How to Edit Like an Editor (With Help From Generative AI)

Generative AI won’t replace a sharp editor. But if you use it right, it can sharpen your instincts, cut the grunt work, and raise your editorial floor.

Here, you’ll learn how to craft precise prompts, manage tone, avoid common missteps, and choose the right AI tools to complement your editing. In short, I’ll show you how to fold AI into your editorial workflow without losing your edge — or your voice.

Create a Smarter Editing Workflow with AI

Pair traditional editing with smart prompts. You’ll catch more issues and clarify your message without losing that human touch.

1. Use the Right Language

AI follows your lead. If you give it bad directions, you’ll get bad edits. Solve this with highly specific prompts that mirror the language we’d use in a newsroom.

Here are the terms I use, along with prompt examples.

Punchier: Make the writing more concise and energetic by cutting filler and collapsing long sentences.

“Make this paragraph punchier, and choose stronger verbs to grab the reader’s attention.”

Tighten: Streamline the copy by removing redundancies and unnecessary words.

“Tighten this section without losing the clarity or meaning.”

Soften: Adjust blunt or aggressive phrasing to sound more diplomatic.

“Soften this paragraph. Right now, it’s too aggressive for our brand.”

Brighter: Shift the tone to sound more upbeat, hopeful, or optimistic.

“This CTA reads as sad. Give me a brighter version without changing the core message.”

Reword: Replace awkward, unclear language with smoother alternatives.

“Reword this weird sentence. Give me three smoother alternatives that keep the meaning intact.”

Deeper: Add nuance or insight to strengthen a point.

“Make this section deeper with a relevant, real-world example or statistic that reinforces the main idea. Prioritize accuracy and clearly indicate your source.”

Expand: Develop under-explained ideas with more context or support.

“Expand this idea. Give me at least two more sentences that don’t duplicate the content.”

Pro tip: “Expand” and “Deeper” prompts can invite hallucinations — instances when AI generates plausible-sounding (but entirely incorrect) details. Always check the AI’s facts!

Along the same lines, when you use “tighten,” check the phrasing to make sure the sentence still means what you want it to.

2: Lock in the Right Tone

Tone is the lifeblood of a brand, giving your voice consistency regardless of the channel or medium. To maintain that consistency when using AI for editing, give it the same tone guidance for every copy project.

If you already have brand copy guidelines, just add those to your initial prompt whenever you begin editing a new piece. When I’m using ChatGPT, I’ll attach a doc with brand guidance along with the draft and, then, start my editing session with a prompt like this:

“Edit the attached draft according to the guidelines provided in the attached brand voice document. Ensure tone, phrasing, and style match the guidance precisely.”

If you don’t have voice and tone guidance in place, then choose three to five adjectives that capture your brand’s personality. For instance:

• Confident.
• Approachable.
• Insightful.

Consistently reinforce your tone by adding and defining these adjectives in your editing prompts for each new piece. For example:

“When editing this copy, ensure the tone remains (1) confident: clear, decisive, assured; (2) approachable: friendly, relatable, welcoming; and (3) insightful: thoughtful, perceptive, informed.”

That said, tone often requires fine-tuning at the paragraph level. Here are some practical prompts to help you get the AI back on track, using the example adjectives above:

• “Make this paragraph sound more confident by removing qualifiers and expressing ideas clearly and decisively.”

• “Rewrite this section to be more approachable, like you’re advising a trusted peer.”

• “Enhance this paragraph by adding a meaningful insight that demonstrates deeper understanding of the topic. Include a relevant, accurate example or data point to support it, and cite your source.”

Getting your brand’s tone of voice right is about making sure the copy has the kind of personality that connects with your audience. AI can help fine-tune the tone of your content, but only if you give it clear, deliberate guidance.

Read more: Driving Innovation: Generative AI’s Impact on 80 B2B SaaS Companies

3. Talk to It Like It’s a Person (or a Duck)

In software, some devs keep a rubber duck on their desk. When they have a particularly complex coding issue, they talk to the duck. Saying things out loud has a way of helping you organize your thoughts and spot problems.

The same principle applies here. When you tell the AI what’s not working, you help yourself understand why it’s not working.

When you create the initial prompt to edit a piece, contextualize your ask by telling the AI to take on the role of an editor. Explain the copy’s purpose and audience as well as your desired outcome for readers.

For example:

“Assume the role of an experienced editor reviewing a customer-facing email announcing a new software feature. The audience is small business owners who value clear, concise communication. Edit the copy, so readers quickly understand the feature’s benefits and feel motivated to try it.”

As you work through the piece, give the AI feedback on revisions like you would to a junior editor:

1. When you know a sentence isn’t working, but don’t know why, ask for three different versions.
2. Don’t like the revisions you’re getting? Say so, and explain why.
3. Ask why the model suggested a change, deleted a word, or added a stat.

When in Doubt, Try Again

If the AI isn’t giving you what you want, just close the conversation and start with a fresh prompt.

Before you end the session, ask the AI to summarize what it learned from your conversation. Use that summary when crafting your next prompt. If you’re consistently getting stuck, consider switching to a different AI model that might better fit your needs.

