{
“title”: “Two Steps to Better AI Writing”,
“Text1”: “
Long prompt lists are the default fix for bad AI writing. Most people try to cram tone, audience, structure, and format into a single giant instruction and hope the model gets it right on the first pass. A Redditor going by u/Illustrious_Mine8995 skips that grind entirely and gets cleaner drafts using two short moves instead, and after testing it out, it’s the simplest writing fix worth stealing this month.
Quick start: before you touch a rewrite, let the AI ask you questions first. Then, when you actually ask for the rewrite, tell it what reading level to hit. That’s the whole system.
The Old Way vs. The New Way
The old way treats the prompt like a spec sheet. You write three paragraphs covering audience, tone, purpose, and formatting, then cross your fingers. The problem: the model still doesn’t know what you know. Context that lives in your head never makes it onto the page, no matter how long the prompt gets.
The new way flips the order. Instead of trying to predict every question the model might have, the original poster just asks it to ask. Context gets pulled out through a short back and forth instead of guessed at up front. Then, once the draft exists, a second lever gets pulled: reading level. That’s the contrast. One approach front-loads guesswork. The other pulls out real information first, then tunes the output second.
Step 1: Let the Model Ask For Context 🙋
This author’s exact move is to hand over the draft and say: “Before rewriting this, ask me questions that would help you understand the context and what I’m trying to communicate.”
The model comes back with real questions: who’s the audience, what’s the goal, what does a specific term actually mean here. You answer those, then ask for the rewrite. The value is you’re not guessing what context matters. The model tells you what it’s missing, and you fill exactly that gap.
Picture a short internal update about a delayed feature. Hand that over with the prompt above, and the model might ask who’s reading it, whether the delay needs a reason attached, or if \”soon\” means a specific date. Answer those three things and the rewrite lands closer to what you actually meant on the first try. Compare that to writing a five-paragraph prompt trying to cover the same ground in advance and still missing the one detail that mattered.
Step 2: Control the Reading Level 📏
The second move comes from a completely different source: the book The Bezos Blueprint, which argues for an 8th-grade reading level when writing for a general audience. This contributor borrowed the idea and turned it into a direct instruction: \”Rewrite this at an 8th-grade reading level while keeping the meaning and key details.\”
Swap \”8th-grade\” for a specific target if you want more control, using the Flesch-Kincaid Grade Level as your benchmark. Ask for grade 6 on a landing page, grade 10 for a technical audience that still wants clarity. The result strips out the padding that makes AI writing sound like AI writing, without losing the details that actually matter.
The shift is subtle but it shows up fast. A paragraph full of \”leverage,\” \”utilize,\” and \”facilitate\” turns into \”use,\” \”show,\” and \”help\” once the reading level instruction is in place. Long compound sentences split into two shorter ones. Nothing about the meaning changes, but the friction to actually read it drops.
Putting It Together
Here’s the full sequence, step by step:
- Paste your draft and ask the model to question you before rewriting.
- Answer honestly, even the \”obvious\” stuff. It’s not obvious to the model.
- Ask for the rewrite once the context is on the table.
- Add the reading level instruction, either \”8th-grade\” or a specific Flesch-Kincaid score.
- Read it back out loud. If it still sounds stiff, ask what grade level would make it simpler.
One warning worth flagging: this works best on drafts that already have real content in them. If the draft itself is thin, no amount of context-gathering fixes that. Fix the thinking first, then let this process clean up the sentences.
What makes this approach worth stealing isn’t either trick alone. Plenty of people already know about reading-level prompts. It’s the order that matters: get context before you get output, and only tune style once the substance is right. Skip the marathon prompt. Ask two short questions instead, and let the model handle the rest.
The original discussion has more reactions worth reading, including people testing their own variations on both prompts. Worth a scroll if you want to see what else is working for people.
”
}
Two simple things I do to get better writing from LLMs
by u/Illustrious_Mine8995 in ChatGPTPromptGenius