Where the Value Actually Lives
Every major AI coding tool launched in the past two years has made the same bet: help people create new software from nothing. A blank canvas. A fresh repository. An empty prompt. The entire category is optimized for the moment before a product exists.
But that moment is a tiny fraction of a product's life. The vast majority of software work happens after launch. New features on existing architectures. Bug fixes across interconnected systems. Design updates that need to respect years of accumulated logic. Performance improvements on codebases that serve real traffic.
This is the 1 to 100. It is where most engineering time goes, where most business value is created, and where most teams are struggling to move faster. Yet the entire vibe coding market is fighting over the 0 to 1.
We are focused on everything that comes after.
The Real Problem Nobody Is Solving
Every company with an existing product has the same bottleneck. Non-technical team members, PMs, designers, and marketers generate ideas constantly. But they have no way to act on them. They write tickets. They wait. The backlog compounds. Changes that could ship in a day sit untouched for months.
Meanwhile, a new generation of AI coding tools promised to unlock software creation for everyone. Lovable, v0, Bolt.new, Replit. They delivered on that promise, but only for greenfield projects. Only for prototypes. Only for the 0 to 1.
These tools are genuinely useful for exploration and validation. Describe what you want, and AI generates a working interface in minutes. That speed matters when the goal is to learn fast.
But here is what none of them can do: work on your existing product.
Most software value lives in codebases that already exist. Products with real users, real revenue, and real complexity. Different stacks, different configurations, different deployment pipelines. You cannot spin up a generic environment and expect it to work against a production system.
That is the hard problem. And the market is ignoring it.
Why Vibe Coding Breaks in the Real World
The hype peaked in early 2025. By mid-year, traffic to major vibe coding platforms had dropped over 50 percent. People tried, hit the ceiling, and moved on.
The ceiling is predictable. A generated app looks complete to anyone who is not an engineer. The interface renders. Buttons work. Forms submit data. It feels done.
Under the surface, the foundations are missing. Authentication that lives on the client side. Databases that buckle under concurrent users. APIs with no rate limiting or error handling. No logging, no tests, no deployment automation. Code that was produced quickly but structured poorly, making future changes expensive.
These are not edge cases. They are the baseline requirements of any system that serves real users.
But the technical gaps are only half the story. The workflow is fundamentally broken.
AI-generated code still needs to follow engineering process. It needs to live on a branch. It needs to go through code review. It needs to be merged deliberately, not pushed straight to production from a chat window. The tools that skip these steps are not accelerating development. They are creating liability.
Software that lasts is built on fundamentals. Any tool that bypasses them is building on sand.
A Better Model Already Exists
The right pattern for AI-assisted development is not new. Companies like Stripe have already proven it at scale: AI agents generate code, engineers review and approve the output through standard pull request workflows. The model preserves speed without sacrificing control.
The problem is that building this internally requires enormous infrastructure investment. Custom agent frameworks, thousands of automated tests, isolated environments, dedicated platform teams. Most companies cannot justify that cost.
What if you could get the same model out of the box?
Kosuke: AI-Powered Contribution on Existing Codebases
Kosuke is built for the gap that nobody else is filling. Not new projects. Not prototypes. Existing products, with existing teams, on existing codebases.
Import your repository — web applications, React Native, Flutter, any stack. Non-technical team members describe the change they want in plain language. AI generates code that respects your conventions and architecture. The output is submitted as a pull request for engineering review.
Every change lives on its own branch. Nobody bypasses code review. Engineers retain full control over what ships. The workflow is the same one your team already follows — branches, PRs, reviews, merges — with a new class of contributors feeding into it.
Kosuke adapts to your environment. Give it the commands to run your application, and it handles the rest. Any stack. Any configuration. Real changes that work in your actual deployment setup.
The result so far: 80 percent of AI-generated pull requests get merged. Not on toy projects. On production codebases with real engineering teams reviewing the output.
The Vision: We Will ALL Be Builders
Developers and designers are still working in silos. Not because the technology is not good enough. Because the tools are built that way. Every tool is designed for one or the other. Figma for designers. Cursor for developers. Nobody is building for product teams that want to contribute to the same codebase.
That is the gap we are filling.
We are not replacing developers. We are not skipping pull requests. Code is still the source of truth. Engineers still review everything. But now designers, PMs, and marketers can contribute too. Same codebase. Same workflow. No silos.
We will ALL be builders. Builders with different skill sets, but at the end of the day, all shipping on the same codebase. AI for speed, engineering for strength.
The company that unlocks collaboration for non-developers on existing codebases will win. We intend to be that company.
If you have an existing product and a team that wants to ship faster, we built Kosuke for you.