Product Manager Builds Legal-Tech App Using 'Vibecoding' and Claude AI

Product manager Aniket Bhosale has developed a production-grade legal-tech application by replacing a traditional engineering department with a single AI agent. The project, a tenant-landlord dispute resolution platform called VaadNivaaran, was built using Claude AI through a process known as "vibecoding."

According to Bhosale, the AI performed the roles of a Chief Product Officer, Chief Technology Officer, and several specialized engineers, including backend, frontend, AI/ML, and QA roles, as well as technical writing. The resulting codebase consists of 14,400 lines of production code distributed across 57 source files. To ensure stability, the development process included the creation of 195 passing tests. The total financial investment in API costs for the development was approximately $100.

The Rise of Vibecoding

This project exemplifies "vibecoding," an emerging trend where product managers or developers use high-level AI agents to generate entire applications. Rather than focusing on manual coding and technical implementation details, the practitioner uses natural language and iterative prompting to guide the AI. This approach prioritizes the "vibe"—the overarching intent of the product—allowing the AI to handle the underlying architecture and execution.

Lowering the Barrier to Entry

The development of VaadNivaaran demonstrates a significant shift in how complex software, particularly in specialized fields like legal-tech, can be brought to market. By utilizing AI to handle system architecture and quality assurance, solo founders can now build sophisticated tools—such as those providing risk scoring for rental disputes—with minimal capital. This removes the traditional requirement for large seed investments to hire full-stack engineering teams during the prototyping phase.

As Bhosale noted regarding the shift in focus from syntax to strategy, "The code is the easy part."

Future Implications

While the VaadNivaaran project proves that production-ready code can be generated at a fraction of traditional costs, the industry continues to evaluate the long-term maintainability and security of AI-generated architectures. Observers are now watching to see if this "vibecoding" model can scale to larger, more regulated enterprise environments or if it will remain a powerful tool primarily for solo founders and rapid prototyping. This shift suggests a future where the primary bottleneck for software creation is no longer technical execution, but the clarity of the product vision and the ability to prompt AI effectively.