A 30-day Journey with AI Coding Assistants
Recently, software developer Anand Panchal embarked on a unique challenge: to build a complete full-stack application using only AI coding assistants. Throughout the 30-day experience, Panchal relied on tools such as GitHub Copilot, Cursor, and Claude Code to generate code, provide feedback, and assist with debugging.
The end result of this experiment was a fully functional SaaS product developed in just 2 weeks. However, the journey was not without its challenges and revelations about the capabilities and limitations of AI in software development.
One of the key takeaways from this project was the effectiveness of AI in tasks like generating standard code and handling CRUD operations. These coding assistants proved to be valuable resources in speeding up the development process and reducing manual coding efforts.
Despite these successes, Panchal also encountered significant flaws in areas such as system design, security practices, and debugging processes. The AI coding assistants struggled with complex problem-solving and often generated code that was inefficient or prone to errors.
Overall, the experience highlighted the importance of understanding when and how to leverage AI in software development. While AI can be a powerful tool for certain tasks, it is not a one-size-fits-all solution and requires human oversight and intervention to ensure quality and reliability.
To read the full blog post detailing Anand Panchal’s 30-day journey with AI coding assistants, visit Here.
