Dynamic Low-Code Flashcards Widget Using AI

Learn how to build a dynamic low-code HTML flashcard widget powered by Google Sheets using ChatGPT. Create dynamic, searchable content with ease.

Creating interactive tools doesn’t have to be time-consuming or require a complex tech stack. In this post, I’ll walk you through how I created a dynamic Flashcards widget in minutes, using nothing but natural language prompts to ChatGPT.

As a product manager who is not a developer, I often know what I want to build and why — but coding it myself can be a challenge. However, with tools like ChatGPT (Gemini, Claude, etc), creating simple, useful widgets like this one is now within reach for anyone.

Before trying ChatGPT, I explored several WordPress plugins for building a flashcard-style experience. Many were clunky, lacked spreadsheet import support, or required paid upgrades to unlock core features. That’s when I turned to ChatGPT for a cleaner and faster approach. I had a working version running in under an hour.

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The Goal

Build a simple browser-based flashcard widget that:

• Displays AI terms and their definitions
• Allows users to shuffle and cycle through cards
• Filters by knowledge level (Beginner, Intermediate, Advanced)
• Is mobile-responsive with a toggle-based UI
• Pulls all term data dynamically from an online source (in this case, a Google Sheet in my drive)

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Prompts and Planning

The conversation started with this:

"Can you create an HTML app that helps people learn AI terminologies? The layout will include 2 sections - one to show a term and one for its description."

From there, I kept building on the idea — adding level filters, a search feature, and shuffle functionality. For every increment, I just asked ChatGPT how to do it and to update the code. It handled everything smoothly. I also wanted the widget to work well on my WordPress site, which meant keeping it self-contained and lightweight.

ChatGPT generated a single HTML file that included:

• Frontend layout using HTML + Tailwind CSS
• Integration logic for reading from a Google Sheet
• Responsive UI and interactive behavior

The entire development process felt more like a design collaboration than a technical build. I do recognize that scaling or extending this for an business use case would require experienced developers. But for this focused use case, the solution checked all the right boxes.

Note 1 : You don’t need to know Tailwind CSS or any coding. Since the goal is to create a single file app. All HTML, CSS and JavaScript will be in a single page that can be copied to create an HTML page.

Note 2 : If you want a more traditional HTML app with separate HTML, CSS and JS files, you can simply ask for it.

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Connecting to Google Sheets

I wanted to manage the flashcard content in a spreadsheet — and ChatGPT helped me do exactly that. Here’s how:

1. Create a Google Sheet with three columns: Term, Definition, Level
2. Publish it to the web via File > Share > Publish to web > CSV
3. Plug the public CSV link into a fetch() request:

const response = await fetch("https://docs.google.com/spreadsheets/d/e/.../pub?output=csv");
const csvText = await response.text();

To parse the data correctly, ChatGPT suggested using PapaParse:

const parsed = Papa.parse(csvText, { header: true });

Caution : Do not use this method for sensitive data since this publishes your data to public, even though not editable, it is readable by anyone. Use Google Sheets API or host data yourself for restricted access.

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HTML & Layout Structure

The layout is clean, responsive, and uses Tailwind:

• Search Panel: Search bar + result list
• Flashcard Panel: One term at a time + shuffle + level filter

<div class="flex flex-col lg:flex-row gap-6 min-h-[600px] items-stretch">
  <div id="search-panel">...</div>
  <div id="flashcard-panel">...</div>
</div>

On mobile, I asked ChatGPT to add tabs so users can toggle between the two sections.

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Troubleshooting (ChatGPT Was Key)

Along the way, I ran into a few common issues — each resolved quickly with a simple prompt:

• CSV header mismatch: My spreadsheet had column names with capital letters. The code expected lowercase. ChatGPT spotted the issue and updated the parsing logic.
• Layout height mismatch: The search panel grew taller than the flashcard one. I asked, “Make both panels the same height.” ChatGPT adjusted the layout using flex, h-full, and max-h utilities. There’s still a slight variance when search results overflow, but it’s much cleaner now.
• JavaScript missing: At one point I accidentally deleted the script. ChatGPT regenerated the full logic within seconds.
• Version control & Preview: I used the basic revert for rollbacks a few times when ChatGPT went on a tangent and preview feature for reviewing changes quickly.

Note 3 : To improve communication, share screenshots showing the issue. In some cases, annotating the image to visually indicate what is needed helps troubleshoot faster and effective.

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Establishing Transparency & Consistency

Using AI to write code is exciting — but we still need clear logic and reasoning. For example, our flashcards were categorized by level: Beginner, Intermediate, Advanced. As a product manager, I wanted to ensure the criteria for these levels were clearly defined.

I first asked ChatGPT to help categorize the terms, then asked it to explain its reasoning. I reviewed and tweaked the criteria and asked ChatGPT to re-categorize the list accordingly. Once finalized, I saved the categorization rules for future reference so that any new AI assistant or conversation can apply the same standards. You can view the same below the widgets on the Glossary page.

This is exactly the kind of rules & standards that can be saved as organization knowledge and leveraged using RAG.

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Updates to the original prompt

Initially, I wasn’t sure what was possible. So I took small steps in my prompts. Now that I’ve seen what ChatGPT can do, here’s the kind of prompt I’d start with next time:

You are an expert application developer. Your primary objective is to solve user problems by creating robust software solutions that create a delightful user experience. 

I want you to build a fun browser-based widget for [Objective]. I should be able to run it directly on my browser. The project should be responsive and work across mobile and desktop. Follow best practices to create a Robust software solution, including clean and modular code. Leverage [link or source] as the data source. Make sure the output can run in a browser without a build step.

You will seek clarifications on requirements when unclear. You will advice me on best practices and potential options in lay man terms to ensure your primary objective is met. 

Note 4 : You can share screenshots or even a hand drawn sketch to help guide the layout design.

Note 5 : You can start without a connected data source (sample data – hard coded) and then leverage an appropriate source once you have ironed out the experience.

Caution : Using readymade one shot prompts is enticing, however, in a creative process it is always better to start small and iterate as you go, especially if you plan to learn the tool. Ask questions and learn better ways to do things. In a fast evolving landscape were new capabilities emerge frequently, a rigidly crafted prompt does more harm than good.

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Final Functionality

• Real-time search across all terms
• Click-to-view term definitions in the flashcard
• Shuffle and next buttons for discovery
• Level selector for filtering content

All built with no backend, no frameworks, and no third-party plugins. Once done I copied the entire code into a Custom code block on HTML.

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This flashcard widget is a great example of how easy it’s become to build functional apps — not by coding line-by-line, but by collaborating with AI. ChatGPT made the process feel like I had a design and engineering partner rolled into one.

In the Age of AI, product managers have the opportunity to lead the no-code, low-code revolution. With a clear vision and the right tools, we can all build the tools we imagine with a simple conversation.