Can a Beginner Truly Use Vibe Coding to Create an App? My Experience with Cursor and Replit

Overview of My Journey

Generative AI technologies are significantly transforming the field of programming, reducing the necessity for manual coding. Various companies, including tech giants and new startups, are developing systems that simplify programming tasks.

This made me ponder whether someone like myself, who has little programming experience, could verbally guide one of these tools to develop an application.

With Nvidia's CEO stating that conversational coding in English is likely the next big thing in programming, I decided to put this theory to the test.

Experimenting with Different Tools

My experimentation was quite an adventure; tools like Cursor set up virtual environments, installed necessary libraries, and ran local servers with just a few natural language prompts.

After several attempts across different tools, I managed to execute a basic data analysis application. This initial success, however, highlighted the limitations I faced without deeper coding skills.

I found PC-based tools like Cursor redirected me to terminal windows more often than I liked, and while I am familiar with command lines, the extra steps felt cumbersome. Less patient individuals might abandon the effort at this stage.

Cloud-based solutions such as Replit posed their own challenges, like consuming credits rapidly as I attempted various modifications. Additionally, the thought of having my private data on the cloud was nerve-wracking.

Initial App Concept

The aim was to create a tool that could scrutinize word-processing files for patterns, enabling more advanced queries over my extensive collection of articles.

Using Cursor to Start the Project

Choosing Cursor as my initial tool, I installed it on my Mac without any fuss. Despite the initial daunting options presented after sign-up, I opted for the free version to test the waters.

Navigating the interface, which resembles a chat-based system, became straightforward, confirming its similarities with platforms like ChatGPT.

Cursor's environment comprises three core areas: an agent panel for entering prompts, a terminal view for advanced tasks, and a GUI preview that exhibits the app's user interface.

Initial Enthusiasm and Letdowns

At first, Cursor was remarkable—laying out project requirements I hadn’t even considered, organizing projects, and connecting to databases with ease.

However, a setback occurred when my chat history disappeared after the program restarted during library installations. Without the ability to restore this history, it rendered the tool impractical for me.

Challenges with Replit

Replit’s cloud-based operation didn’t sit well with me initially due to privacy concerns, but I proceeded for the sake of the experiment. Although initial setup was swift, I quickly exhausted the free trial limitations.

The system failed on my first major query due to data upload issues, which coupled with hitting a usage limit causing further delays.

Trying Out Visual Studio

Seeking a local development experience, I turned to Microsoft’s Visual Studio, known for its GitHub Copilot feature. Nevertheless, using it involved manually executing code snippets.

Despite eventually launching a prototype app and feeling accomplished, the solution lacked depth, centering on basic text matching rather than genuine analytical capabilities.

Exploring Lovable

Next, I experimented with Lovable, whose simplistic interface and fast setup were comparable to others but came with similar limitations on tool output.

Despite employing Gemini for more insightful text analysis, obstacles like the limitation of file format interactivity persisted.

Eventually, I paid for Lovable’s pro version, enabling further exploration with XML files and achieving a baseline-analysis application.

Concluding Thoughts

These AI tools certainly facilitate tasks beyond my ability but revealed the extent of know-how still needed to master their quirks.

Balancing productivity between local and cloud environments highlighted different challenges, such as cost management and data privacy.

While large companies can dedicate resources to optimize these tools, solo users like me face a significant workload boost.

Ultimately, I’ve gained an understanding of the complexities programmers and product developers handle and why these roles remain indispensable despite advances in automation.

The coding profession won’t become obsolete, and neither will the strategic planning essential for building capable applications.