Hi everyone,
I’ve been exploring a concept I’m calling AI-Controlled Party: a way to use AI as a kind of “show director” for live events, while keeping TouchDesigner as the deterministic real-time engine.
The idea is not to let an LLM directly control everything on stage. Instead, AI would operate at a higher level: suggesting or selecting pre-approved cues, changing the visual mood, reacting to show context, drafting announcements, or helping the operator navigate a live visual system.
TouchDesigner would still handle the actual real-time execution: visuals, audio-reactive systems, cue playback, dashboards, mappings, and operator controls.
I’m building this around my tool, TDMCP, which connects AI assistants to TouchDesigner workflows:
https://pantani.github.io/tdmcp/guide/ai-controlled-party
Right now, this is still a concept / dry-run pattern, not a fully validated live production system. The current direction is based on a safer architecture:
AI input → show intent → policy decision → approval queue or dry-run plan → TouchDesigner / TDMCP execution only through operator-safe mappings.
For example, AI could request a pre-approved cue like band_intro, suggest a mood change, or queue a fog request for operator approval. More hazardous actions such as lasers, moving heads, blackout, PA control, or audio routing should remain blocked or operator-only by default.
I’m especially interested in feedback from the TouchDesigner community:
How would you approach this kind of AI-assisted show control?
Would you use it only for visuals, or also for cueing, announcements, dashboards, and rehearsal workflows?
What safety boundaries would you consider essential?
Do you see this as a useful direction for live events, clubs, installations, performances, or VJ workflows?
Would love to hear what you think.
Thanks!
Pantani