How to Use AI for Writing Exceptional Content (7 Best Practices)

If you publish writing, you’d be crazy not to use artificial intelligence.

It’s like telling a carpenter not to use a drill. You can build a deck without one. But why would you?

Writers have always embraced new tools to improve their craft.

Writing Tools Timeline

The challenge with AI, or any technology, is that we want the easy way out.

We hope the tech will magically automate everything. And for mediocre content, AI is the perfect solution.

But creating exceptional content is HARD. No matter what tool you use.

For example, I used AI extensively to write this article.

Yet, it still took me 40+ hours to produce.

Why?

AI has made me realize how much I can improve my content. And you can, too.

I asked our content team about how they use AI in their writing and editing.

Our senior writers Yongi Barnard, Kate Starr, Shreelekha Singh, and senior editors Chris Hanna and Chris Shirlow shared their workflows and insights, which I’ll feature throughout this article.

These talented folks help Backlinko generate almost 800,000 sessions per month.

Backlinko – Sessions


Below are seven timeless writing practices supported by AI.

Let’s start with planning your writing project.

1. Use AI to Define Your Audience

Without a deep understanding of your audience, even brilliant insights can fall flat.

AI makes reader research way easier.

You can analyze thousands of real conversations in minutes. No need to spend weeks on interviews or surveys.

A Faster Way to Do Audience Research

Using this article as an example, I wanted to understand how people felt about using AI for writing.

The best place for unfiltered thoughts? Reddit.

So, I Googled “reddit using ai to write good content” and found dozens of threads.

Google SERP – Reddit using AI to Write Good Content

I gathered a handful of community discussions and exported them as PDFs.

Reddit to PDF

Then I gave Claude the following prompt:

I’m researching for a piece about using AI to write good content. I’ve attached five relevant Reddit threads. Please analyze these conversations and create a table of:

  1. Desires: What do people want to achieve?
  2. Pain points: What problems or challenges do they face?
  3. Objections: What concerns or resistance do they express?

For each theme, please include a relevant supporting quote from the discussions.


The result was eye-opening.

Claude – Eye Opening Result

The analysis revealed patterns I hadn’t considered.

It also included quotes that captured the audience’s raw emotions and language.

This helped me ground my writing in real experiences.

You don’t have to follow my exact process. For instance, Kate Starr, our senior writer, uses various sources for audience research:

“I often feed different data sources to AI. This includes Google’s People Also Ask sections and client conversation transcripts. The key is finding real conversations where your target audience expresses their challenges.

I recently took a consulting call transcript and created a detailed customer persona. This helped shape our entire content strategy”.


The key is to use AI to:

  1. Process large amounts of audience data quickly
  2. Identify patterns you might miss manually
  3. Connect insights to real human experiences through quotes

Tip: Create a folder of interesting community discussions. When you find an engaging thread, save it immediately. You never know when that insight will be useful for future content.


2. Use AI to Find Your Unique Angle

It’s easy to get inspired by popular content in your field and remix those ideas.

That’s exactly what AI does by default, too.

A better approach?

Find perspectives that other content and most LLMs overlook. This makes your writing fresh and engaging.

Here’s how to do it in three simple steps.

Step 1: Gather Your Source Material

Find the top 3-5 posts for your topic.

You can do this for social media posts, articles, and emails (if you have access).

For instance, I found three posts on AI writing and copied them to a Google Doc before exporting the text file.

Google Docs – How to Use AI

Step 2: Get AI to Summarize the Data and Suggest Ideas

Take your source materials from Step 1 and ask AI to create a comprehensive analysis.

