MakendranG

Posted on Sep 14

I Built an AI Meeting Assistant in One Day Using Kiro AI 🎤

#kiro #aws #productivity #javascript

How AI-assisted development transformed a complex project into a single-day build

The Challenge 🎯

We've all been there - sitting in meetings, frantically taking notes, missing important action items, and spending hours afterward trying to remember who was supposed to do what. I wanted to build something that could automatically transcribe meetings and extract actionable insights in real-time.

Traditionally, this would be a massive undertaking requiring:

Real-time audio processing
Speech recognition integration
Natural language processing for action item detection
WebSocket architecture for live updates
Professional UI with responsive design
Comprehensive testing and documentation

Estimated time: 2-3 weeks of development

Actual time with Kiro: 1 day 🚀

What I Built ✨

The Intelligent Meeting Assistant is a web app that:

Transcribes speech in real-time using browser APIs
Automatically detects action items from natural conversation
Tracks decisions with confidence scoring
Generates meeting summaries with key highlights
Works in two modes: Demo (with sample data) and Real Speech

How Kiro Changed Everything 🤖

1. Spec-Driven Development

Instead of writing code first, I started by describing what I wanted in plain English. Kiro helped me create a comprehensive specification that became the blueprint for the entire project.

# Meeting Assistant Specification
- Real-time audio transcription with 95%+ accuracy
- Automatic speaker identification and labeling
- AI-powered content analysis for action items
- WebSocket integration for live updates

From this spec, Kiro generated the entire project architecture!

2. Intelligent Code Generation

The most impressive part? Kiro didn't just write simple functions - it created complex, production-ready systems:

Complete TypeScript Backend:

export class AudioTranscriptionService {
  private voiceProfiles: Map<string, VoiceProfile> = new Map();
  private activeLanguages: Set<string> = new Set(['en-US', 'es-ES', 'fr-FR']);

  async transcribeAudio(audioBuffer: ArrayBuffer, sessionId: string): Promise<TranscriptionSegment[]> {
    // Complex audio processing logic generated by Kiro
  }
}

Real-time WebSocket Integration:

// WebSocket connection handling
wss.on('connection', (ws) => {
    ws.on('message', (message) => {
        const data = JSON.parse(message);
        // Handle real-time transcription updates
    });
});

Dual Speech Recognition System:

// Toggle between demo and real speech modes
toggleSpeechMode() {
    this.realSpeechMode = !this.realSpeechMode;
    if (this.realSpeechMode && this.speechRecognition) {
        this.speechRecognition.start();
    }
}

3. Automated Workflows

Kiro set up automated workflows that ran throughout development:

Test-on-Save: Automatically ran tests when I saved files
Deploy-on-Push: Automated deployment pipeline
Code Quality Checks: Ensured consistent formatting and standards

Key Features That Impressed Me 🌟

Dual-Mode Operation

Demo Mode: Perfect for presentations with realistic sample data
Real Speech Mode: Live transcription using browser Speech Recognition API
One-click toggle between modes

Technical Highlights 🔧

Architecture

Frontend: Vanilla JavaScript with WebSocket integration
Backend: Express.js with TypeScript
Real-time: WebSocket for live transcription updates
AI: Browser Speech Recognition + NLP for content analysis

Performance

Sub-100ms UI responsiveness
Efficient audio processing
Cross-browser compatibility with fallbacks
Mobile-responsive design

Try It Yourself 🚀

The project is open source and ready to run:

git clone https://github.com/MakendranG/intelligent-meeting-assistant.git
cd intelligent-meeting-assistant
npm install
npm start
# Open http://localhost:3000

Quick test:

Click "Start Meeting"
Toggle to Real Speech mode (microphone button)
Say: "We need to complete the user authentication by next week"
Watch it automatically detect the action item!

🎬 Video Demo:

What This Means for Developers 💭

This project showed me that AI-assisted development isn't just about writing code faster - it's about building better software:

Before Kiro:

Weeks of architecture planning
Boilerplate code writing
Manual testing and debugging
Documentation as an afterthought

With Kiro:

Spec-driven development from day one
Production-ready code generation
Automated testing and quality assurance
Comprehensive documentation included

The Results 📊

Development Time: 1 day (vs. 2-3 weeks traditional)
Code Quality: Production-ready from first iteration
Features: Complete meeting assistant with AI analysis
Testing: Comprehensive test suite included
Documentation: Professional-grade docs generated

What's Next? 🔮

The foundation is solid, and extending it is straightforward:

OpenAI Integration: Enhanced AI analysis with GPT
Task Management: Asana, Trello, Jira integrations
Calendar Sync: Automatic meeting scheduling
Mobile Apps: Native iOS and Android versions

Key Takeaways 💡

Start with specs, not code - Clear requirements lead to better architecture
AI-assisted development is transformative - Not just faster, but better quality
Focus on the problem, not the implementation - Let AI handle the technical details
Iterate through conversation - Natural language is the new programming interface

Try Kiro for Your Next Project 🎯

If you're working on complex projects that would normally take weeks, consider trying AI-assisted development. The combination of human creativity and AI capability is genuinely game-changing.

What would you build if development time wasn't a constraint?

This project was built for the Code with Kiro Hackathon. The complete source code, including all Kiro specifications and workflows, is available on GitHub.

Tags: #ai #productivity #javascript #typescript #webdev #kiro #speechrecognition #meetings

Have you tried AI-assisted development? What's your experience been like? Drop a comment below! 👇

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