Sled

Product Introduction

1. Definition: Sled is a voice interface application (technical category: AI-powered coding assistant tool) that enables remote interaction with local coding agents (e.g., Claude Code, OpenAI Codex, Gemini CLI) via mobile devices.
2. Core Value Proposition: It eliminates workflow interruptions when developers step away from their desks by providing secure, voice-controlled access to local coding agents, ensuring continuous productivity without compromising code security.

Main Features

1. Voice Input/Output:
   • Uses browser-based speech recognition to transcribe voice commands into text inputs for coding agents. Handles technical syntax (camelCase, function names) accurately.
   • Converts agent responses into synthesized speech (300+ voice options) via Layercode’s processing (audio discarded post-conversion).
2. Local Execution Security:
   • Coding agents run locally on the user’s machine; code never leaves the device. Connects to mobile via encrypted tunnels (Tailscale or ngrok) with optional basic auth.
3. Remote Accessibility:
   • Browser-based interface allows access from any location (couch, outdoors) without moving the host machine. Supports hands-free operation via AirPods/headphones.
4. Real-Time Notifications:
   • Sends push alerts to mobile when agents complete tasks or encounter errors, with spoken summaries of actions taken.
5. Open-Source Flexibility:
   • Self-hostable (MIT license) via GitHub; compatible with macOS, Linux, and Windows. Setup uses pnpm for dependency management and Prisma for database migrations.

Problems Solved

1. Pain Point: Coding agents idle during developer absence (e.g., breaks, walks), wasting compute resources and delaying workflows due to required input every 10-60 minutes.
2. Target Audience:
   • AI Developer Teams using Claude/Codex/Gemini CLI for rapid prototyping.
   • Remote Developers needing flexibility to work away from desks.
   • Solo Engineers managing long-running agents while multitasking.
3. Use Cases:
   • Debugging code while walking outdoors.
   • Iterating on agent outputs from a couch/bed.
   • Monitoring automated tasks during commutes.

Unique Advantages

1. Differentiation: Unlike cloud-based alternatives (e.g., GitHub Copilot remote), Sled prioritizes on-device code execution and zero data retention. Outperforms terminal-only tools by enabling bidirectional voice workflows.
2. Key Innovation: Secure tunneling integration (Tailscale/ngrok) with low-latency voice processing, enabling real-time agent control without local code exposure.

Frequently Asked Questions (FAQ)

1. Is Sled secure for sensitive codebases?
   Yes—agents run locally, and audio data is ephemeral. Use Tailscale’s zero-trust security or ngrok with --basic-auth to prevent unauthorized access.
2. Which coding agents does Sled support?
   Sled integrates with Claude Code, OpenAI Codex, and Gemini CLI. Open-source adaptability allows custom agent integration.
3. Can Sled work without internet?
   No—voice processing requires internet, but agent execution remains local. Disable voice output in settings for text-only local responses.
4. How difficult is Sled’s setup?
   Requires 5 minutes: clone GitHub repo, run pnpm install && pnpm migrate, and start the server. Pre-requisites include Tailscale/ngrok and a local coding agent.
5. Does Sled store my voice data?
   No—audio is processed in real-time via Layercode and discarded immediately after speech synthesis.