GoKawiilEx-OpenAI designer details evolution of random gradient generation techniques
A designer who worked alongside OpenAI's Ben Barry recounts building multiple algorithms for generating random gradient art, starting from Barry's 2017 four-corner color interpolation. The author later developed heightmap-based gradients using smoothed Perlin noise combined with randomized color scales, and separately built a lightweight layered radial gradient system that powered OpenAI's homepage in 2019 using an 85-byte image.
GoKawiil's interpretation of the reporting above, not reported fact.
The piece offers a rare inside look at how a major AI company's visual brand identity was engineered, showing that even seemingly simple design elements involved careful procedural generation work. It's a useful case study for designers and engineers on balancing visual richness with performance constraints on the web.
- OpenAI's original gradient branding began with a simple four-corner color interpolation by designer Ben Barry in 2017.
- The author later experimented with heightmap-based gradients using modified Perlin noise and randomized color scales.
- A separate layered radial gradient technique used a tiny 85-byte image to power OpenAI's homepage gradient in 2019.
Source: justinjay.wang, 2026-09-03
Published there as: “Methods for Random Gradients”
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