The AI MVP Development Process

This is the flow we use for developing an AI-focused MVP, with special consideration for voice, video and LLM integrations.

We scope the requirements for the MVP, typically limiting to 1-2 core AI-powered features.

The process

1. Create technical product requirement document (PRD), with detailed AI integration specifications
2. Here are 6 important flows we focus on:
   1. User journeys: How users interact with AI features and the overall app flow
   2. The UI screens: Descriptions and visual mockups including AI interaction interfaces
   3. Brand color palette: The app’s visual identity and AI feature styling
   4. AI Architecture planning: How different AI services connect (ElevenLabs, Replicate, AssemblyAI, Flux)
   5. Feature implementation: Implementation of core AI features and their integration
   6. Handover of assets: Transfer repository, AI service credentials, and production environment setup

Tentative Timelines

1. 1st week: Planning, requirements gathering, UI/UX for AI features, technical PRD creation
2. 2nd week: Setting up AI service integrations (ElevenLabs, Replicate, AssemblyAI), basic UI implementation
3. 3rd week: Core feature 1 implementation with AI integration testing
4. 4th week: Core feature 2 implementation, AI pipeline optimization
5. 5th week: AI model performance optimization, error handling, final testing, UI polish, production deployment and monitoring
6. 6th week: Handover of assets, repository, AI service credentials, production environment setup

For faster urgent delivery in 4 weeks, we involve more devs

Tech stack

1. Next.js: Full-stack framework for AI-powered applications
2. Tailwind: Styling and responsive AI interfaces
3. Supabase: Backend database and file storage for AI assets
4. Vercel: Production hosting with edge functions for AI processing
5. Typescript: Type-safe AI integration development
6. AI Services:
   • ElevenLabs: Voice synthesis and cloning
   • Replicate: Video generation and processing
   • AssemblyAI: Speech recognition and analysis
   • Flux: AI workflow orchestration

General MVP Features

Based on requirements, we implement these AI-focused features:

1. AI Core Features
   • Voice synthesis and cloning with ElevenLabs
   • Video generation/editing with Replicate
   • Speech-to-text with AssemblyAI
   • AI workflow management with Flux
   • LLM integration (ChatGPT, Claude) as needed
2. Payments - Stripe/Lemonsqueezy for usage-based AI feature billing
3. SEO - Optimization for AI-related keywords and features
4. Authentication - Secure access to AI features
5. Landing page - Showcase AI capabilities with interactive demos

Note: Timeline may extend based on AI model complexity and integration requirements. Additional time might be needed for model training, testing, and optimization. Regular communication is maintained for AI-specific challenges and solutions.

If you have any questions about AI integrations or need clarification on the process, please don’t hesitate to reach out!