Here’s a prompt:

I’ve shared several articles about [TOPIC]. Please analyze them and create a detailed breakdown with these categories:

Common Patterns:

  • List 3-4 approaches that appear frequently
  • Include specific examples from the articles
  • Note any patterns in structure or presentation

Assumptions Made:

  • List 3-4 assumptions these articles make without questioning them
  • Point out any gaps in evidence or logic
  • Identify claims that could use more support

Missing Views:

  • List 3-4 important perspectives that aren’t being discussed
  • Note any audience needs that aren’t fully addressed
  • Highlight opportunities for deeper coverage

Notable Elements:

  • List any unique or particularly effective approaches
  • Point out strong evidence or examples
  • Identify innovative structure or presentation

Here’s the output for using AI in writing:

Category Details
Common Patterns
  • Tool comparisons focusing on features over strategy
  • Basic “input/output” workflow examples
  • Generic productivity benefits without specifics
  • Heavy focus on prompt engineering
Assumptions Made
  • More AI usage automatically means better content
  • Readers already understand AI fundamentals
  • One-size-fits-all approaches will work
  • Ethical concerns can be handled with simple disclaimers
Missing Views
  • Quality control processes and measurements
  • Strategic frameworks for tool selection
  • Real examples of human-AI collaboration
  • Cost-benefit analysis for different approaches
Notable Elements
  • One article included detailed workflow diagrams
  • Another featured mini case studies of failures
  • Several had good ethical guidelines
  • One included original research on AI output quality

After analyzing, ask the AI for new ideas based on the opportunities it found.

Here’s what Claude came back with for this article:

Claude AI – Topic Angles

Step 3 – Analyze and Refine Your Angle

Sometimes, the angles are usable with the first output.

But often, it’s a dance between you and the robot to find something compelling.

Here’s how this process shaped this article:

While plenty of tool comparisons and basic workflows existed, few posts offered strategic frameworks for using AI effectively.

As I dug deeper, I noticed something more fundamental.

Everyone was focused on making writing easier. Tools, prompts, shortcuts.

But they were missing the tough reality:

Creating top-notch content is difficult. With AI or not.

That became my angle: How to use AI thoughtfully while embracing the necessary work of writing great content.

Pro tip: Your first insight often leads to an even better angle. Don’t be afraid to evolve your thinking beyond what the initial analysis shows.


3. Use AI to Create An Outline

Nearly every exceptional piece of content starts with a detailed plan. But many writers skip this step.

You risk wasting hours writing in circles or missing the brief entirely.

That’s why our team never writes a draft without a thorough outline.

With AI, creating that outline just got a lot easier.

Strengthen Your Draft Outline Through Collaboration

It’s tempting to ask AI to create your entire outline (losing your unique perspective). Or ignore AI completely (missing valuable insights).

A better approach?

Treat AI as a thoughtful discussion partner.

Our senior editor, Chris Shirlow, emphasizes using AI strategically during outlining:

“I use my own competitor analysis to create outlines first. Then, I’ll use AI to spot potential gaps. For example, when outlining an email marketing guide, AI might suggest adding a section on automation that I hadn’t considered”.


The key is to start with your own research. This ensures the foundation reflects real expertise. Then, use AI to refine and expand your thinking.

With this article, for example, I started with some loose structural notes:

  1. Demand
  2. Audience
  3. Angle
  4. Structure
  5. Research
  6. Writing
  7. Visuals
  8. Enhancements
  9. Editing

Then, I prompted Claude with some attached reference material.

Hey Claude, I’m writing an article about using how to use AI to write better content. I’ve prepared my brief and a very loose outline. I’ve also attached an article that inspired the idea.

What are your initial impressions of my approach?


Claude’s analysis (I’ve summarized the output):

Strong Points

  • AI positioning: Framed as a tool (like a carpenter’s drill) rather than a replacement
  • Realistic expectations: Acknowledges content creation remains challenging (40-hour example)
  • Timeless focus: Principles over specific AI tools/prompts for longer relevance
  • Credibility: Using concrete case studies and personal examples

Areas for Development

  • Structure: Consider combining overlapping principles (e.g., “Audience” and “Research”)
  • Implementation: Add more specific examples of AI enhancing each practice
  • Meta-narrative: Strengthen how we’re using AI to write this very article
  • Balance: Include section on AI limitations for completeness

From the AI’s first output, we started our collaboration.

Claude helped me name each element “practices” instead of “tips.

We challenged each other on the substructure of each practice.

Then it suggested H2s—many of which I didn’t like.

