Chatscape

Are you drafting or iterating? Some thoughts on writing with AI

I use AI in my day-to-day at work — yes, sometimes, even to write!

Despite the hype about "removing critical thinking," somehow it hasn't taken away any of the mechanics, structure, or thought processes behind writing. Although I compose these blog posts from my brain (plus other people's research/brains), the very act of putting words into a blank digital page hasn't changed at all with AI. At least not for me.

I read a lot about how non-developers are using AI and what keeps coming up in these discussions is the idea that AI removes the fear behind the "blank page." People keep saying that because AI can put together a "pretty ok" first draft, they're able to jump in to edit and rewrite, rather than staring at the blinking cursor in front of them, wondering what to say. I don't have blank page syndrome. I have no problem filling the pages with messy thoughts and then iterating my draft from there, but my experience seems to be somewhat uncommon.

So today I'm thinking about the idea of the "draft" and where it might go with AI.

Death of the Rough Draft?

For many everyday AI users, the traditional "rough draft" has vanished. AI is turning writing into a vending machine experience: You put in a prompt, throw your messy ideas at it, and out comes a finished product. It's wrapped up nicely though you don't know if it's whole or broken into pieces until you tear into it.

I'll divide this into two perspectives to add nuance: that of a "non-writer," who is someone who maybe has to write for work or school but doesn't want to, and that of a "writer," someone who self-identifies as a writer and takes pride in it (professionally or not).

If you're writing with generative AI, the concept of the "draft" has changed from a human-originated, static text, to a dynamic, collaborative artifact. The journey of a draft varies based on the writer's intrinsic motivation and professional background.

AI Journeys (Some Examples)

If you view writing as a functional chore (rather than a necessity or creative outlet), AI serves as a cognitive scaffold and anxiety reducer. It reduces the barrier to entry (instead of a blank page, they start with a generated draft). They only need the sketches of an idea to use AI to generate the initial chunk of text, then lightly edit it. Instead of engaging in the full writing process, they fix grammatical errors and try to "humanize" the language.

Those sound like negatives, especially when in conversation with folks who fear what too much AI usage does to critical thinking. On the flip side, they might have more motivation to do it than they used to. Writing with AI is less of a chore; the quality of the draft is higher (through little effort of their own) and they can deliver faster, which is likely going to become an expectation if your job has AI tools available. Suddenly those writing tasks at work are more bearable and easier to check off so you can focus on the stuff you like about your work.

Writing Drafts Before vs After Generative AI.

Element Before GenAI With GenAI
Origin of Draft Human-led internal thought or research/notes. Often a prompt: AI-scaffolded or co-created.
Human Effort All generation. Curation, verification, editing.
Process/Structure Linear (outline, draft, revise). Iterative (prompt, verify, edit, feedback, re-prompt).
Error Rate Stylistic or grammatical, usually. Fact-checking often happens during the drafting phase. High risk of factual hallucinations (~26-36% in some studies).

If you love writing and don't hate AI, you're likely viewing AI as less of a ghostwriter and more like a sparring partner. Instead of prompting AI to write your draft for you, you might be going for help exploring specific aspects of your ideas. Professional writers are using AI for higher-level structural tasks, rather than generating sentences. The AI helps them frame thoughts, find alternative ways to phrase things, and pressure-test arguments.

Every other article you read on the topic stakes claim to the idea that writers will evolve into "editors or supervisors" reviewing AI-generated content. While a non-writer might go to AI to help get something done faster, a writer is likely employing metacognitive strategies to increase creativity. They're not just producing an artifact, they're attacking it from multiple angles to understand the best way to output. It's likely only a handful of writers are taking the first output as a "good enough" draft. Most of them know they could have written it better, so instead they ask: what else can AI do to help them achieve their goals?

A Personal Example

When AI was first introduced at my institution, I felt threatened because everyone kept saying we "finally have something to write for us." But you had me to write for you this whole time??

It wasn't until multiple AI options were released that I realized AI usage in workflows is entirely personal and that as the sole doc person in my department and operational workflows, no one else was going to be able to dictate how I used it. Non-writers probably use AI to write things, but at work, I'm using AI to organize knowledge effectively. In weeks/months I'm learning how to serve my colleagues better in my job; without AI, it would have taken years to gain intermediate understanding of the foundational concepts of using our technology stack as a knowledge repository.

I have a personal agent at work that helps me write release notes, not because I can't do it by myself, but because it's an incredibly time-consuming process and the results must speak to multiple non-technical roles about very technical updates. Previously, it took 2 weeks to go through the writing process (play/understand, draft, refine, SME review, finalize); now it takes 3 days. (SME = Subject Matter Expert.) I can do this because I've done it before. I knew which instructions to give the agent, I know what to put in my prompt for a good result, and I know how to review/refine the results for what's required. Rarely does AI output something I can use as-is, but it helps me through the hurdles of understanding the release item (shaving off some play time) and how it impacts the people who use the technologies, each group with its own goal.

