and paste them into the terminal, and you’re done.

Once installation is complete, you can systematically instruct everything from project initialization to planning, analysis, and verification through slash (/) commands in Claude Code.Now, AI is not just a ‘coding machine’, but becomes a ‘developer who knows the process’.

3. Practical Project: Resurrecting the Nostalgic MDIR as a Terminal App

So, what can you make with this?I tried making a file management program like the MDIR that made using computers easy back in the DOS era.I utilized the modern tech stack of Node.js and React, and the Ink library that draws UIs in the terminal.

Here is the step-by-step process where the true value of bkit shines.

1) Project Initialization (Init Dynamic):Instead of just “Make a file management app”, start by clearly defining the project scale and tech stack (React, Ink, etc.) with the init dynamic command. If you do this, the AI sets up the skeleton code very solidly.

2) Application of PDCA Cycle:This is the core point of today’s post. bkit forces the execution of the PDCA (Plan-Do-Check-Act) methodology.

Plan: First, write a document on what to make.
Do: Write code according to the plan.
Check: Verify if what was made is correct.
Act: Improve the deficiencies.

Going through this process results in much more logical and less error-prone output than code just whipped up instantly.

4. ‘Zero-Script QA’ and ‘Gap Analysis’ Where AI Fixes Bugs Itself

The features that surprised me the most are ‘Zero-Script QA’ and ‘PDCA Analyze’.

Usually, when AI writes code and an error occurs, I have to ask again, “This isn’t working, is it?”But if you use bkit, the AI tests the functions one by one by running the app, and if something doesn’t work, it says, “Uh? This isn’t working. I will fix it,” and runs the correction cycle itself.

If there are missing features (e.g., file copying doesn’t work) or the design is crude, try using the PDCA Analyze command.It writes a report analyzing the gap between the currently implemented code and the initial requirements, and modifies the code again based on that report.Repeating this process significantly reduces the places I need to touch.

5. The Aesthetics of 90% Completeness: Pragmatic Development and Deployment

What’s interesting about bkit is that it suggests aiming for “90% completeness”.Since the effort to fill the remaining 10% is too great, it makes the judgment that 90% is deployable from a pragmatic perspective.Isn’t it quite impressive that AI even possesses this kind of judgment?

When verification is done, it even prepares for deployment automatically.

Security Check: Since it’s an app that touches the file system, it inspects and fixes vulnerabilities as if hacking itself to see if there are any that could destroy my computer.
Documentation: The README.md file is basic, and it even handles package.json settings on its own.
Website Creation: It even creates a promotional website introducing this project in an instant with React and Tailwind CSS through a 9-step process. The design quality is also substantial.

6. Expert Perspective: Beyond Simple Coding to ‘Process Engineering’

Most news or YouTube channels focus only on “AI writes code”.However, the real core point is “teaching AI how to work”.

The emergence of tools like bkit is a signal that we must now move beyond ‘prompt engineering (how to speak well)’ to ‘process engineering (system of assigning work)’.There are many people who use AI coding tools, but the difference in the quality of the results will ultimately be decided by “how systematically you manage the AI”.

If you want to create a product that is commercially viable beyond a toy project made simply for fun,I strongly recommend adopting tools like bkit that give AI “time to think (Plan)” and the “duty to verify (Check)” instead of ordering recklessly.This is truly like having one reliable mentor by your side for a solo developer.

< Summary >‘bkit’, which maximizes the performance of Claude Code, is a tool that dramatically improves coding accuracy and completeness by forcing the PDCA (Plan-Do-Check-Act) process on the AI. Beyond simple code generation, it systematically performs self-error correction, security checks, documentation, and even the creation of deployment websites. The core competitiveness of the Vibecoding era lies in the process management ability to assign an ‘order of work’ to the AI.

*Source: 코드깎는노인

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