Plain colored shapes in prompts shift AI models' coding choices, DeepMind and Stanford find
Overview
A Google DeepMind and Stanford paper reports that adding a plain colored shape to a coding prompt changed how three models solved a problem.
Across 288 shapes, the study tracked how often Claude Opus 4.7, Gemini 3.1 Pro and GPT-5.4 chose recursion. Per Rohan Paul's account of the paper, a red heart moved Claude Opus 4.7 and GPT-5.4 from 0% to 100% recursive solutions on a binary tree problem.
The paper also reports that 71.5% of Gemini 3.1 Pro's steered thinking traces called the image irrelevant.
Written by AI from the articles below · updated Nov 3, 11:27 AM ET
Check the sources:
Article timeline
The articles in this story. Times are ET.
Rohan Paul@rohanpaul_aiXGoogle DeepMind and Stanford find simple shapes in prompts steer AI coding choicesAIA Google DeepMind and Stanford paper reports that adding a plain colored shape, such as a red heart, to a coding prompt changed how models solved a problem. Across 288 shapes, the study tracked how often Claude Opus 4.7, Gemini 3.1 Pro, and GPT-5.4 chose recursion. A red heart moved Claude Opus 4.7 and GPT-5.4 from 0% to 100% recursive solutions on a binary tree problem, and 71.5% of Gemini 3.1 Pro's thinking traces that were steered called the image irrelevant.

Heat Trend
- Current comparable heat
- 9
- Peak comparable heat
- 10Nov 3, 12:00 PM ET
- Change in past 24 hours
- –
The trend compares only continuously observed participants, so its scope may be smaller than the current heat total. Hover or tap for hourly heat; use arrow keys with a keyboard.