AI agents spend hours in aesthetic feedback loop, unable to decode qualitative shader instructions
Description
A developer worked with Claude and GPT on Three.js 3D visualizations with custom shaders and particle systems. When given qualitative aesthetic instructions ('make it more fluid', 'feel more organic', 'that's not what I mean by porous'), the agents produced technically valid code but could not converge on the intended visual result. The developer spent hours watching agents iterate in circles, each producing technically correct but aesthetically wrong outputs. The author diagnoses the failure as a missing 'language game'—agents and humans lack a shared referential framework for aesthetic concepts, so vague natural language gets optimized literally.
Instruction Given
Iterative aesthetic refinement: "make it more fluid", "feel more organic", "more porous"
Expected Behavior
Visual convergence toward intended aesthetic over iterations
Actual Behavior
Repeated technically-valid but aesthetically-misaligned outputs, hours of circular iteration with no convergence
Impact / Damage
Hours of developer time wasted on circular iterations; project stalled