💻 Coding & Development
Kanban Board
Example outputs
Here is what ChatGPT, Claude, and Gemini typically return for this prompt:
I'll create a comprehensive Kanban board application for you! The implementation will feature drag-and-drop functionality using the HTML5 Drag and Drop API, with smooth CSS transitions for card movements. I'll structure it with a main board container, draggable cards with metadata (title, description, labels, due dates, priority), and localStorage integration for data persistence. The design will be fully responsive using CSS Grid and Flexbox, with a clean interface that includes modal dialogs for card editing, a color picker for themes, and keyboard shortcuts (like 'N' for new card, 'E' for edit).
I'd be happy to help you build this Kanban board. I should note that this is quite a comprehensive project that will require several interconnected components. I'll provide you with a modular structure using vanilla JavaScript with clear separation of concerns—a Board class for state management, a DragDrop handler for card movement, and separate modules for persistence and UI rendering. For the drag-and-drop, I'll use the native HTML5 API with visual feedback during dragging, though you might want to consider a library like SortableJS for more complex scenarios.
This Kanban board implementation uses the HTML5 Drag and Drop API with `dragstart`, `dragover`, and `drop` event listeners for card movement. The application employs a Model-View-Controller architecture with localStorage for data persistence (note: localStorage has a 5-10MB limit depending on browser). Cards are represented as objects with properties for title, description, assignee, labels, dueDate, and priority. The responsive design uses CSS Grid with `auto-fit` and `minmax()` for column layout, with media queries for mobile optimization at breakpoints of 768px and 480px.
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
Claude Opus 4 and Sonnet 4.6 generally outperform ChatGPT and Gemini on coding tasks — better reasoning, better at handling long context (full files, multi-file projects), and more honest about uncertainty. ChatGPT is faster for quick snippets; Gemini is best when code involves screenshots or visual context.
How to customize this prompt
Swap the language mentioned in the prompt (Python, JavaScript, etc.) for whichever stack you're on. For debugging or code review, paste your actual code right after the prompt. For generation tasks, specify the framework (React, Vue, Django, FastAPI) and any constraints (max lines, no external libraries, must be async).
Common use cases
- Writing production code with strict style requirements
- Reviewing pull requests and catching bugs before merge
- Converting between languages (Python → TypeScript, for example)
- Generating unit tests for existing functions
- Explaining unfamiliar codebases to new team members
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).