Picture a listing page for a power bank that reads exactly like the listing page for a phone case, a fan, and a travel pillow. Same three words every time: “crafted for the modern traveler.” One seller running products into Thailand and Malaysia hit that wall so many times he finally snapped and changed his prompt.
🎯 Intro
This Redditor sells electronics across two markets where every listing used to sound like the same generic premium brand, whatever the product actually was. Power banks, phone stands, portable fans, it didn’t matter, the copy came out with the same three or four adjectives stapled to the front. So he added one weird step before the AI wrote a single word of copy: force it to roast the product first. I love this because it’s the opposite of how most people use AI for marketing, and it’s such a simple flip that it’s almost annoying nobody tried it sooner. Most sellers spend their time tweaking adjectives and swapping synonyms for “premium.” He went the other direction and asked the model to find what was wrong before it was allowed to say anything good.
💡 Why It Matters
AI writing tools default to flattering language because that’s what most marketing prompts ask for. Nobody tells the model to find the weak spots, so it never does, and every listing ends up sounding like a polished ad instead of an honest pitch from an actual shop owner. The seller noticed his buyers were asking vague questions like “is this good?” which is exactly what happens when copy gives them nothing concrete to react to. When every listing sounds identical, buyers have no real signal to make a decision on, so they default to the laziest possible question. Making the AI surface objections first flips that: the copy that comes out the other side answers questions buyers haven’t even asked yet, and it does it before they even reach the review section looking for reassurance.
🛠️ How-To Steps
Here’s the exact sequence the original poster landed on, in order.
- Ask the AI to attack the product before it writes anything. The first version of this instruction was blunt: list five reasons the product is not worth buying. The model refused to be harsh enough to be useful. It hedged, softened every point, and basically turned “reasons not to buy” into a backhanded compliment list.
- Soften the instruction until the AI actually complies. The working version was: “List what a skeptical buyer would notice.” This framing worked because it’s not asking the AI to be mean, it’s asking it to role-play a specific, realistic reader. That’s a small wording change with a big effect on how honest the output gets. Instead of judging the product, the model is just describing what a cautious shopper would clock in the first ten seconds of looking at photos and specs.
- Read the objections, even the uncomfortable ones. For this seller, that meant admitting the battery life was mediocre, the plastic case looked cheaper in person than in photos, and the “free gift” was really just old stock he was trying to clear out. None of these were things he wanted to hear about his own products, which is sort of the point. If it stings a little to read, that’s usually a sign the objection is real and worth addressing head-on instead of hoping nobody notices.
- Feed those objections back into the actual writing prompt. The final instruction was simple: “Write the listing knowing those objections exist.” That’s it, no elaborate rewrite process, just handing the model its own criticism and telling it to write with that knowledge already baked in.
- Let the copy change shape. The word “premium” disappeared. Some listings started mentioning the plastic case directly and explaining why it still holds up anyway, like noting it survived a drop test or held up fine after months of daily use. The tone shifted from marketing brochure to a shop owner being straight with a customer, the kind of copy that sounds like it was written by someone who actually owns the product rather than someone paid to describe it.
🔑 Tips & Tricks
- If the AI won’t give you real objections, ask for a persona instead of a demand. “What would a skeptical buyer notice” beats “tell me what’s wrong with this,” every time.
- Treat the objections step as a separate prompt, not a single mega-prompt. Two clean steps beat one messy one, and it keeps the model from watering down the criticism to soften the final draft.
- Watch your inbound questions after you switch styles. The seller’s buyers went from “is this good?” to “does the 10000mah version fit my setup,” which is someone who already decided to buy and just needs a detail confirmed.
- Don’t expect a clean conversion number here. The original poster is honest that he can’t measure the lift directly, but the shift in question quality was enough for him to keep the roast step in every prompt now.
- This works past product listings too. Try it on a cold email or a landing page headline before you publish it, or even on your own bio if you’re tired of sounding like everyone else’s LinkedIn.
🏴☠️ Ready to make your prompts a little meaner? Head over to the original Reddit thread in r/PromptEngineering and see how other sellers are reacting to this one.
Source: u/Inevitable-Good219 on r/PromptEngineering
i make my AI roast my products before it writes about them
by u/Inevitable-Good219 in PromptEngineering