Through a LONG chat and many pauses of me returning to my document, we landed on an outline.

Here’s how the structure evolved through discussion:

Version 1 Version 2 Version 3 Version 4 Version 5
Demand Deep Research: Moving Beyond Surface-Leval Facts Talk to Your Customers First Define Your Audience Use AI to Define Your Audience
Audience Audience Understanding: Creating Content That Deeply Resonates Build Your Audience Map Find Your Unique Angle Use AI to Find Your Unique Angle
Angle Strategic Positioning: Finding Your Unique Angle Develop Your Unique Angle Create a Clear Outline Use AI to Create an Outline
Structure Narrative Architecture: Building Clear, Compelling Flow Structure Your Content Flow Research Your Topic Use AI to Research Your Topic
Research Evidence & Examples: Making Ideas Concrete Show, Don’t Just Tell Writing Engaging Content Use AI to Write Engaging Content
Writing Voice & Style: Crafting a Distinctive Presence Find Your Brand Voice Add Valuable Supporting Elements Use AI to Add Valuable Supporting Elements
Enhancements Enhancement Elements: Amplifying Impact Add Powerful Enhancements Edit for Impact Use AI to Edit Your Draft
Editing Refinement & Optimization: Polishing for Performance Polish Your Final Product

This iterative process helped me:

  1. Make headings more action-oriented
  2. Create a consistent pattern (“Use AI to…”), which also helps for search engine optimization

Let’s look at how AI can help you turn this outline into content through research.

4. Use AI to Research Your Topic

Research has always been the foundation of excellent writing.

Pre-internet, research meant hours in libraries digging through catalogs, journals, and textbooks.

Then, digital changed everything. But it created a new problem:

Information overload.

Writing Places Timeline

Now you have instant access to millions of sources.

Blog posts. Academic papers. Community discussions. Expert interviews. Analytics data.

But do you have time to process it all?

That’s where AI shines.

It can scan thousands of sources in seconds, helping you catch insights you might miss.

Let’s explore how to use it effectively.

Using AI for Primary Research

When you do interviews, gather raw data, or run surveys, you create unique content that’s hard to copy.

The trick is to use AI throughout the research process—not just for analysis.

Planning Better Research Questions

The quality of your research depends on asking the right questions.

For example, when writing this article, I initially planned to use only my own AI experiences as examples. But something felt missing.

So, I started a discussion with Claude:

Me: I’m finding limitations in my thinking. I could add more perspectives by surveying our editorial team about how they use AI.

AI: This could significantly strengthen the article. Multiple writers demonstrating how they tackle AI challenges would make your points more powerful than theory alone.

Consider:

  • What specific insights you need
  • The most efficient way to gather them
  • How to make participation easy

With Claude’s validation, I developed survey questions through an iterative process.

If you want to try this approach, here’s a template to get started:

Before we design specific questions, please evaluate this research approach:

  • Target: [describe who you’ll survey/interview]
  • Goal: [what you need to learn]
  • Method: [how you plan to gather data]
  • Timeline: [your constraints]

Identify any:

  • Potential issues
  • Missing opportunities
  • Ways to improve efficiency

Then, the research questions:

Help me create [survey/interview] questions about topic.

Consider:

  • Audience: [describe participants]
  • Time constraints: [expected time commitment]
  • Key objectives: [list 2-3 main goals]
  • Required output: [what you need to create]

Structure questions to be:

  • Focused yet open-ended
  • Easy to answer quickly
  • Specific about examples needed

Finally, test your questions:

Here are my draft questions. Please analyze them for:

  • Clarity and potential confusion
  • Leading or biased language
  • Gaps in coverage
  • Logical flow

Example:

After several rounds with AI, my original idea of “let’s survey the team” changed to:

  • A focused survey using conditional logic
  • Clear examples of what I needed
  • A friendly, collaborative introduction
  • Specific prompts for AI usage

The result? Rich insights from the team that enhanced this article.

Getting More from Expert Interviews

Want to fully engage with your interview subjects while capturing all the details? AI can help.

