Module 3 · Files, tools and your own data Lesson 10 of 15
Automation and the imagery pipeline and your first script
Midjourney generation runs through its own app rather than a general API, so the automation to learn here is the pipeline around it: batch prompts, a naming convention, and an edit pass. You do not need this to finish the course, and you do not need it for a fresher job either — but an afternoon here is what turns "I have used Midjourney" into "I have built with it", which is a different sentence in an interview.
The concept
Midjourney generation runs through its own app rather than a general API, so the automation to learn here is the pipeline around it: batch prompts, a naming convention, and an edit pass. The idea is simple: the same model you have been chatting with also answers a web request, so you can put it inside a script, a spreadsheet or a page. A key identifies you; a request sends the text; a response comes back as data.
The reason to try it once, even if you never build anything: it makes the chat version less mysterious. You see that the whole conversation is text in and text out, that your instructions are literally lines of a request, and that "the model" is one parameter among several.
A first call looks like this:
# The pipeline, in plain steps:
#
# 1. Write the prompt skeleton once (subject / medium / light / comp / ratio).
# 2. List the 20 subjects you need in a spreadsheet, one per row.
# 3. Generate in batches, and rename each result as you accept it:
# projectname-01-cover.png
# projectname-02-inset.png
# 4. Keep only the accepted ones, and keep the prompt for each in the sheet.
# 5. Edit outside the tool for anything that must be exact: text, numbers,
# a logo, a specific person's face.
#
# Step 5 is the one people skip. The generator makes images, not layout,
# and every headline belongs in your editor, not in the prompt.Common mistakes
The mistake is asking the image model for accurate text. Any lettering it produces will be wrong or slightly wrong, and on a poster a slightly wrong word is worse than none.
Worked example
A spreadsheet of twenty prompts run in one sitting, with a fixed naming convention for the outputs, is a realistic way to make a set of course thumbnails in an afternoon.
Your practice task
Get a key, run one request that works, and change one word in it to see the answer change. That is the whole of the first afternoon.
Do this before moving on. Reading a solution teaches the shape of it; typing it teaches you.
Key takeaway
Midjourney generation runs through its own app rather than a general API, so the automation to learn here is the pipeline around it: batch prompts, a naming convention, and an edit pass.
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