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An AI draft can sound ready before it’s actually useful. The sentences flow, the advice seems reasonable, and the call to action lands in the right place. That polish makes it tempting to treat the draft as the finished product.
But a reader isn’t only receiving words. They’re receiving advice, assumptions, and an invitation to trust the business behind them. Those parts need more than fluent writing.
A useful way to review any AI draft is to separate its language from its authority. AI can help arrange language. You’re responsible for the authority behind it: what you’ve actually seen, what you can verify, and what you’re willing to tell a customer.
That distinction changes the editing question. Instead of asking, “Does this sound good?” ask, “What would have to be true for me to stand behind it?”
Follow the authority behind each sentence
Consider a gardening service preparing a spring post. The owner asks AI for a short Facebook update about getting a garden ready for the season. The tool returns:
Spring is here! Give your garden a fresh start by clearing away winter debris, pruning your plants, and adding fertilizer. A little care now will help your garden thrive all season. Contact us today to schedule your spring cleanup!
The draft has a recognizable structure. It opens with the season, suggests actions, and ends with an invitation. As a starting point, that saves the owner from facing a blank page.
The problem is that the post presents several decisions as though they apply to every garden. Which plants should be pruned? Does the reader’s garden need fertilizer? What does “thrive all season” promise that the business can actually support?
The owner doesn’t need to reject every sentence. They need to identify where the draft has quietly made decisions on their behalf.
For example, “Contact us today” is primarily a wording choice. The owner can adjust it to match how customers usually get in touch. “Adding fertilizer” is different. It’s a recommendation, and the business needs a reason to give it before publishing it as general advice.
The owner might decide to remove that recommendation altogether. Or, if they have reliable information relevant to the audience, they might explain the conditions under which it makes sense. The point isn’t that AI must never mention fertilizer. It’s that a smooth sentence doesn’t establish whether the recommendation belongs there.
Now suppose this particular owner has noticed something during spring visits: some customers have already filled bags with last year’s plant material before asking what should stay and what should go. The owner knows those customers often feel uncertain about where to start.
That observation gives the post a more useful direction. Instead of offering a broad list of chores, the owner can address a decision customers actually face: pause before clearing everything and identify what needs attention first.
For this example, the owner also checks the business’s current service information and confirms that spring cleanup appointments can be requested through its contact form. That’s a modest claim, but it matters. A call to action is only helpful if it reflects how the business actually operates.
After adding those details and choosing language that sounds like something the owner would say, the revised post might read:
Before you fill those spring cleanup bags, take a minute to look at what you’re removing. We often meet customers who aren’t sure what to clear and what to leave alone, and it’s easier to make that call before everything is in a pile.
Walk through the garden first and note the areas you’re unsure about. If you’d like a hand planning your cleanup, you can request an appointment through our contact form.
The second post isn’t stronger because it contains more personality words. It’s stronger because the owner contributed a specific observation, removed advice they weren’t ready to stand behind, and checked the next step. The writing now helps a particular reader make a particular decision.
The example is illustrative. A real gardening service should use an observation it has actually made and check the details of its own offer. If the owner hasn’t seen customers make that mistake, the answer isn’t to borrow the story. It’s to find a different observation that’s true.
Three questions for a draft you can stand behind
You can use the same review on a social post, email, article, or product recommendation. Read the draft sentence by sentence and ask three questions.
What is this sentence doing?
Some sentences simply organize ideas or make a passage easier to read. Others make a claim, give advice, describe your business, imply a result, or ask the reader to act. One sentence can do more than one of these things.
That first pass helps you spend your attention where it matters. You can revise an awkward opening based on taste. A sentence that tells someone what to do with their garden requires a different kind of review.
Watch for small words that hide large assumptions. “Always,” “best,” and “guaranteed” are obvious signals, but a casual instruction can be just as consequential. “Add fertilizer” sounds simple because it skips the question of whether that action fits the reader’s situation.
What gives this sentence authority?
A claim might be supported by something you can check, such as your current pricing or the features of a product you recommend. An observation might come from work you’ve actually done or questions customers have genuinely asked. A recommendation might depend on the reader’s circumstances and need a condition attached.
