Developed a comprehensive Next.js-based prompt management application with full CRUD operations, import/export capabilities, variable templating, and modern UI components for managing AI prompts with advanced features.
Why Care
This application provides a complete solution for teams working with AI prompts, enabling efficient creation, organization, and iteration of prompt templates. The modular architecture and export/import functionality make it suitable for collaborative workflows and prompt versioning, while the variable templating system supports dynamic prompt generation for different use cases.
Implementation
Implemented an ultra-cool splash screen with modern CSS animations and enhanced the PerplexityConfig component with custom properties generation capabilities for AI-powered record augmentation.
Why Care
The splash screen creates a professional first impression with engaging animations that showcase the app's core workflow. The custom properties feature significantly expands the AI augmentation capabilities, allowing users to define specific data points they want generated for each record, making the tool much more flexible and powerful for business intelligence workflows.
Implementation
Reorganized export functionality to centralize it on the Export page and added individual loading animations for record augmentation.
Why Care
These changes improve user experience by providing clearer separation of concerns between record management and export operations, while adding visual feedback during AI augmentation processes.
Implementation
Implemented a complete three-phase Data Augmenter application using Next.js 14, featuring CSV import/export, AI-powered data augmentation with Perplexity AI integration, and comprehensive record management with responsive design.
Why Care
This establishes a scalable foundation for AI-powered data processing workflows, demonstrating modern React/Next.js best practices with a clear three-phase architecture (Import → Augment → Export) that can be extended for enterprise data enhancement needs.
Implementation
Overview
This document provides a comprehensive analysis of the Augment-It codebase, which is a customer data management application with AI capabilities. The application is built using React, TypeScript, Vite, Zustand, and Supabase.
Why Care?
This application provides a complete workflow to augment data records with AI, albiet limited services available to start. The functionality make it suitable for iterating a data augmentation workflow on a long list of customer records, individually or in batches.