DMX via AI
Using Claude to generate QLC+ lighting cues from natural language.
The Challenge
The Problem
Programming DMX lighting cues is tedious and technical. Wondered if AI could help translate 'make it look like a sunset' into actual fixture commands.
Why I Took This On
Pure curiosity. Seemed impossible, which made it interesting.
Constraints
QLC+ has a specific XML format for scenes and cues. AI output has to be precise or it breaks.
The Process
Initial Approach
Fed Claude the QLC+ documentation and tried direct generation of XML files.
What Went Wrong
Raw XML generation was too error-prone. One wrong character and the whole file corrupts.
Breakthroughs
Built a translation layer that converts AI suggestions into validated QLC+ format. AI handles creative intent, code handles precision.
What I Learned
Skills Gained
Unexpected Discoveries
AI is surprisingly good at understanding lighting mood words. Less good at precise technical output without scaffolding.
What I'd Do Differently
Would have built the validation layer first instead of debugging corrupted XML files.
Where It Stands Now
Current State
Working prototype. Can generate basic scenes and chases from descriptions.
What's Next
Want to add beat detection for music-reactive cue generation.
The Bigger Picture
Direct application to venue work. If this matures, it dramatically speeds up show programming.
The Impact
Personal Impact
A potentially game-changing tool for live production work. Also a lot of DMX knowledge I didn't have before.