If you can’t identify the basis for a claim, don’t treat the AI’s confidence as evidence. Check it, qualify it if the support justifies a narrower statement, or leave it out.
This applies to your own business details too. A draft may confidently name a service area, describe an offer, or promise a response time. Even if those details sound plausible, they need to match what you currently provide. You don’t need an elaborate research project to verify your contact form works, but you do need to make the check.
What can I add that the draft can’t know on its own?
Look for a real question customers ask, a decision they get stuck on, a misconception you’ve encountered, or a detail from your work that changes how the advice should be understood. These contributions don’t need to be dramatic. They need to be relevant and accurate.
A gardening owner might know that customers often ask whether to clean up everything at once. An affiliate marketer might know that readers regularly confuse two features when comparing tools. A consultant might notice that prospects ask for a solution before defining the problem.
In each case, the useful contribution isn’t a claim that the business owner knows everything. It’s a closer view of where a specific audience needs help. That view gives the draft a reason to exist beyond filling a space on the calendar.
There’s a difference between making content personal and making it personal-sounding. Asking AI to “make this more authentic” may change the tone, but it won’t establish which experiences are yours. Give it a real detail you’re comfortable sharing, then decide whether its version represents that detail accurately.
The same applies to a natural turn of phrase. You don’t have to force slang into a post or reproduce every habit of speech. Read the draft aloud and notice where you’d hesitate to say something to a customer. Replace those phrases with clear language you’d actually use, without changing what the evidence supports.
Your voice can make a claim sound like you. It can’t make the claim true.
That’s why checking comes before polishing. If the gardening owner first asks AI to make the original post warmer and punchier, the tool might produce a more appealing version of the same overbroad advice. The weak recommendation becomes easier to overlook, not more reliable.
There’s also a limit to experience. Seeing a few customers make the same mistake doesn’t automatically prove that most customers do it. A useful observation can stay modest: “We’ve met customers who aren’t sure where to start” says something different from “Everyone clears their garden the wrong way.” Keep the wording as narrow as what you actually know.
When a draft makes a claim outside your experience, don’t fill the gap with a stronger opinion. Either verify the claim using information suited to the question, rework the passage around what you do know, or remove it. If a useful detail comes from a source rather than your own observation, represent it that way.
Once you’ve supplied the right material, AI can still do valuable work. Give it your verified details and ask it to propose a shorter version, offer different openings, or make the order easier to follow. Then review the result again. An edit can accidentally remove a condition, turn an observation into a universal claim, or add a promise you never made.
The practical division is simple: let AI help shape the message, but keep ownership of the decisions inside it. Before you publish, find every claim, recommendation, and business promise. For each one, identify what supports it or revise it until you can. Then add one genuine detail that helps your reader recognize their own situation.
That review does more than protect a single post. Over time, the questions and observations you collect become better raw material for future drafts. The advantage isn’t that AI learns to sound more like a business owner. It’s that the business owner gets clearer about what’s worth saying.
Try This With AI
Use the AI you’re already using: ChatGPT, Claude, Gemini, Grok, Meta AI, Copilot, or another general-purpose AI assistant. Replace the example information inside the brackets with your own information, then copy and paste the complete prompt into your AI.
AI Prompt
Review this marketing draft and any relevant business details or observations I provide: [Paste your draft and any details you know are true. Example: “Spring is here! Prune your plants, add fertilizer, and contact us for a cleanup.” I run a gardening service, and I’ve met customers who aren’t sure what to clear from their gardens. Customers can request an appointment through our contact form.] Separate the writing from the decisions behind it. Identify the most consequential claims, recommendations, implied results, and business promises, explaining what each would need to be true for me to stand behind it. Distinguish details supported by my input from those I need to verify, qualify, or remove. Then identify where a genuine observation I supplied could help the reader make a more useful decision. If I haven’t supplied one, suggest the kind of firsthand detail I could look for without inventing it. Offer a concise revised version using only supported details and natural language, preserving any necessary conditions. Label inferences, flag anything that still needs my review, and don’t invent experiences, facts, results, or business details.
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Reg Ervin