Start by recording your conversations (with permission, of course). Have a real dialogue. Follow interesting threads. Then, let AI help you extract every valuable insight.

Here are some simple prompts:

Prepare your interview.

Please help me prepare for an expert interview about topic.

Review this background material and suggest:

  • Key discussion areas to cover
  • Follow-up questions for each area
  • Potential examples to request
  • Data points to validate

Process the recording.

I’ve shared a transcript of my expert interview about topic. Please:

  1. Create a structured summary of key points
  2. Extract specific examples and case studies
  3. Identify unique insights or perspectives
  4. Pull compelling quotes
  5. Note areas needing clarification or follow-up

Validate insights.

Here are my key takeaways from the interview. Please:

  1. Check if conclusions are supported by the transcript
  2. Identify any assumptions I’m making
  3. Suggest additional context needed
  4. Note alternative interpretations

Making Sense of Raw Data

The challenge of research isn’t gathering data—it’s finding the story in it.

When our editorial team finished the AI usage survey, I faced this exact situation.

I wanted to process the responses quickly, but also to capture every valuable insight.

Here’s how AI helped me analyze the responses:

Get a high-level overview.

I’ve shared our team’s survey responses about AI usage. Please:

  1. Identify common patterns across responses
  2. Note unique or unexpected approaches
  3. Highlight particularly detailed examples
  4. Suggest potential themes to explore

Drill down to the specifics.

For the [specific practice], please analyze:

  1. Different approaches team members use
  2. Most successful use cases
  3. Common challenges or limitations
  4. Specific tools or prompts mentioned
  5. Notable workflow differences

Extract supporting material.

From these responses about topic, please:

  1. Find compelling quotes that illustrate key points
  2. Identify concrete examples with clear outcomes
  3. Note any interesting AI prompts shared
  4. Suggest potential visuals or diagrams

This analysis revealed that our team uses AI differently for each practice. Some excel at research, others at editing.

For instance, everyone stressed the need to use AI carefully. And not fully depend on it.

Pro tip: Before using AI to analyze data, clearly define what “valuable insights” means for your project. This helps AI focus on what matters most.


Using AI for Secondary Research

Secondary research meant spending hours reading papers, reports, and discussions.

Not anymore.

AI reshapes how we process existing content.

Let’s look at some use cases.

Extracting Audio and Video Content for Gems

Some of the best insights are buried in hour-long podcasts and conference talks.

Founders share behind-the-scenes stories. Experts reveal their frameworks. And industry veterans discuss trends they haven’t written about yet.

But watching hours of video isn’t always practical.

AI can save time here.

Here’s how I used AI to extract powerful insights from founder interviews for my ecommerce growth strategies article:

First, I found a podcast where Who Is Elijah’s founders shared their journey to $20M in revenue.

Youtube – Foundr Video

Then, I used Rev AI to transcribe the full interview.

Rev AI – Transcription

Instead of reading through 19,000 words of transcript, I had Claude analyze the conversation with this prompt:

“I’m writing about ecommerce growth strategies. Please analyze this founder interview and:

  1. Identify key decisions that drove growth
  2. Extract specific metrics and results
  3. Find unique insights about their process
  4. Pull compelling quotes to support each point”

The analysis revealed a fascinating story about operational efficiency:

  • They cut their team from 44 to 21 people
  • Shifted from full-time specialists to agency partnerships
  • Rebuilt their systems from scratch
  • Turned unprofitable (-60%) campaigns into winners

This single podcast gave me both a compelling case study and practical lessons readers could apply.

Synthesizing Complex Documents

Academic papers and industry reports contain valuable data. But they’re often dense, jargony, and hard to apply practically.

Shreelekha Singh, our senior writer, uses detailed context to get better research results from AI.

“When writing about AI in healthcare, I always share my article’s specific objectives and approach with Perplexity.

I’ll outline that I need evidence-based analysis focused on measurable outcomes. Not just predictions.

This detailed context helps AI find more relevant research papers and case studies.”


Another example:

When writing an article about information gain, I needed to wrap my head around Google’s patent application.

But it’s written in technical language that would make your eyes glaze over.