Get Used to the Word "Iterative"

We previously used this word only in the context of agile methodologies and the iterative work involved in scrum frameworks. Some people see this word and think that it's "too technical." Pretty soon, the word "draft" may never be used without a heavy emphasis on an iterative process.

There are strengths in collaborating with AI while writing, but only if you embrace the iterative process. Instructions are important and good prompting is vital, but to produce a good piece of writing with AI, you need to take it iteratively. The first AI draft, though perhaps better than what a non-writer would have done alone, should never be seen as a final.

Wide usage of any technology (especially disruptive) comes with a whole new set of words to know and love. Another one you'll see a lot is the idea of the "human in the loop (HITL)." That's you reviewing the output. And if you're doing a "single pass" and correcting only a few words and punctuation, you're dismissing the value that your knowledge provides.

Division of Strengths When Writing Drafts with Generative AI.

Element Human Strength LLM Strength
Structure Ensuring the narrative arc or outline feels authentic and makes sense. Rapidly generating outlines and logical flows.
Tone Reviewing for nuance, irony, and empathy. Filling in blanks where assumptions may live. Mimicking styles (professional, clear, succinct, etc.).
Volume Cutting out the fluff to focus on something people can actually comprehend. Expanding a 50-word thought into 500 words, or as directed.
Accuracy Identifying logical fallacies and hallucinations. Organizing existing data points into 'best guess' connections.

All of the old tips & tricks still apply:

AI doesn't know how to do any of that; although you could ask it to read aloud for you, you'd still have to identify where to update it. You can ask it to verify results or argue against your ideas, but we all know that AI sometimes makes up shit to serve its prompter. By itself, AI is unable to determine how to write best for YOUR audience. By itself, AI cannot replace a human writer.

Now in addition to the usual tips, there are new ones. You must learn how to fact-check the unknown. At work I mostly use AI to help with things I already know, but how do you check a draft if you aren't an expert? I've developed some tactics to share, but I'm sure I'll bring more onto this blog as I learn more.

Reverse the Flow

In my reading and predictions, the traditional binary of "human-written" vs "plagiarized" will be replaced with a multidimensional framework that evaluates a draft in multiple ways: content generation, structural assistance, creative input, and analytical contribution. A framework like this allows AI collaboration on a rubric, rather than defining it in the constraints of the current (pre-AI) binary views of what constitutes "human-written."

Maybe a human had the idea, structured the outline, but used AI to assist in writing the words. Perhaps AI helped with outlining, but the human wrote all the words. Where you draw the line may be individual, but standards will (and must) be defined in academic contexts to ensure learning and comprehension takes place.

Most advice tells you to let AI draft, then you refine. For students and professionals who want to keep their "intellectual muscles" in tact, try reversing the flow.

  1. Brain dump: Write a messy blurb or bullet list of your thoughts, observations, and takes on a topic. Drop notes from your research (cited properly) that you think support your claims and which you'd like to include in your final result.
  2. Prompt for structure: Feed the mess into the AI with a prompt suitable to your assignment. For example:
    • Here are my raw thoughts. Do not add new information, but organize these into a logical structure and identify any gaps in my logic.
  3. HITL review: Review the output and refine, edit, or restructure into what you'd like to produce. Fill in gaps that you identify. Expand your thoughts on gaps the AI identified.
  4. Prompt for connections: Use the AI to help bridge missing details or add structure to anything new that was added in the previous step.
  5. HITL finalization: Take some time away, then return to your most recent draft. Does it make sense? Does everything flow well? Are your sources cited properly? Is your paper formatted to the specifications of your degree? (Many institutions rank proper citation and paper format highly.) And perhaps most importantly: If your instructor asked you to summarize this paper and what you learned about the topic, could you?

Note: Use steps like this outlined on people's blogs as a starting point, not a rule. How you write and your development process is very individual.

Instead of using AI to dictate the direction your writing goes, use it to assist with the direction you want to go. If you let the AI draft first, you're essentially giving it your ideas to compile into a meaningful thought, then editing it. If you draft first and use AI to organize, you are using it to amplify your own intellect.

If you're a student who seeks to use AI effectively, find ways to ensure the "intellectual property" of the output (the actual ideas) starts in your own head. The AI is your documentation specialist, here to help translate and organize your ideas; you are the subject matter expert.

Further Reading

#prompting #working-with-AI