Obviously, the bot doesn’t really understand you, but going through the process of refining copy this way will help you get the messaging right.

4. Know Where It Falls Short

AI isn’t magic. It breaks in predictable ways. Learn those, and you’ll stay in control.

Comprehension

Generative AI doesn’t truly “get” your content. To vastly simplify things, it relies on pattern recognition, predicting the next word or phrase based on vast amounts of training data.

While this can produce coherent and contextually relevant text, AI lacks genuine comprehension of meaning, nuance, or strategic intent.

The general solve for this is better prompts, like the examples sprinkled throughout this article.

Read more: From AIOs to LLMs: How B2B Teams Must Evolve Search Strategy and Reporting for the AI Era

Hallucinations

Statistics are great for search engine optimization (SEO), but they have to be right or they’re useless to your audience. As I mentioned, AI models sometimes confidently make things up. It might even hallucinate citations. (Ask your legal team how that’s working out.)

Combat this by always asking for sources and, then, actually clicking on or Googling those sources.

A more insidious problem is when AI gets it kind of right. I’ve seen this happen most often when asking a large language model (LLM) to explain a product feature in less technical terms.

For example, the AI might simplify a nuanced database integration feature by describing it as “real-time syncing.”

That sounds accurate on the surface, right? But if your product actually syncs at short intervals, this oversimplification could mislead your customers and create unrealistic expectations.

If you don’t have the expertise to fact-check specific things about your brand’s product or service, run the copy by a subject matter expert before you go live.

Token Limits

A context window is the amount of text a generative AI model can process and “remember” during a single conversation. It’s measured in tokens, or units roughly corresponding to words or parts of words. There’s a limit to how many tokens you get for a given interaction.

When you’re working with longer content (e.g., ebooks, scripts, really long blogs), it’s easy to hit that limit. This can also happen when you’re going back and forth with lots of follow-up prompts.

You know you’ve hit the limit when you start seeing weird behavior, like:

• Abrupt endings: The AI suddenly stops mid-sentence or mid-thought without completing the response.
• Ignored instructions: It fails to pull in details provided in your initial prompt, such as giving three examples instead of five.
• Generic output: Responses become overly vague or repetitive because the model lacks the space to consider detailed context.
• Explicit warnings: Some platforms will simply tell you when you’ve exceeded the model’s token limit or context window.

To avoid this, segment longer content projects into smaller chunks, and clearly restate essential context, like your brand tone or the piece’s purpose, in each new conversation.

Don’t Start With AI-Generated Copy

Listen: AI generation is great for quickly building out libraries of templates, glossaries, and FAQs.

But if you lean on AI to write your bottom-of-funnel blogs, white papers, and thought leadership, you’re going to get lost in the search engine results page (SERP). Frankly, I’ve watched it happen to dozens of great brands.

There’s a whole industry devoted to “editing” AI copy these days. Nine times out of ten, they’re just rewriting it. No matter what training data you feed it, AI-generated text lacks accuracy, depth, and your brand’s unique perspective.

You’ll save a ton of time editing if you start with a clear outline, plenty of research, and a human’s words.

5. Use the One You Already Have

At the end of the day, editing is just complex pattern recognition, and every LLM is already great at that. The model matters a lot less than your ability to prompt effectively.

Here’s a breakdown of the current big names and what they’re good at.

For full transparency, I use ChatGPT because Directive bought me a license. But for the purposes of editing with AI, you genuinely can use whatever you have at hand.

Read more: 6 Tips for Integrating AI With Your Existing B2B Marketing Tech Stack

6. The Last Eyes on Copy Should Be Yours

AI can get you 80% there, but the last 20% is all you.

Here’s the steps I’ve been following years:

• Read it aloud to hear the flow and catch sentences that’ll trip readers up.
• Add value by inserting links, first-party data, industry-specific insights, and “from the field” anecdotes.
• Fact-check every number, reference, quote, and explanation.
• Break up the walls of text using bullets and subheaders or just making new paragraphs.
• Fix the structure by moving sections around and adding strong transitions.

When doing your final pass, read it out loud again. But this time, go backwards, sentence by sentence. You’ll catch things your brain skipped over the first time.

Build Better Content with the Right Partner

Sorry to bury the lede, but using AI tools effectively in your editing won’t save you much time. Instead, the bots can help you make better decisions, which, ultimately, leads to better copy.

I’ve spent more than 20 years in publishing, both print and digital. I’ve seen the technology shift from red pens and Dictaphones to Slack threads and WordPress.

Technology alone never made anyone a better editor. But, learning how to use new tools to enhance the editing process actually works.

Still, if you’re hoping to use AI to get content published more quickly, maybe what you really need is some human help. That’s where we come in.

At Directive, we help marketing teams:

• Publish more content without sacrificing quality.
• Deliver leads that qualify with sales.
• Develop a brand voice that actually connects.

Whether you need an audit, a few extra hands, or a production engine that doesn’t cut corners, we’ve got you covered.

Let’s talk if you’re ready to scale like an editor: sharp thinking, clean execution, and no wasted words.

Book an intro call today.