11/09/2024
In 2 minutes I created this with not one bit of code
Plug in APIs and you have an app that is ahead of the curb using real time data on trends across each social plafform.
First I ask the Chatgpt to act a a product team, with developers and a project manager,
Describe the app i want
Request a draft PRD document which is basically a brief on how to make it.
Copy and paste the PRD document into the new No Code Auto Developer
And in not even 2 minutes have full up and running app that just required APIs to do the prompts in the background
Here the PRD
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Trend Forecaster for Creators - MVP Product Requirements Document (PRD)
1. Project Overview
Product Name: Trend Forecaster for Creators (MVP)
Version: 0.1 (MVP)
Objective: Build an MVP within 24 hours that provides basic functionality for content creators to discover trends and get content suggestions. This MVP will focus on trend analysis and simple content suggestions.
Target Audience: Content creators, small business owners, social media marketers.
Platform: Web-based dashboard accessible via desktop.
2. Key Features (MVP)
2.1 Trend Discovery
Feature: Basic trend discovery module for Instagram and TikTok.
Functionality: Display trending hashtags and keywords based on recent posts from Instagram and TikTok.
Outputs:
A list of the top 10 trending hashtags.
Top 5 trending content formats (e.g., carousels, reels, stories).
Trending challenges or themes (e.g., a specific dance or meme format).
2.2 Content Suggestion
Feature: Simple AI-generated content suggestions based on trending topics.
Functionality: Suggest one post idea (caption and format) for each trending hashtag or content format.
Outputs:
Suggested captions that include trending hashtags.
A recommended format (carousel, video, etc.) based on the trend.
Suggestions on best posting times based on general data (no calendar integration in MVP).
2.3 Basic Content Calendar View
Feature: Display a simplified content calendar.
Functionality: Shows suggested posts and the days they are recommended to be published.
Outputs:
A basic calendar interface where users can see the next 7 days with AI-suggested post ideas.
2.4 User Input: Niche Selector
Feature: Users select their content niche (e.g., fitness, fashion, marketing).
Functionality: The app will filter trends and suggestions based on the selected niche.
Outputs:
Trend and content suggestions tailored to the selected niche.
3. User Flow
Onboarding: User logs in via email and selects their niche (e.g., fitness, fashion, or marketing).
Trend Discovery: User sees a list of trending hashtags and content types from Instagram and TikTok based on their selected niche.
Content Suggestions: The app provides one AI-generated post suggestion per trend.
Calendar: User views a basic calendar with suggested posts for the next 7 days.
Posting: Users can manually copy the suggested captions and hashtags for posting on Instagram or TikTok (no automated posting for MVP).
4. UI/UX Design (MVP)
4.1 Dashboard Layout
Navigation Bar: Simple left-hand menu with sections for "Trends," "Content Suggestions," and "Calendar."
Main Panel:
Trends: Displays the top 10 hashtags, content types, and formats.
Content Suggestions: AI-generated post suggestions based on the trends.
Calendar: A simple weekly view with post ideas.
4.2 Design Style
Colors: Clean, minimalist design using shades of white and blue.
Fonts: Simple, sans-serif fonts for readability.
Visuals: No complex charts or animations. Keep it basic for fast loading and ease of use.
5. Technical Requirements (MVP)
5.1 Backend Development
API Integration: Use public APIs for Instagram and TikTok (or web scraping if API is unavailable) to gather trending data.
AI Integration: Basic natural language processing (NLP) model for generating captions (can leverage OpenAI’s GPT or similar for caption generation).
Database: Use Firebase or a simple cloud database to store user preferences and suggested posts.
Authentication: Simple email-based login system for user authentication.
5.2 Frontend Development
Frontend Framework: React.js for quick and responsive UI.
UI Library: Use a pre-built UI component library (e.g., Material UI) for faster development.
Mobile Compatibility: Ensure responsive design for mobile view, but primary focus is desktop.
6. Development Plan (24-hour Schedule)
6.1 Hour 1-4: Wireframe and UI/UX Design
Create a basic wireframe for the dashboard.
Finalize color schemes and layout.
Develop static HTML/CSS pages for trend discovery, content suggestions, and the calendar.
6.2 Hour 5-12: Backend Development
Set up database (Firebase or AWS) to store trending data, user preferences, and post suggestions.
Integrate APIs for trending data from Instagram and TikTok.
Implement basic AI caption generation using pre-trained models (GPT-3 or other available APIs).
6.3 Hour 13-18: Frontend Development
Implement the React.js frontend based on the wireframes.
Integrate the trend discovery and content suggestion features.
Develop a basic calendar view for showing suggested posts.
6.4 Hour 19-22: User Input & Personalization
Implement niche selector to filter trends and content suggestions.
Ensure the AI suggestions are tailored to the selected niche.
6.5 Hour 23-24: Testing and Debugging
Test the entire flow, from user onboarding to content suggestion.
Fix any critical bugs and ensure the MVP is functional.
7. Risks & Mitigation
Risk: API limitations from Instagram or TikTok.
Mitigation: If APIs are restricted, implement web scraping or use Google Trends as a backup for trend data.
Risk: AI-generated content may not always be relevant or high-quality.
Mitigation: Ensure the MVP uses a simple, pre-trained model and allows users to tweak captions manually.
8. Success Metrics
User Engagement: Track how many users log in, select a niche, and interact with the trend discovery and content suggestion features.
Trend-to-Post Conversion: Measure how often users copy the AI-generated suggestions for real-world posting.
Feedback Collection: Include a simple feedback form to gather user input on what features they want in the next iteration.
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GPT Engineer Generated Project
