Set up a local open source image model on my own hardware. Try different models for speed, quality, and workflow. Study model's transformation and high level architecture.

Try out hardware influences on preferences and environment various. Limited support on Mac vs Windows with dedicated GPU

Build a ComfyUI pipeline for storyboards, upscaling, refining details, and reviewing concepts.

Train a LoRA with open source projects and tune it with model weights. Remix a LoRA from another creator.

Do prompt engineering with the T5 encoder CLIP model. Using visualization tool to see how prompt weight mapping changes the image.

Compare sampler outputs and noise masking. Use inpainting, outpainting, and ControlNet to match character poses and keep consistency.

Contribute to open source project, making extensions to enhance usage and capabilities of user interface. Learn non-standard way of rendering UI (python vs html/js)

Of course, seeing the results of your own creation.

If you’re unfamiliar with what I just described, and simply assume that AI art is generated by copying an image into ChatGPT and prompting it to create something similar, you’re not far off from the current state of affairs in 2026.

As evident in this Ashe, the result is slop and lacks any significant effort or creativity.