Course → Module 1: What Makes Slop, Slop
Session 9 of 10

The most common advice for improving AI content is "use AI for the first draft, then edit." This sounds reasonable. It is the approach that most people default to. It does not work, and understanding why it does not work is essential before you can build a process that does.

The Editing Illusion

When you edit a document, you work within the document's existing structure. You fix sentences. You cut paragraphs. You improve word choices. What you do not do, almost ever, is change the fundamental architecture of the piece: what topics are covered, in what order, with what emphasis, from what angle.

When AI generates a first draft, it makes all of those architectural decisions for you. It chooses what to include and what to exclude. It decides the order of ideas. It picks the framing, the angle, the emphasis. It determines which points get one sentence and which get three paragraphs. By the time you start editing, the architecture is set.

Editing AI output means renovating a building with a bad foundation. You can repaint the walls, but the rooms are in the wrong places.

What AI Decides Before You Start Editing

The table below lists the decisions an AI makes when generating a first draft. These are the decisions you inherit when you choose to edit rather than rewrite.

Decision What AI Chooses What You Would Choose (If Writing From Scratch)
Topic coverage Covers the obvious subtopics based on training data Covers what your specific audience needs to know
Order of ideas Most common sequence from training data Sequence that builds your specific argument
Angle/framing Neutral, balanced, addresses "both sides" Your perspective, your experience, your conclusion
Depth per section Even distribution, each subtopic gets similar space More depth on what matters, less on what does not
Examples Generic, hypothetical, or common knowledge Specific cases from your experience
What to exclude Anything outside the statistical norm for the topic Deliberate exclusions based on audience and purpose

The Anchoring Effect

Behavioral economics describes an anchoring effect: once you see a number or a reference point, your subsequent judgments are pulled toward it. The same effect operates when editing AI output. Once you read the AI's framing, your thinking is anchored to that framing. It becomes harder to conceive of a fundamentally different structure, even if a different structure would be better.

graph TD A["AI generates draft"] --> B["You read the draft"] B --> C["Your mental model
anchors to AI's structure"] C --> D["Editing happens within
AI's framework"] D --> E["Surface improvements
Structural limitations remain"] F["You outline from scratch"] --> G["Structure reflects
your expertise"] G --> H["AI generates text
within YOUR structure"] H --> I["Editing improves
already-correct architecture"]

This is why "write from scratch, then use AI" produces better results than "let AI write, then edit." When you start with your own outline, your own structure, your own decisions about what to include, the AI fills in text within a framework you control. When AI starts, you are editing within a framework it controls.

The Experiment

Here is a test you can run yourself in thirty minutes. Pick a topic you know well. Something you have professional experience with.

Path A: Prompt AI to write a 500-word article on the topic. Spend 15 minutes editing it to your standards. Note the time and effort.

Path B: Write a 5-point outline of what you would cover, in what order, with what emphasis. Then write 500 words yourself, or use AI to generate text for each section of your outline separately. Note the time and effort.

Compare the outputs. Path A will be smoother in some ways, because AI generates fluent prose. But Path B will contain information, perspectives, and structural choices that Path A does not. Path B will sound like you. Path A will sound like a more polished version of generic.

What Editing Can Fix

Editing is not useless. It has a proper role in the production pipeline. But that role is narrower than most people assume.

Editing Can Fix Editing Cannot Fix
Word choice and phrasing Fundamental structure and argument
Removing hedges and filler Adding experience and specificity that was never there
Fixing factual errors (if you catch them) Replacing the AI's framing with yours
Adjusting tone Establishing voice
Tightening prose Changing what the article is fundamentally about

Editing belongs at the end of the pipeline, after the human decisions (structure, angle, evidence, emphasis) have already been made. It is a polishing step, not a rescue operation. Using editing as the primary quality control on AI output means you are polishing a piece whose fundamental architecture was determined by a machine that has no expertise, no experience, and no stake in the outcome.

The Alternative

The alternative to "AI writes, I edit" is "I decide, AI executes." You make the architectural decisions: what to cover, in what order, from what angle, with what evidence. AI generates text within those constraints. You edit the text, not the structure. This approach is covered in detail in Module 2. The takeaway for now: the first draft is where the important decisions happen. Do not outsource those decisions to a machine.

Further Reading

Assignment

  1. Pick a topic you know well. Generate a 500-word AI article on that topic with no structural guidance.
  2. Spend exactly 15 minutes editing it to your standards. Save the result as Version A.
  3. Now write 500 words on the same topic from scratch, using your own structure and framing. You may use AI to help with individual sentences, but the outline and structure must be yours. Save the result as Version B.
  4. Compare the two versions. Which one sounds like you? Which contains information only you would think to include? Which would you publish under your name?