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A deliberate path from zero to making your first images. Roughly 60 minutes total. Free.
Stable Diffusion in the Cloud: No GPU Required
Don't have a powerful GPU? Here's how to run Stable Diffusion using free and paid cloud services — generate…
Seeds, Samplers, and CFG: The Settings That Actually Matter
What the generation settings in Stable Diffusion actually do — explained with no jargon so you can stop…
Checkpoints vs LoRAs vs Embeddings: What They Are and When to Use Each
The three types of models you'll use in Stable Diffusion — what they do, how they're different, and when to…
The Secret: I Don't Start With a Prompt
Everyone asks why they can't get the same results with my prompts. The answer: the prompt you see is the last…
The Three Starting Points: How I Decide Where to Begin
Every image starts somewhere different. A reference, extracted tags, or someone else's prompt. Here's how I…
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Two Hard Rules For Blind Evals: 5-Prompt Floor And Always-Control
You ran a blind eval, picked a winner, almost shipped it — then a verification round flipped the result entirely. The candidate that won two of three prompts placed fourth across five. Three prompts felt like enough data; it was actually noise dressed up as signal. There are two specific design rules that prevent this failure: a hard floor on prompt count, and always including the previous version as a control. Cheap to apply, painful to ignore. Here's what each one buys you and the exact thresholds I use now.
Weighted Scoring — When Your 3/2/1 Tournament Hides The Real Winner
Your blind eval came back with two models tied at the top. 21 points each across 10 prompts under standard 3 / 2 / 1 top-3 ranking. Looks like a coin flip. It probably isn't. The standard scoring scheme treats 'never bombs' and 'wins more often' as equivalent — but for production model selection, those are very different qualities. Here's how to re-score the same data under different weighting schemes to surface the real preference, why ties under standard scoring often resolve cleanly when you reweight, and how to pick a scoring scheme that matches what you'll actually do with the result.
Multi-Round Merge Tournaments: Wide → Narrow → Dial-In
You ran a tournament with five candidate merges. Picked a winner. Shipped it. Two months later you wonder if the loser at slot 3 might have actually been better with slightly different weights — and you have no way to know without redoing everything. The fix is a multi-round tournament structure: wide net first, narrow on the winner's neighborhood, dial in along a single axis. Three rounds, ten or so total candidates, an answer you can defend. Here's how to design each round so the result is interpretable, not just a winner.
V2 Or A New Model? How To Decide When To Add A Version On Civitai
You've got an updated checkpoint or LoRA ready to ship. Same family as something you've already published — but it's a meaningfully different output. Do you click "Add Version" on the existing model page, or post it as a new model? It sounds like a small decision but it's actually a strategic one. Here's the rule I use, when I break it, and what each path actually costs.
My Complete Daily Workflow: Idea to Upload, Start to Finish
The capstone — every tool, every script, every decision point connected into a single walkthrough of how I produce 100-500 images a day from start to upload.
Building a Prompt Library: Save Everything, Reuse Forever
How I built a reusable library of image prompts and enhancement prompts over years of testing — and how having that library makes every new idea faster to execute.
How I Use the Prompt Toolkit to Upgrade Any Prompt
The enhancement meta-prompts I run on every image prompt before it touches the splitter — what each one does, when to use it, and the exact order that works.
How I Remix Any Prompt Into Something New
You find a prompt on Civitai that catches your eye. Instead of copying it and hitting generate, here's how I break it apart, add hundreds of variations, and turn one prompt into something completely new.
My Complete Workflow: A Full Day of Image Generation
What a real day of generating 100-500 images actually looks like. The morning review, the setup, the generation, the selection, and the upload. Every step, in order.
50,000 Variations From One Prompt
One prompt. One recipe. 50,000 possible combinations. Here's how I generate hundreds of unique images from a single concept without writing a single prompt by hand.
The Three Starting Points: How I Decide Where to Begin
Every image starts somewhere different. A reference, extracted tags, or someone else's prompt. Here's how I decide which door to walk through — and what happens after I do.