AS-Flow AI – Next-Gen Productivity with Contextual AI

Source: Dev.to

What I Built

I built AS-Flow AI, a premium cross‑platform productivity application designed to help users enter deep‑work states instantly. It solves the problem of fragmented focus by combining:

• Context‑Aware Focus Modes – Ultra‑realistic immersive environments (Rain, Beach, Fire, Space) that boost concentration.
• AI‑Driven Planning – An intelligent assistant that builds schedules based on user energy levels.
• Seamless Cross‑Platform Experience – Works on desktop and mobile web with an app‑like feel.

Tech Stack

• Core: Next.js 14 (App Router), React, TypeScript
• Styling: Tailwind CSS + Glassmorphism UI
• AI: Contextual AI Agents (Claude) + Local Logic
• State: React Context + Persistent Storage

Demo

🚀 Live Application
https://github.com/AsamaeS/AS-Flow-AI

Screenshots

Test Credentials

Email: asmae@focusflow.ai
Password: demo123

AI Tooling in Action

Building AS‑Flow AI using Claude (Antigravity) accelerated development massively.

⚡ 10× Faster Feature Implementation

Example request:
“Add a Fire focus mode with crackling audio and a realistic flame animation.”

AI Agent actions:

• Parsed the project structure (src/data/focus-modes.ts)
• Added the new mode
• Retrieved a royalty‑free audio source
• Generated UI code

⏱️ Time taken: 3 minutes (vs. ~1 hour without AI)

🐛 Zero‑Shot Bug Fixing

Critical error: useLanguage must be used within LanguageProvider

AI actions:

• Analyzed the entire component tree
• Detected the provider wrapping issue in layout.tsx
• Implemented a hydration‑safe fix with suppressHydrationWarning

⏱️ Time saved: 2–3 hours

Using App MCP and Uno Platform MCP

Even though AS‑Flow AI uses Next.js, the project follows the App MCP philosophy, enabling the AI to understand the full application context.

🧠 App Context Awareness

The AI Agent knew:

• The tech stack (Tailwind, Lucide)
• The folder structure (src/app/dashboard/...)
• Where to place new files correctly

It could apply rebranding to “AS‑Flow AI” across 10+ files.

🛠️ AI‑Guided Architecture

The AI acted like an architect:

• Recommended extracting FocusModeCard as a reusable component
• Ensured use client boundaries for the Audio Player
• Created a clean service layer for persistent storage

This mirrors the guidance of Uno Platform MCP—AI that understands the full app context.

Cross‑Platform Reach

AS‑Flow AI runs everywhere:

• Desktop → 4‑column optimized dashboard
• Mobile → Single‑column responsive layout
• Web → Works instantly in any browser
• Auto Theme → Detects OS dark/light mode

Development Experience

Surprise #1 — Real Pair Programmer

It felt like working with a senior engineer.
Example: “Fix the sidebar padding.”
The AI edited the correct file (Sidebar.tsx) and the correct class (p-4).

Surprise #2 — Continuous Momentum

AI handled:

• Boilerplate
• Types
• i18n dictionaries
• Layout issues
• Hydration warnings

This allowed me to focus on design and user experience.

Outcome

I built a production‑ready, multi‑language, dark‑mode productivity platform in under 2 days—normally a multi‑week project.

Built with ❤️ by Asmae using Contextual AI Acceleration