Google Patent

Instead of getting overwhelmed, I used AI to help me interpret this complex material.

I uploaded the patent application to Claude and asked about information gain signals.

Claude helped identify and explain relevant metrics like “UserActionSignals” and “ClickSatisfaction” in plain language.

I quickly learned Google’s process for evaluating and testing new information.

The same approach works for:

  • Academic papers and studies
  • Technical documentation
  • Industry reports
  • Legal documents
  • Research data

The takeaway?

Think of AI as your study partner. One that can read a 100-page document in seconds and explain the key points in plain English.

5. Use AI to Write Engaging Content

LLMs generate pretty good output with minimal prompting.

But producing engaging writing in your authentic voice? That’s where AI can be rather underwhelming.

I’ve been trying to write with AI since 2021, and I’m convinced the models have a default writing style.

AI LOVES writing in contrasting pairs: “Not this. But that.”

It also enjoys phrases like “transform,” “game-changing,” “leverage,” and “optimize.” (Not that there’s anything wrong with these words.)

Common AI Writing Patterns

And if AI could write your entire project in a list, it would.

If you’re often dissatisfied with the output, let me show you how to get better results.

Create Excellent Reference Materials

The more specific context you can give AI, the better the output matches your style.

This means defining your writing style clearly.

How?

Create detailed guidelines, including:

  • Reader personas
  • Target grade level
  • Headline formulas
  • Tonality
  • Examples
  • Opening hooks

In addition to your guidelines, make it your mission to create the perfect article or chapter to use as a writing sample.

Once you have your guidelines and examples, you’ll be more satisfied with the AI output.

For example, I’ve created a dedicated project in Claude for Backlinko. It has over 20k words of reference materials.

Claude – Project Knowledge

Every time I start a new conversation, Claude has this context readily available.

There’s no need to explain our style requirements over and over.

Tip: If your AI tool doesn’t have a project feature, you can save your resources in a folder on your computer. Then, you can use them in your chats.


Build Progressive Context

Your conversation with AI should evolve as your content develops.

Take this article section as an example. I started a dedicated chat on “Using AI for Writing.” I shared:

  • The outline
  • The article draft so far
  • Team survey responses
  • My goals for this section

When I write the next section about supporting elements, I’ll start a new chat. But I’ll include this completed section as reference material.

Writing AI Sessions

This progressive approach helps AI maintain consistency while adapting to each section’s unique needs.

Shreelekha uses a similar method.

“I create different projects for different aspects of my writing. This helps me maintain focus and ensures AI has exactly the context needed for each task”.


Depending on your LLM, this sectional approach will help manage your daily credits as long chats burn through your usage.

Pro tip: Write the first 10% of your project from scratch. This will set the tone for your piece and give AI a clear direction for better outputs.


Embrace Messy Collaboration with AI

The best AI writing output happens through conversation.

Share your half-formed ideas. Question its suggestions. Challenge it to think deeper.

For instance, when writing this section, I asked AI to expand on my outline. But I didn’t just accept the first response.

Instead of settling for general advice about “prompting for a specific tone,” I asked for concrete examples of how AI’s default writing differs from Backlinko’s style.

This led to identifying specific phrases and patterns.

For instance, here’s how my opening hook evolved through AI collaboration:

Evolution of an Opening Hook

You might go sentence for sentence, idea for idea, until you strike gold.

It can be tedious, but it’s better than doing it alone.

Find Perfect Examples (When You Need Them)

LLMs excel at suggesting relevant examples and case studies to strengthen your writing.

Shreelekha uses AI to brainstorm examples when she’s stuck:

“I describe the concept I’m trying to illustrate and the type of example I need. AI often suggests angles I hadn’t considered, which I can then research further.

Here’s my go-to prompt template:

“I’m explaining [concept]. I need an example that shows [specific aspect]. Ideally from [industry/type of company]. The example should demonstrate [desired outcome].”

For instance, while writing about data visualization, I needed examples of companies using charts effectively in their content. I gave AI these parameters, and it suggested looking at HubSpot’s State of Marketing report—which perfectly illustrated my point about making complex data accessible.

