Last week, I watched a friend spend four hours writing product descriptions for her new candle line. Four hours. For twelve candles. She was stuck in that loop where every description started sounding the same — "hand-poured," "artisan," "premium soy wax" — and by candle number seven, she'd run out of adjectives entirely. I've been there. Most people who write for a living have been there.
The thing about AI copywriting is that it's genuinely useful. But it's also genuinely easy to use badly. I've tested enough AI-generated copy across enough platforms to know that the difference between "this reads like a robot" and "this actually converts" comes down to a handful of specific techniques. Not prompts. Techniques.
Let me walk through what I've learned.
The "Garbage In, Garbage Out" Rule Still Applies — But Not How You Think
Everyone talks about prompt quality. Fair enough. If you feed an AI tool vague instructions, you'll get vague copy. But here's what's less discussed: the problem isn't usually the prompt. It's the context.
Most people write prompts like this: "Write a product description for a soy candle." That's it. No target audience. No differentiator. No brand voice. The AI has to guess — and it guesses generic. Copywriting research consistently shows that AI-generated copy performs dramatically better when it includes specific product details, clear audience context, and a concrete call to action. Without those elements, even well-written copy falls flat.
I've found that the single highest-impact change you can make is feeding the AI three things before you ask for anything:
- Who this is for. Not "women 25-45." That's demographic nonsense. I mean: "Someone who just moved into their first apartment and wants it to smell like a home, not a rental."
- What makes this different. Not "high-quality." Something real. "We use coconut wax because soy wax gave inconsistent hot throws in testing."
- What you want them to do. "Buy this candle" isn't a CTA. "Try the sample size before committing to the full jar" — that's a CTA with psychology behind it.
When I skip any of these three, the output quality drops noticeably. Every time.
AI Is Terrible at Being Interesting (Unless You Force It)
Here's a sentence AI tools love to write: "Our candles are crafted with care using premium ingredients to create a warm, inviting atmosphere."
Nobody has ever been persuaded by that sentence. Nobody has ever read that sentence and thought "yes, this is the candle for me." It's filler. It's what AI produces when it doesn't have enough to work with.
The fix is counterintuitive: you need to give the AI permission to be specific, even weird. I'll sometimes include a note like "use sensory details — mention how the wick sounds when it first catches, or how the wax pools unevenly on the first burn." That kind of detail forces the AI out of generic mode. It won't always nail it, but it'll get closer than "premium ingredients."
One trick I use regularly: ask the AI to write three versions — one straightforward, one humorous, one emotional. Even if I don't use any of them directly, seeing the range helps me identify what tone actually fits the product. Sometimes the humorous version is terrible but contains one line that's genuinely good. I'll steal that line and rebuild around it.
Product Descriptions at Scale: The Etsy Seller's Nightmare
Let me paint a real scenario. You're selling handmade ceramic mugs on Etsy. You've got 50 SKUs. Each one needs a title, a description, five bullet points, and 13 tags. If you're fast, each listing takes 20 minutes. That's nearly 17 hours of writing. And you're not a copywriter — you're a potter.
The traditional approach is brutal. You sit down with coffee, open your spreadsheet, and by mug #12 you're writing things like "beautiful ceramic mug, great for coffee" because your brain has turned off. The descriptions get shorter. The bullet points get repetitive. Your conversion rate suffers and you don't know why.
AI tools change this math. With a tool like Jasper or Copy.ai, you can feed in your product specs and get a decent first draft in seconds. But here's the catch: you still need to write a decent prompt for each one. For 50 mugs that differ only in glaze color and handle shape, that's still tedious. You're trading one kind of writing for another.
This is where I've seen zero-prompt tools actually earn their keep. AI-Mind, for example, doesn't ask you to engineer prompts. You select "product description" as the content type, drop in your mug details — dimensions, glaze type, what makes this one different from the other 49 — and it generates the copy. The first 30 generations are free, which is enough to test whether the output matches your shop's voice. For someone managing dozens or hundreds of listings, that approach saves the prompt-writing step entirely.
Is the output perfect? No. You'll still edit. But editing a decent draft is faster than writing from scratch or wrestling with prompt syntax. I've timed it. For a 50-SKU shop, the difference between prompt-based tools and zero-prompt tools can be several hours of work.
When AI Copy Fails (And How to Catch It Before Publishing)
AI-generated copy has a few failure modes that show up consistently. Once you know what to look for, they're easy to spot:
- The adjective pileup. Three adjectives before every noun. "Luxurious, handcrafted, artisanal soy candle." One adjective, maybe two. Three is a cry for help.
- The enthusiasm problem. AI loves exclamation points and words like "amazing," "incredible," and "perfect." Real brand voices are usually more restrained. Strip these out aggressively.
- The missing "why." AI will tell you a product is "designed for comfort" but won't explain what makes it comfortable. Always ask: does this sentence contain a reason, or just a claim?
- The generic CTA. "Shop now" and "Learn more" are placeholders. Replace them with something that actually relates to the product. "See which size fits your space" beats "Shop now" every time.
I keep a mental checklist for this. Before anything goes live, I scan for adjective pileups and generic CTAs specifically. Those two issues account for maybe 70% of the AI copy I reject.
Editing AI Copy Is a Different Skill Than Writing From Scratch
This took me a while to learn. When you edit AI-generated copy, you're not line-editing — you're doing something closer to art direction. You're looking at the overall shape, the emotional arc, whether the right details are in the right places. The actual sentence-level fixes are secondary.
My workflow usually looks like this: generate the draft, then read it once without touching anything. Mark the spots where my attention drifts. Those are the sections that need restructuring or cutting. Only then do I go back and fix individual sentences.
I also have a rule: if I can't improve a sentence in under 30 seconds, I delete it and write a new one from scratch. Spending two minutes polishing an AI sentence that's fundamentally hollow is a waste of time. Sometimes the best edit is a delete key.
The tools that work best for this are the ones that get out of your way. ChatGPT is great if you know how to prompt it precisely. Claude handles longer-form content well. And for people who don't want to learn prompting at all, AI-Mind's approach — pick a content type, add your details, get a draft — removes the friction of figuring out what to ask for. Different tools for different tolerances of complexity.
The common thread across all of them: the human editing step is non-negotiable. AI gives you clay. You still have to shape it.
What Actually Matters for Conversion
I've seen beautifully written AI copy that didn't convert, and clunky human-written copy that sold like crazy. The difference usually isn't writing quality. It's whether the copy answers the questions a buyer actually has at that moment.
For product pages, those questions are predictable: What is this? Why should I care? What makes it different from the alternatives? What happens if I don't like it? AI can answer all of these — but only if you tell it to. The default output often skips the "what makes it different" part because the AI doesn't know your competitive landscape.
You have to supply that. Every time. No tool will do it for you.
One practice I've adopted: before generating any copy, I write down three objections a buyer might have. Then I make sure the AI addresses at least two of them in the output. If it doesn't, I add them manually. This alone has improved conversion rates on the pages I've worked on more than any prompt tweak ever did.
AI copywriting isn't magic. It's a time-saving tool that works best when you know exactly what you want to say but don't want to stare at a blank page figuring out how to say it. The tips that matter aren't about prompts or tools — they're about clarity, specificity, and editing discipline. Everything else is just typing.
Sources: Copywriting and conversion rate optimization research on AI-generated content performance, 2025; HubSpot State of Marketing Report on AI tool adoption among marketers, 2025.