fixkey.ai - LLM Writing Assistant Contributions

The Context

I’ve been contributing to fixkey.ai, a macOS LLM-driven writing assistant, at two key points in its development. First in 2023 helping with the initial UI, then returning in 2025 to implement audio transcription and hardware change detection.

These focused contributions leveraged my deep macOS expertise to solve specific technical challenges.

Technical Challenges

Initial UI Development (2023)

• Designed native macOS interface patterns
• Implemented AppKit-specific behaviors for system integration

Audio Transcription System (2025)

• Implemented Core Audio integration for voice input
• Handled microphone permissions and privacy
• Created robust audio pipeline for real-time processing
• Responding to hardware changes (plugging/unplugging microphones)

System Integration

• Deep macOS integration for seamless operation
• Accessibility API usage for text manipulation
• Performance optimization for background operation

Team Dynamics

Working with the fixkey team involved:

• Quick, focused work on specific features
• Asynchronous collaboration with the solo founder

Personal Reflections

These intermittent contributions to fixkey highlight the value of specialized expertise. Rather than being a full-time team member, I could drop in, solve specific macOS challenges, and hand off clean, maintainable code.

Returning after two years revealed interesting lessons about rapid product evolution. The codebase had grown significantly, with heavy use of AI-assisted development to accelerate feature delivery. This presented unique challenges – the AI-generated code worked in isolation but lacked cohesive architecture. Small, incremental generations had created gaps that revealed the size of LLM context windows that needed bridging.

My 2025 work became about more than just adding audio features. It was an opportunity to introduce sustainable patterns and help establish architectural guidelines that could support continued growth. It’s a reminder that while AI can accelerate development, human expertise remains crucial for maintaining code health and ensuring long-term maintainability.

Impact

My contributions helped fixkey:

• Launch with a polished, native macOS experience
• Add voice input capabilities that feel truly integrated
• Maintain high performance despite complex LLM operations
• Stand out in a crowded field of AI writing tools

The project demonstrates how focused expertise can accelerate product development, allowing the core team to focus on LLM integration while I handled platform-specific challenges.