But don’t just take AI’s suggestions at face value. Use them as starting points for deeper investigation. When AI suggests an example, I:

  • Verify the details independently
  • Look for additional context
  • Consider alternative examples
  • Evaluate if it truly serves my argument


Chris Shirlow emphasizes this balanced approach:

“The key is to start with your own ideas and research. Then use AI to expand those concepts and find fresh angles. Never let AI drive the direction of your content.


6. Use AI to Create Content Assets

Content assets like checklists, calculators, and infographics turn your writing into practical tools for readers.

The right asset can clarify complex concepts, aid learning, or guide important decisions.

Creating these resources once required designers and developers.

AI makes it possible to create without these skills.

Create Visual Assets

Many readers don’t consume every word you write.

They scan. They skim. They look for visual anchors to guide them through your ideas.

A study by MIT found that the human brain can process images in as little as 13 milliseconds. That’s up to 600 times faster than text.

Speed – Image vs Text

But creating professional graphics used to mean:

  • Learning design software
  • Understanding design principles
  • Spending hours on each visual
  • Hiring expensive designers

Not anymore.

AI can help you create compelling visuals in seconds.

For example, in our 4 P’s of Marketing article, our senior writer, Yongi Barnard, used a graphic to explain why personalization matters.

Why Personalization Matters

The visual tells a compelling story at a glance.

To recreate this, gather your data.

Then, give AI parameters:

“Please help me design a graphic showing these three personalization statistics:

  1. 80% of consumers are more likely to purchase if brands offer personalized experiences
  2. 48.2% of marketers say personalization improves click-through rates the most
  3. 66% of customers expect companies to understand their personal needs

Use:

  • A clean, minimal design
  • Progress circles to represent percentages
  • Dark background with light text for contrast
  • Short, clear descriptions under each statistic
  • Space for source attribution”

Then, you just need to refine the finishing touches (colors, spacing, etc.).

Pro tip: Don’t just think about data visualization. Use AI to create:

  • Process diagrams
  • Comparison charts
  • Timeline graphics
  • Concept illustrations
  • Feature breakdowns


Our senior editor, Chris Hanna, puts it well:

“The best writers think like producers now. They ask themselves: how can I make this concept visual? How can I show instead of tell?

AI makes that possible without becoming a design expert”.


Create Smart Checklists

Converting processes into checklists makes your content more actionable.

But creating an effective checklist isn’t as simple as writing bullet points. You need to:

  • Break down complex processes
  • Put steps in the optimal order
  • Include validation checks
  • Add resource links
  • Consider different user scenarios

This is where AI can help.

The key is to prompt AI after you’ve written your draft.

This way, the LLM will have full context for your content and can create more detailed, relevant checklists.

For example, our senior editor, Shannon Willoby, made a 12-month checklist to help with her article on starting a blog.

Backlinko – Blog Launch Checklist

She prompted AI to create the checklist based on her article content. Pretty simple but effective.

Here’s a template to get started:

“I’ve written an article about topic. Please create a comprehensive checklist that:

  • Breaks down each major step
  • Includes key decision points
  • Notes important resources needed
  • Flags common pitfalls to avoid
  • Suggests ways to validate progress”

Build Interactive Tools

Interactive tools like calculators, analyzers, and decision trees turn your knowledge into useful solutions. Readers can use these tools right away.

There are many opportunities, regardless of your industry:

Say you write about productivity. You could create a workload capacity analyzer that helps readers balance their projects.

Claude – Workload Capacity Analyzer

If you’re a wellness writer, you might develop a habit-stacking planner to help people create healthy routines.

Claude – Habit Stacking Planner

Or, if you’re a gardening expert, you could create a seasonal planting calculator.

Claude – Seasonal Planting Calculator

For my ecommerce growth strategies article, I used AI to build an interactive profitability calculator.

Backlinko – Profitability Calculator

Instead of explaining formulas, readers can explore different scenarios to understand how variables like cost of goods sold (COGS), shipping, and marketing expenses impact their bottom line.

The best part?

