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ComfyUI started as a learning project for me. I wanted to understand AI image workflows and things like LoRAs that I hadn't really got my head around.
It's easy to collect the vocabulary without understanding what the pieces do together. I wanted to work with the pieces.
ComfyUI lets you connect steps in a visual graph. A node does a particular job; a connection carries something into the next step. Settings feed generation, and the result can move through refinement or upscaling.
A LoRA is a smaller set of learned adjustments used with a compatible base model, rather than a whole replacement model. Learning where it fits in the workflow gives the term somewhere to live.
I could follow the connections, inspect the settings and see which stage I was changing. That gave me a more useful way to learn than collecting another list of AI terms.
Changing the image without rebuilding the setup
The local work grew to include reusable workflow builders. They assemble connected steps while letting selected controls vary.
That gives me a way to change inputs without rebuilding the whole graph. The surrounding generation and finishing stages can stay in place while I work on one part of the setup.
There's an engineering question hiding in that arrangement. If a script assembles the workflow, how do I know it connected the pieces correctly?
I added structural checks for things such as unique identifiers, valid connections and compatible types. They inspect whether the assembled graph is wired together as expected.
They can't tell me whether I like the resulting image.
A graph can pass those checks and still produce something unsuitable. Composition, usefulness and consistency need their own assessment. I haven't established that these workflows save time or produce more consistent results for a business.
Two questions to keep separate
Working with the graph helped me separate the setup from the result.
First, did I assemble the process I intended? Then, did that process produce an image that works for the task?
If I mix those questions together, a disappointing image tells me very little about what to change. A wiring check gives me one thing I can inspect separately, without pretending it settles the creative judgment.
There's also a useful question to ask before making the graph more elaborate: which inputs should be easy to change, and which parts should stay steady while I change them?
In this project, that means deciding where controls enter the graph and keeping generation distinct from refinement or upscaling. Those choices make the setup easier to inspect. They don't guarantee a good image.
If I take this further, I'd choose one image task and compare outputs while changing one selected input at a time. I'd record the setup changes alongside the images, so I could judge the result as well as the wiring.