LiveIn5

Building Browser Video Tools with AI: Lessons Learned

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My AI Development Journey

Creating a fully client-side video recording and streaming tool with Claude Code

The Breakthrough: LiveIn5

After evaluating AI for browser-based video tools for a while, Claude Code finally delivered an outcome I'm happy with. The result is LiveIn5, a complete video recording and streaming solution that:

  • • Supports webcams, screen shares, local videos and audio
  • • Records to browser's IndexedDB as chunks (crash-resistant)
  • • Streams to Twitch via WebRTC's WHIP protocol
  • • Just 3 files: index.html, styles.css, script.js
  • • No server required - everything runs locally

Tested primarily on desktop and mobile Chrome (including dual front/back camera streaming)

6 Essential Tips for AI-Assisted Development

Based on my experience switching from chat interfaces to Claude Code in WSL with VS Code

1

Start with the Bare Minimum

Begin with simple, focused prompts rather than detailed project plans.

Example prompt:

"Help me build a browser-based video recording tool that uses a HTML canvas and allows me to add my webcam and a screenshare as a main feed or a picture-in-picture feed"

This simple prompt eventually became LiveIn5

Full project plans and detailed component instructions tend to confuse the AI quickly.

2

Avoid Complex Libraries Initially

AI excels with native solutions over external libraries like PixiJS. When you do need libraries, it's better at converting existing native implementations than writing from scratch.

Pro tip: Get it working with native APIs first, then ask to convert to your preferred library
3

Fix Visual Issues Yourself

AI struggles with aspect ratios and minor CSS imperfections. You'll save time fixing these manually rather than going back and forth.

Still vastly better than ChatGPT's errors from a year ago (and current ones on rare attempts).

4

Start Fresh When It Gets Complicated

If the code becomes unwieldy, restart with lessons learned. Include successful details from previous attempts in your new instructions.

This approach results in cleaner code and less debugging time.

5

Use Solid Reference Links

For complex implementations, provide specific tutorials or documentation links. This ensures consistent, reliable results. 

WHIP Streaming to Twitch:
dev.to/dolbyio/how-to-broadcast-a-webrtc-stream-to-twitch-7fa
Hand-tracking with TensorFlow.js:
getstream.io/blog/tensorflow-gesture-recognition/
6

Interrupt When Things Go Wrong

Stop the AI when you see it heading down the wrong path. Ask it to roll back and try again rather than letting it dig deeper into problematic code.

Both you and the AI will lose track if you let it continue fixing broken approaches

Key Takeaway

Claude Code in a proper development environment (WSL + VS Code) has been a game-changer for complex browser-based projects like LiveIn5. The key is knowing when to guide, when to restart, and when to step in yourself.