Why I stopped model-hopping and built a predictable image pipeline

## A small confession: the project that broke my assumptions Two months into a side project I was building for a design studio (March 12, 2025 - prototype branch, GPU: RTX 4090, Python 3.10), I hit the kind of mess that makes you swear off "the best model for the job." I had a tight deadline to produce a set of marketing hero images that matched client copy and typography; I tried stitching together three different public checkpoints and the outputs clashed so badly that the art director refused to approve anything. That moment forced a change: stop chasing every shiny model and build a reproducible pipeline that any teammate could run tomorrow. The rest of this post is what I learned rebuilding that pipeline: the mistakes, the quick experiments that worked, and the tools and trade-offs that made the work predictable for both engineers and designers. Read on if you've ever been burned by inconsistent styling, unstable sampling, or "it looked great on my laptop" syndrome - and if you wa