You can bring these AI-designed tools to life using no-code platforms like Calculator Studio. Here’s how:

  1. Identify calculation needs in your content
  2. Ask AI to help structure the logic and formulas
  3. Design the user interface (AI can mock this up)
  4. Build it in your no-code tool of choice

For instance, when building the profitability calculator, I prompted AI with:

“I need a calculator that helps ecommerce owners estimate profitability. It should:

  • Include key metrics like COGS, shipping, and marketing costs
  • Calculate gross and net margins
  • Show breakeven analysis

Start simple.

A basic calculator that solves one specific problem well is better than a complex tool that confuses users.

7. Use AI to Edit Your Draft

Editing is the difference between good content and exceptional content.

But getting quality edits can be expensive and slow. You either:

  • Pay editors by the hour
  • Lose billable time as a freelancer
  • Wait through lengthy review cycles
  • Miss issues when editing your own work

AI changes this dynamic.

You can get quick, unbiased feedback and try different versions before your editor reviews a draft.

Let me show you how to do this effectively.

Get Strategic Input First

It’s tempting to jump right into line editing—fixing grammar and polishing sentences.

But start with the big picture.

Here’s how Chris Hanna uses AI for strategic editing:

“I feed the draft, outline, and brief to Claude. Then I ask: What’s missing? Where could we strengthen the argument? Which sections need more evidence?”


AI can help by:

  • Comparing your piece against successful examples
  • Identifying patterns and gaps
  • Suggesting structural improvements

This approach saves revision time. Why polish paragraphs you might cut or rewrite anyway?

Create Quick Quality Checks

Once you have your structure solid, create systematic quality checks.

You want to verify your content hits key engagement metrics.

At Backlinko, we track three readability metrics:

  1. Single-Sentence Paragraph Percentage: The ratio of paragraphs with just one sentence.
  2. Visual Break Density: Number of visual elements per 1,000 words. Higher density means better scannability.
  3. Grade Level: We target Grade 7 or below for accessibility.

Claude – Content Quality Checker

AI can calculate these instantly and suggest specific fixes. Here’s how:

  1. Share your metrics targets with AI
  2. Paste in a section of your content
  3. Ask for both analysis and specific fixes

Beyond metrics, use AI to check for:

  • Redundant ideas and phrases
  • Passive voice overuse
  • Transition effectiveness
  • Brand voice consistency
  • Technical accuracy

Test Critical Elements

Some parts of your content matter more than others.

Your headline determines whether people click.

Your introduction decides if they stay.

Your calls-to-action influence if they convert.

These elements deserve extra attention.

Using headlines as an example, I note 3-5 potential titles.

I Google the topic I’m writing about and screenshot the search results.

Google SERP – How to use AI for Better Writing

I upload the screenshot to Claude. Then, I ask how my title ideas compare to the top articles.

Claude will make suggestions based on our title guidance, best practices, and differentiators.

Yongi uses a similar process for introductions:

“I write three different openings and ask AI which one creates the strongest hook. Then we discuss why—looking at elements like curiosity, relevance, and emotional pull”.


You can also test:

  • Section transitions
  • Examples
  • Proof point placement
  • Technical explanations
  • Closing arguments

Balance AI and Human Editing

AI accelerates the editing process, but human judgment remains essential.

Here’s how to make this work:

  1. Start with AI for broad analysis and quick fixes
  2. Apply your judgment to AI’s suggestions
  3. Test variations of important elements
  4. Verify technical accuracy independently
  5. Maintain your unique voice and perspective

Chris Shirlow supports this balance:

“AI helps us identify potential issues faster. But we still need human expertise to decide what changes actually serve our readers.”


Start Writing Smarter, Not Harder

Pick one project you need to write this week.

Apply just one of these practices—maybe getting AI’s help with audience research or outlining.

That’s all you need to do to start seeing results.

Ready to put these practices to work? Check out our guide on how to write a blog post.

You’ll see how to combine these AI techniques with proven writing principles to create content that ranks and converts.

The post How to Use AI for Writing Exceptional Content (7 Best Practices) appeared first on Backlinko.