Vibe Coding: Conversational Software Development — Part 1: Introduction

Since I started coding, I have seen developer communities strive to make programming more human-readable, almost like writing in English or a preferred language. Many modern languages introduced syntactic sugar to make code more intuitive and conversational. These efforts have made significant advancements, but now, we are witnessing something far more transformative.

Natural language can now be translated directly into functional software. The concept is trending and is widely referred to as vibe coding. It is an AI-first approach for rapid software development. Let me try to explain the idea with the help of a step-by-step diagram that I have added below. As the picture shows, you put down your thoughts or overall idea as a prompt. You direct what step you want to achieve or what your end goal is. The chat-based AI works on your prompt and comes up with a generated code. You preview the output of the code and can fine-tune it further. Once you are happy, you put that code into your server.

My Exploration of Vibe Coding

I recently started to explore this new notion of coding. While the definition makes it look straightforward, its applications vary depending on what you want to achieve and the tools you use. So far, I have seen it manifesting in several forms based on what you want to get out of it. You can perform things like:

• Rapid prototyping – This is my favourite use case. It can be used for a quick UI mock-up or lightweight programs to validate a hypothesis.
• Automating repetitive tasks – Developers constantly look for ways to reduce toil. It can generate scripts or small programs that can come in handy.
• Experimentation – You can ask how a library works, generate example usage, or compare multiple implementations — all in minutes.
• Problem solving and debugging – Something I use for debugging obscure issues. Although, I am not convinced that it is saving time.

Shifting Focus from Syntax to Problem Solving

In my opinion, vibe coding shifts your focus from typing every bracket or declaring every variable to problem solving. You concentrate on delivering features instead of obsessing over implementation details.

You can use AI tools to bounce off ideas, look for alternative implementations, and race through your development. But be cautious, at the end of the day, it is still your code. You are responsible for verifying it, testing it, and making it production-ready. You must critically review the code whether all edge cases are handled and make any tweaks, if needed.

AI-Driven Tools

As I mentioned earlier, it does not matter whether you are a new developer or a seasoned programmer — you can leverage vibe coding to your advantage. Just like you would hire the right candidate for a specific role, you need to use the right AI platform for the right use case. 

In this series of blogs, I intend to explore several available options and categorize them based on how and where they can be used effectively.

Easy Entry: Chat-Based Builders

Let us start with the most accessible option, which is chat-based builders. If you are new to all this, the easiest way to get started is by using conversational AI tools. All you need is a well-structured prompt. 

These tools gained traction with the popularity of Anthropic’s Claude artefact. It lets you build a live dashboard, tools, and interfaces directly in the chat window. 

Try prompting:

Create a dashboard for analysing social media posts performance using most relevant visualisation from D3.

Claude will generate a live preview that you can tweak, inspect, and even publish. Below is a screenshot of the dashboard that it generated for me.

Tools like ChatGPT, Google Gemini, and Microsoft Copilot offer similar features. You can generate fully functional code with simple natural language prompts. 

Try something fun like 

Build a simple recipe idea generator. I want to input a few ingredients I have, and it suggests a random recipe. I should be able to save recipes I like and add my own custom recipes

You will get a working prototype that you can experiment with or customize further. Here is another screenshot — this one is from ChatGPT.

You can execute the same prompt on Google Gemini and Microsoft Copilot to compare the results, and you may share in the comments.

What Is Next

In part 2 of the series, I will continue this discussion and add some of my experiences of working with these tools.