← Back to PortfolioProof Playbook
Proof Playbook - AI Character Platform
Yes Coach
A multi-modal AI companion platform proving UX taste, system design, and technical depth from React 19 through secured AI infrastructure on Google Cloud.
Deliverables
- -Product strategy for AI-native coaching experiences
- -React 19 + Vite + Tailwind application shell with fine-grained state flows
- -Node.js + Express API backed by Firestore, Cloud Run, and Secret Manager
Core Features
- -AI Character Management - create characters, browse trending personas, favorite them, and react with emoji micro-interactions.
- -Multi-Modal Conversations - mix text, voice, generated images, video snippets, and real-time TTS so characters feel alive.
- -Conversation Management - threaded chats with resume points, session history, and progress tracking.
- -Persona System - scoped identities and guardrails per character so behaviors stay on-brief.
- -Media & Gallery - cloud storage integration that saves uploads, model outputs, and highlight reels automatically.
Technical Architecture
- -Frontend: React 19 + TypeScript + Vite + Tailwind for fast builds and ergonomic theming.
- -Backend: Node.js + Express API, Firestore data models, and Cloud Run autoscaling.
- -AI Services: Gemini, Imagen, and Veo orchestrated through a capability router.
- -Infrastructure: Entire workload deployed on Google Cloud Platform with IaC-ready config.
Key Technical Implementations
- -Secret Manager based API key vaulting and rotation utilities.
- -Bidirectional WebSocket layer powering real-time voice calls.
- -Comprehensive data modeling for characters, personas, media, and session telemetry.
- -Signed URL media pipeline for uploads and generated assets.
- -Complete API surface with 20+ documented endpoints.
Testing & Workflow
- -Frontend unit + interaction coverage through Vitest + Testing Library.
- -Backend integration suite validating every endpoint and Firestore rule.
- -Development and deployment guides that detail branching, preview builds, and production releases.
Design & Experience
- -UX principles that prioritize clarity, pacing, and delight for AI assistants.
- -Code quality standards covering component boundaries, accessibility, and design tokens.
Security & Scalability
- -Production-ready auth, audit logging, and rate-limiting considerations.
- -Horizontal scaling strategy for chat, media, and streaming workloads.
Technical Highlights
- -Demonstrates multi-modal AI UX, cloud infra, and thorough documentation in one proof.
