We Want No Plates:

Confounding Food Placement with Local AI

Dog Days of DevOps 2026

Slides at ian.im/dd26

Ian Littman / @ian@phpc.social / @ian.im / @iansltx

The idea (August 7)

> ......i found a use for AI i want to investigate but i'm too lazy to do it
> train image gen model on r/WeWantPlates
> i want it to go the other way
> here is a normal food, present it in a ridiculous way

let's reticulate the splines

The Components

1. LLM with vision input
   1. Image prompt: Original food pic
   2. Text prompt: "Give me a prompt for putting this in a different env"
   3. Output: prompt
2. Diffusion image-to-image model
   1. Image prompt: Original food pic
   2. Text prompt: Output from step 1
   3. Output: cursed image
3. LLM with vision input: verify that the output from step 2
4. Python (because LLM codegen) to wire this together (incl. retries)

Runtime

• Gemma3 12B (steps 1 and 3) via ollama
• black-forest-labs/FLUX.1-schnell (step 2)
• Gemma4 ollama MLX doesn't have vision?!?

Codegen

• DeepSeek V4 Flash 0731
• A little bit of GLM 5.2
• Initial vision testing with MiniMax M3
• Zed built-in harness

the models

• M1 Max MacBook Pro (64GB)
• Whatever Ollama Cloud runs on

the hardware

the Repo

🔥/iansltx/wewantnoplates

Let's see what we've got

Thanks!

Slides at ian.im/dd26

Questions? Find me here / @ian@phpc.social / @ian.im / @iansltx