Can a newbie really vibe code an app? I tried Cursor and Replit to find out

2026-02-13 · Source: News and Advice on the World's Latest Innovations | ZDNET · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Novice, long

Summary

This article details an experiment by a non-programmer attempting to create a data analysis application using various AI coding tools. The author tested desktop-based tools like Cursor and Microsoft Visual Studio with GitHub Copilot, alongside cloud-based platforms such as Replit and Lovable Labs. While these tools simplified tasks like virtual environment setup and library installation, the author encountered significant challenges, including Cursor's disappearing chat history, Replit's rapid credit consumption and data handling issues, and Visual Studio's reliance on manual command-line inputs. Ultimately, a basic text analysis application was achieved using Lovable's Pro plan, integrating with Algolia and Google Gemini, but it highlighted the substantial effort still required for meaningful analysis and product design, even with AI assistance.

Key takeaway

For AI Product Managers evaluating the feasibility of "vibe coding" for non-technical users, recognize that while AI tools streamline initial development, they do not eliminate the need for deep understanding of application goals and iterative refinement. Your teams should focus on defining precise analytical functions and user experience, as AI currently automates code generation more than it automates complex problem-solving or robust product design.

Key insights

AI coding tools simplify initial setup but require programming knowledge and significant refinement for complex applications.

Principles

• AI coding shifts effort from coding to problem definition.
• Cloud-based tools incur costs and data privacy concerns.
• Desktop tools often require command-line interaction.

Method

The author used natural language prompts to describe a desired application, then iteratively refined the output and debugged issues across multiple AI coding platforms, including Cursor, Replit, Visual Studio with GitHub Copilot, and Lovable.

In practice

• Expect to manage virtual environments and libraries.
• Anticipate manual command-line tasks with desktop tools.
• Monitor credit usage on cloud-based platforms.

Topics

• AI Coding Tools
• Generative AI
• Application Development
• Natural Language Programming
• Developer Experience

Best for: Software Engineer, Prompt Engineer, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by News and Advice on the World's Latest Innovations | ZDNET.