Frontend Development Cheat Code for DMC Ai Prompting

Dash Python
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:bullseye: AI Prompting Guide for Beautiful Dash UIs with Mantine Components - Video + Comprehensive Resource

Hey Dash community! :waving_hand:

I’ve been working on something that I think could be a game-changer for anyone using AI assistants (ChatGPT, Claude, Copilot, etc.) to help build Dash applications with Dash Mantine Components with increased accuracy.

The Problem

We’ve all been there - you ask AI to help create a Dash UI and you get:

  • Generic layouts that look like they’re from 2010
  • Inconsistent styling across components
  • Poor use of spacing and visual hierarchy
  • Components that technically work but don’t follow UI/UX best practices

The Solution

I’ve created a comprehensive guide that essentially teaches AI assistants how to build clean, useful, and aesthetically pleasing Dash applications using DMC. Think of it as “project knowledge” that transforms your AI from a code generator into a UI/UX-aware developer.

:television: Video Overview

:page_facing_up: The Resource

Download the guide here: GEO🗺️Index

This 65+ page markdown file includes:

:white_check_mark: Declarative AI Directives - Specific instructions mapping UI/UX principles to exact DMC components and props :white_check_mark: Complete Theming System - How to instruct AI to create cohesive color systems, typography, spacing, and global styles :white_check_mark: Layout Patterns - Responsive grids, proper component composition, visual hierarchy :white_check_mark: Data Display Best Practices - When to use tables vs cards vs lists, with specific prop configurations :white_check_mark: Advanced Patterns - Empty states, error handling, accessibility, interaction cost optimization :white_check_mark: DMC v1.3.0 Documentation - Updated component references with all the latest features

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  • Example of using this prompt to create a Yelp App Clone Ui Ux Design (Claude 4)

Who This Helps

  • Developers using AI assistants - Get 10x better UI outputs
  • Teams standardizing their UI - Use this as a design system reference
  • Anyone learning DMC - It’s also a comprehensive component guide
  • Solo developers - Build professional UIs without a designer

How to Use It

  1. Add the .md file to your AI assistant’s project knowledge/context
  2. Ask it to build Dash interfaces following the DMC UI/UX guidelines
  3. Watch as it generates interfaces with proper theming, spacing, hierarchy, and component selection

The difference is night and day - instead of telling AI “make it look good,” you’re giving it a complete framework for how to make it look good.

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  • Example of using this .md file to create a trading app (claude 4)

Community Contribution

This resource is free for the community to use and improve. If you find it helpful, I’d love to hear about your experiences or any suggestions for making it even better.

Let’s raise the bar for AI-generated Dash UIs app design together! :rocket:

5 Likes
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Thanks for taking the time to share your findings with us @PipInstallPython!

I would consider your approach as “manual” vibe coding.

  • First you let AI generate a specifications file (the output of Gemini)
  • You use that Gemini file as input for the Developer (Claude).

Did you try Cursor or Windsurf? It’s pretty much what you are doing but in one IDE.

Did you come to a conclusion what LLM to use for each specific task? Why did you use Gemini for the specifications file, Claude for coding and not something different?

AI is getting pretty crazy.

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Yeah i agree, think “manual vibe coding” is a good explanation.

Theirs a lot of tedious moments in coding, think designing the layout is one of those things that ai will never get perfect but initial ai rough drafts can speed up the time drastically to primarily focus on the specifc things that need our direct touch rather than the babysitting the ui.

For me Its more about figuring best practices to managing it than coding myself. Its good that i know how to code in dash, python and some react / javascript because when a response doesnt work its usually just a few manual tweaks to get it back on track.

For me personally i haven’t tried cursor or windsurf but i have used pycharms ai and copilot in my ide. But i find myself growingly concerned with granting ai access to a terminal and my entire system. Primarily using it in the browser isolated chat at this point.

As for what LLM to use for specific tasks its changed as ive learned about the strengths and weaknesses of each. I used gemini as it has the largest amount of output tokens. Deep research tool is really good at pulling a ton of sources and drafting the .md file. But for actual building clean code, claude for coding has changed my career. Im building stuff and solving problems that i honestly couldnt even 6 months ago..

Lastly, I dont think crazy is a strong enough word to describe the expodential curve ai is on.. this is the end and the beginning all wrapped up in a package that will change everything about our world.

1 Like
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I feel the same about giving an AI tool access to my terminal. I usually have the same workflow as you, hence my question concerning which LLM to use. Anyways, I’m going off topic, but I could talk about this for days,

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This is an interesting discussion and I’d love to hear more… would you like to start a new topic? I’d like to learn more about how people are using AI to make dash apps.

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Sure, like @AIMPED this is a topic I could talk about for days :joy: