How to Use AI to Optimize Existing Content for Search Intent

 Introduction

Publishing an article and waiting for Google to rank it is no longer a reliable content strategy.

Search results change. Competitors publish new resources. Searchers change the way they phrase questions. Products and technologies become outdated. Even an article containing the right keywords can underperform when it does not satisfy what the searcher actually wants.

This is where search intent optimization becomes important.

Understanding search intent also becomes easier when you combine it with structured AI SEO research and optimization

Instead of immediately creating another article, you can often improve the content you already have.

Artificial intelligence can help you analyze an existing article, understand the likely intent behind its target query, identify missing information, detect repetition, review competing content, find potentially outdated sections, and create a structured improvement plan.

However, AI should support the editorial process—not replace it.

A practical workflow looks like this:

Existing Content → AI Analysis → Search Intent Diagnosis → Content Improvements → Human Review → Publish → Measure

In this guide, you'll learn how to use AI to optimize existing content around search intent while preserving originality, usefulness, accuracy, and human judgment.

 

A practical AI-assisted workflow for improving existing content while keeping human editorial judgment at the center

What Is Search Intent?

Search intent is the underlying reason someone enters a query into a search engine.

When a person searches for something, they usually have a goal. They may want to learn, find a particular website, compare options, or take an action.

For example:

• "what is search intent" → The searcher wants an explanation.
• "how to identify search intent" → The searcher wants instructions.
• "best AI SEO tools" → The searcher is comparing options.
• "Ahrefs pricing" → The searcher wants product and pricing information.
• "buy SEO software" → The searcher may be ready to make a purchase.

Search intent is often grouped into four broad categories.

1. Informational Intent

The searcher wants to learn something.

Examples:

• What is AI SEO?
• How does search intent work?
• What is topical authority?
• How does Google Search work?

2. Navigational Intent

The searcher wants to reach a particular website, service, or page.

Examples:

• Google Search Console
• Canva login
• ChatGPT
• Microsoft Copilot

3. Commercial Investigation

The searcher is researching options before making a decision.

Examples:

• best AI writing tools
• ChatGPT vs Claude
• best SEO tools for bloggers
• Canva vs Adobe Express

4. Transactional Intent

The searcher is ready to take an action such as purchasing, subscribing, downloading, or signing up.

Examples:

• buy SEO software
• download keyword research template
• Grammarly premium pricing
• subscribe to an SEO platform

These categories are useful, but search intent is not always perfectly divided into four boxes. A query can have multiple possible interpretations.

Your goal is therefore to understand the dominant intent and make sure your article satisfies the searcher's most important needs.

 

Why Existing Content Can Underperform

An article can underperform for many different reasons.

Sometimes the problem is technical SEO. Sometimes the topic itself has little demand. In other cases, the page simply does not provide the information searchers expect.

Common problems include:

• The article targets the wrong search intent.
• The introduction takes too long to answer the main question.
• Important subtopics are missing.
• Information has become outdated.
• Headings do not reflect the reader's questions.
• The article is too broad or too narrow.
• Several sections repeat the same information.
• Competitors provide more useful examples.
• The title promises something the article does not deliver.
• The article provides theory but little practical guidance.
• Internal links are weak or irrelevant.
• Important claims are unsupported.
• The article contains unnecessary filler.
• The content does not demonstrate a clear reason for the reader to trust it.

AI can help identify many of these issues quickly.

But identifying a problem is not the same as deciding how to fix it.

That final decision should remain human.

 

Why Optimize Existing Content Instead of Always Creating New Content?

Creating new content is important, but creating more pages is not always the best answer to declining performance.

An existing article may already have:

• A published URL
• Historical performance data
• Search impressions
• Existing rankings
• Internal links
• Backlinks
• Topical relevance
• Existing readers
• Useful original information

Instead of starting from zero, you can improve an asset that already has some history.

A balanced content strategy can therefore combine:

New Content + Existing Content Optimization

For example, instead of publishing five new articles every week, a site could publish new content while also reviewing older pages that have ranking potential.

The objective is not to update every old article simply because it is old.

The objective is to identify pages where meaningful improvements could make the content more useful.

 

Step 1: Choose the Right Article to Optimize

Don't randomly choose an old article and ask AI to rewrite it.

First determine whether the page is actually worth improving.

Google Search Console can provide useful evidence.

Look for articles that:

• Receive impressions but relatively few clicks
• Rank around page two or three for valuable queries
• Have declining organic performance
• Receive many impressions but have a weak click-through rate
• Appear for several related queries
• Contain outdated information
• Have useful backlinks but weak content
• Target an important topic but provide incomplete coverage

For example, imagine an article currently appears around position 11 for:

"AI content optimization"

That page may be a stronger optimization candidate than an article receiving almost no impressions.

The goal is not simply to update old pages.

The goal is to identify pages where improvement has a reasonable opportunity to create more value for readers and potentially improve search performance.

 

Step 2: Collect Evidence Before Asking AI to Change Anything

One of the most important improvements you can make to your workflow is separating evidence collection from AI recommendations.

Before asking AI to optimize an article, collect:

• Target keyword
• Search Console queries
• Current average position
• Impressions
• Clicks
• CTR
• Existing title
• Existing article
• Target audience
• Relevant competing pages
• Important internal links
• Outdated information
• Business or editorial objective

This gives the AI useful context.

Without context, AI may produce generic SEO advice.

With context, it can perform a much more useful editorial analysis.

 

Step 3: Diagnose Search Intent Before Rewriting

One of the biggest mistakes in AI-assisted SEO is starting with:

"Rewrite this article for SEO."

That instruction is too vague.

Before rewriting anything, ask AI to diagnose the problem.

AI Prompt: Search Intent Analysis

Analyze this existing article for the target query "[KEYWORD]."

Determine:

1.     The likely dominant search intent.

2.     Secondary search intents.

3.     What the searcher is probably trying to accomplish.

4.     What questions the searcher expects the page to answer.

5.     Whether the current article satisfies those needs.

6.     Which sections are useful.

7.     Which sections are irrelevant or unnecessary.

8.     Which important topics appear to be missing.

Do not rewrite the article yet.

First provide an editorial diagnosis and explain the reasoning behind each recommendation.

The important part is the final instruction:

Diagnose first. Rewrite later.

AI can help identify the dominant search intent and reveal whether existing content actually answers the searcher's underlying question

Step 4: Analyze the Current Search Results

Search results provide useful clues about what information searchers are currently being served.

Review several relevant pages ranking for your target query.

Look for patterns such as:

• Content format
• Major topics
• Common questions
• Examples
• Definitions
• Step-by-step instructions
• Comparisons
• Original research
• Tools and resources
• Frequently discussed problems

You can then ask AI to help organize your observations.

AI Prompt: Competitor Content Analysis

Analyze the following competing pages for "[KEYWORD]."

Identify:

·       Common topics

·       Important questions

·       Content formats

·       Useful examples

·       Unique perspectives

·       Information that appears consistently

Then compare these patterns with my existing article.

Identify:

·       Topics I already cover well

·       Potential information gaps

·       Weak sections

·       Opportunities for better examples

·       Opportunities to provide a more useful experience

Do not copy competitor wording or structure. Use the analysis only to understand reader expectations and identify opportunities for original improvement.

Competitor research should help you understand the information landscape, not imitate another publisher.

 

Step 5: Identify Meaningful Content Gaps

A content gap does not simply mean:

"My competitor has 3,000 words and I have 1,500."

Word count alone is not a useful definition of content quality.

A meaningful content gap exists when your reader needs information that your article does not adequately provide.

For example, an article about:

"How to Use AI for Keyword Research"

might explain keyword generation but fail to explain:

• Search intent
• Keyword clustering
• Search-result validation
• Keyword prioritization
• Human review
• How to remove irrelevant AI-generated keywords

Those may be meaningful gaps.

Ask AI:

Review my article and identify the most important information a reader may still need after reading it.

Divide the recommendations into:

1.     Essential

2.     Useful

3.     Optional

Prioritize recommendations based on reader usefulness, not word count.

This prevents a common SEO mistake:

Adding information simply to make an article longer.

Content-gap analysis should focus on information readers genuinely need—not simply on making an article longer

Step 6: Improve the Title Based on Search Intent

Your title should accurately communicate what the reader will find on the page.

Suppose the query is:

"how to optimize old blog posts"

A title such as:

"The Complete History of Content Optimization"

does not clearly satisfy that intent.

A more direct title would be:

"How to Optimize Old Blog Posts for Better SEO"

The second title makes the expected value clearer.

AI can generate possible titles, but humans should select the final version.

AI Prompt: Title Improvement

Generate 10 title options for this article based on the dominant search intent.

Keep the titles:

·       Clear

·       Specific

·       Natural

·       Accurate

·       Useful to the reader

Avoid:

·       Clickbait

·       Exaggerated claims

·       Keyword stuffing

·       Misleading promises

Explain what reader need each title is designed to address.

Choose the title that best represents the actual content.

 

Step 7: Strengthen the Introduction

A strong introduction should quickly confirm that the reader is in the right place.

Avoid spending several paragraphs explaining a problem before providing any useful information.

A useful structure is:

Problem → Why It Matters → What the Article Covers → Immediate Value

For example, someone searching:

"how to optimize existing content"

probably does not need a long history of SEO.

They want to know:

• What should I change?
• How do I know what needs changing?
• How can AI help?
• What should I avoid?
• How do I measure the result?

Your introduction should establish that quickly.

AI Prompt

Analyze the introduction of this article.

Determine whether it immediately addresses the likely search intent.

Identify:

·       Unnecessary material

·       Missing context

·       Unclear statements

·       Opportunities to provide value sooner

Recommend a stronger structure while preserving a natural human editorial voice.

 

Step 8: Improve Headings and Content Structure

Headings should help readers understand and navigate the article.

They should describe meaningful topics rather than exist simply to insert keywords.

For example:

Weak:

More SEO Tips

Stronger:

How to Identify Search Intent With AI

The second heading tells readers exactly what they will learn.

You can ask AI:

Analyze the structure of this article.

Recommend a clearer H2/H3 hierarchy based on the primary topic and search intent.

Preserve useful sections.
Remove unnecessary repetition.
Combine overlapping sections where appropriate.
Do not create headings merely to insert keywords.

A good structure should help the reader move logically from problem → diagnosis → improvement → verification → measurement.

 

Step 9: Improve Topical Coverage Without Adding Filler

A useful article naturally covers related concepts that help the reader understand the main subject.

For an article about AI content optimization, relevant concepts may include:

• Search intent
• Content freshness
• Content gaps
• Search queries
• User needs
• Internal links
• Content structure
• Keyword relevance
• SERP analysis
• Content quality
• Human review
• Accuracy
• Originality

But this does not mean you should add every related keyword or concept AI suggests.

Ask:

Identify related concepts that would naturally improve this article's completeness.

For each concept, explain why it matters to the reader.

Do not recommend concepts merely because they are semantically related to the keyword.

This keeps the article focused.

 

Step 10: Use AI to Find Potentially Outdated Information

Older articles can contain information that is no longer accurate.

Potentially outdated elements include:

• Software features
• Pricing
• Statistics
• Product names
• Platform policies
• AI model capabilities
• SEO recommendations
• Screenshots
• External links
• Dates
• Technical specifications

AI can help flag information that may require review.

However, AI should not be treated as the final authority for current facts.

Use this workflow:

AI identifies → Human verifies → Human updates

For example:

Content Element	Possible Issue	Action
Statistic	May be outdated	Verify original source
Tool feature	May have changed	Check official website
Example	Still relevant	Keep
Screenshot	Old interface	Replace
External link	May be broken	Check and replace
SEO recommendation	May have changed	Verify authoritative guidance

This is especially important when writing about fast-changing technologies.

 

Step 11: Improve Examples Instead of Simply Adding More Explanation

Examples make instructions easier to understand.

Compare:

Basic explanation:

AI can help identify content gaps.

With:

Practical explanation:

Give AI your existing article, target query, and a list of relevant competing pages. Ask it to compare the major topics covered by each source and identify information your article may not adequately address. Then manually verify those recommendations before adding anything.

The second explanation gives the reader a process they can actually follow.

Whenever possible, replace abstract advice with:

Action → Example → Expected outcome

 

Step 12: Improve Internal Linking

AI can also help identify internal linking opportunities.

Provide AI with your existing article and a list of related articles.

Then ask:

Analyze this article and the following list of existing articles.

Identify the most relevant internal linking opportunities.

For each recommendation, provide:

·       Source section

·       Destination article

·       Suggested anchor concept

·       Why the link helps the reader

Do not recommend links where the relationship is weak or artificial.

Internal links should help readers discover genuinely related information.

They should not be inserted simply to increase the number of links on a page.

For an AI-focused website, related articles about AI tools, SEO, content creation, productivity, research, and writing can naturally support one another when the relationship makes sense.

 

Step 13: Create FAQs Around Genuine Reader Questions

FAQs can be useful when they answer questions readers genuinely have after reading the main article.

Avoid creating a long list of repetitive questions simply because they contain related keywords.

Instead, ask:

Based on the article's primary topic and search intent, identify the most useful questions a reader may still have after reading the article.

Prioritize questions that provide genuinely useful information.

Avoid questions that simply repeat sections already covered.

Then manually review every answer.

The goal is not to create more text.

The goal is to remove remaining uncertainty for the reader.

 

Step 14: Use AI to Find Repetition and Low-Value Sections

Longer content is not automatically better content.

AI can help identify:

• Repeated explanations
• Duplicate examples
• Generic introductions
• Repetitive conclusions
• Unnecessary sections
• Statements that add little value

Try this prompt:

Identify repetitive or low-value sections in this article.

Categorize each recommendation as:

·       Keep

·       Improve

·       Combine

·       Remove

Explain the reason for each recommendation.

Prioritize reader usefulness rather than reducing word count.

This is particularly useful when updating articles that have grown gradually over several revisions.

 

Step 15: Protect the Original Value of Your Article

This is one of the most important principles of AI-assisted content optimization.

Do not replace everything simply because AI can rewrite it.

Existing content may contain:

• Personal experience
• Original examples
• Unique observations
• Case studies
• Original data
• Brand voice
• Editorial opinions
• Practical lessons
• Explanations developed through your own work

A generic AI rewrite can accidentally remove those valuable elements.

Instead, divide the article into three categories.

Keep

Strong original content that is accurate and useful.

Improve

Useful material that needs clarification, updating, restructuring, or stronger evidence.

Replace

Content that is inaccurate, outdated, repetitive, or no longer useful.

This approach is much safer than:

Copy → AI Rewrite → Publish

A better process is:

Analyze → Select → Improve → Verify → Human Edit → Publish

 

A Practical AI Content Optimization Workflow

You can turn the entire process into a repeatable system.

Phase 1 — Select

Choose an existing article with meaningful search potential.

Phase 2 — Diagnose

Review:

• Search intent
• Search Console queries
• Rankings
• CTR
• Content quality
• Reader expectations

Phase 3 — Compare

Review relevant competing pages and identify common reader needs.

Phase 4 — Identify Gaps

Find important unanswered questions and missing information.

Phase 5 — Improve

Review:

• Title
• Introduction
• Headings
• Main sections
• Examples
• Internal links
• FAQs
• Outdated information

Phase 6 — Edit

Remove:

• Repetition
• Generic filler
• Unsupported claims
• Irrelevant sections

Phase 7 — Human Review

Check:

• Accuracy
• Originality
• Brand voice
• Sources
• Examples
• Reader usefulness
• Overall clarity

Phase 8 — Publish

Update the existing page when appropriate rather than creating another page targeting the same intent.

A repeatable content optimization process: select, diagnose, compare, identify gaps, improve, edit, review, publish, and measure

Phase 9 — Measure

Monitor the page after the update and compare its performance over time.

The complete workflow is:

Select → Diagnose → Compare → Identify Gaps → Improve → Verify → Edit → Publish → Measure

 

A Complete Master Prompt for AI Content Optimization

The following prompt can serve as a starting point for your own optimization workflow.

Master AI Content Optimization Prompt

I want to improve an existing article for search intent without turning it into generic AI-generated content.

Target keyword: [KEYWORD]

Target audience: [AUDIENCE]

Article objective: [OBJECTIVE]

Existing article:

[PASTE ARTICLE]

Analyze the article in the following stages:

Stage 1 — Search Intent

Identify the likely dominant and secondary search intent.

Stage 2 — Reader Needs

Explain what the searcher is likely trying to accomplish.

Stage 3 — Content Gaps

Identify important topics, questions, examples, or explanations that are missing.

Stage 4 — Structure

Evaluate the title, introduction, H2s, H3s, section order, and conclusion.

Stage 5 — Content Quality

Identify unclear, repetitive, generic, outdated, or unsupported sections.

Stage 6 — Internal Linking

Suggest relevant internal linking opportunities using the provided list of existing site content.

Stage 7 — Original Value

Identify useful original insights, examples, opinions, or explanations that should be preserved.

Stage 8 — Improvement Plan

Create a prioritized list of recommended changes.

Classify each recommendation as:

·       Essential

·       Recommended

·       Optional

Do not rewrite the entire article yet.

Preserve useful original material.

Do not add information merely to increase word count.

Do not keyword-stuff.

Do not copy competitor wording.

Do not invent statistics, sources, experiences, or facts.

Clearly identify information that requires external verification.

After the analysis, provide a concise editorial brief describing exactly what should be changed.

This turns AI into an editorial assistant rather than an automatic article spinner.

 

Example: Turning a Weak Article Into a Better Resource

Imagine an article titled:

"10 Ways AI Can Help Bloggers"

The article receives impressions for queries such as:

• AI for bloggers
• how to use AI for blogging?
• AI blogging tools
• AI content workflow

The original article might simply list ten tools.

After analyzing search intent, you may discover that readers want more than a tool list.

They may want to understand:

• How AI fits into blogging
• Which tasks can be accelerated
• Which tasks should remain human
• How to research topics
• How to create outlines
• How to optimize existing articles
• How to fact-check AI output
• How to avoid low-quality AI content
• How to maintain originality

The optimization opportunity therefore isn't necessarily:

"Add 2,000 more words."

It may instead be:

"Transform the article from a generic tool list into a practical AI blogging workflow."

That is a much more meaningful improvement.

 

What AI Should Not Do

AI can assist with content optimization, but several responsibilities should remain under human control.

Don't Automatically Rewrite Everything

A complete rewrite can remove your original voice, experience, examples, and insights.

Don't Trust AI for Current Facts Without Verification

AI can produce outdated or incorrect information.

Verify important:

• Statistics
• Prices
• Product features
• Policies
• Technical specifications
• Current recommendations

Don't Add Keywords Everywhere

Keywords should support the topic naturally.

They should not make the article sound unnatural.

Don't Copy Competitors

Competitor analysis should help you understand reader expectations—not reproduce someone else's content.

Don't Optimize Only for Search Engines

The ultimate goal is to help the reader.

Don't Increase Word Count Without a Reason

A 3,000-word article is not automatically better than a 1,500-word article.

Every section should earn its place by providing useful information.

 

The Human-in-the-Loop Model

A strong AI content optimization system can be summarized as:

HUMAN → AI → HUMAN

Human #1: Strategy

The human decides:

• Who the audience is
• What the article should accomplish
• Which topic matters
• Which perspective to provide
• What information should be included

AI: Analysis and Assistance

AI can help with:

• Search-intent analysis
• Content-gap discovery
• Structural analysis
• Repetition detection
• Outline suggestions
• Internal-link ideas
• Editorial diagnostics
• Draft improvement suggestions

Human #2: Editorial Judgment

The human decides:

• What to keep
• What to remove
• What to verify
• What to rewrite
• What original insights to add?
• Which recommendations are actually useful

This keeps AI in its proper role:

A powerful assistant—not an automatic publishing system.

The strongest AI content workflow combines human strategy and editorial judgment with AI-assisted analysis and acceleration

How to Measure Whether the Optimization Worked

Do not judge an update immediately.

Search engines need time to process changes, and organic performance can fluctuate for many reasons.

After publishing an update, monitor metrics such as:

Organic Impressions

Is the page appearing for more relevant searches?

Clicks

Are more people visiting the page from search?

CTR

Did changes to the title or search snippet improve the percentage of searchers who click?

Average Position

Are important queries moving upward?

Query Coverage

Is the page appearing for a broader set of relevant searches?

Engagement

Are visitors actually using the content?

Conversions

If the article has a business objective, monitor outcomes such as:

• Newsletter signups
• Tool clicks
• Affiliate clicks
• Downloads
• Leads
• Other meaningful actions

The goal should not simply be:

"Rank higher."

A better goal is:

"Attract the right searchers and provide them with a genuinely useful page."

 

Common AI Content Optimization Mistakes

1. Rewriting Without Diagnosing

Understand the problem before changing the article.

2. Optimizing for a Keyword Instead of an Intent

A keyword describes a query.

Search intent describes the goal behind that query.

3. Copying the Structure of the Top Result

Search results should be analyzed—not duplicated.

4. Adding Unnecessary Sections

Every section should have a clear purpose.

5. Trusting AI Facts Automatically

AI output still requires verification.

6. Removing Human Experience

Your own knowledge and experience may be among the most valuable elements of the article.

7. Chasing Word Count

Useful information matters more than arbitrary length.

8. Changing the URL Without a Good Reason

An existing page may already have search visibility, links, and historical signals.

9. Ignoring Search Console Data

Actual search queries can reveal how people are discovering your page.

10. Publishing Immediately After AI Editing

Always perform a human editorial and factual review before publication.

 

A Simple Content Optimization Checklist

Before republishing an optimized article, ask:

• Does the article clearly satisfy the primary search intent?
• Does the introduction address the reader's need quickly?
• Is the title accurate?
• Are the headings logical?
• Are important subtopics covered?
• Are the examples practical?
• Has outdated information been verified?
• Are important claims supported?
• Have repetitive sections been removed?
• Are internal links genuinely relevant?
• Are FAQs useful rather than repetitive?
• Has the original human perspective been preserved?
• Is the article easy to scan?
• Does each major section provide value?
• Have AI-generated recommendations been reviewed?
• Has the final article been checked for accuracy?
• Is the content more useful than it was before?

If the answer is yes, you're not simply updating an old post.

You're creating a better resource for the people who need it.

 

Final Takeaway

AI can make existing-content optimization faster and more systematic, but the biggest opportunity isn't asking AI to rewrite old articles.

It is using AI to better understand what readers actually need.

A strong workflow looks like this:

Find → Diagnose → Analyze → Identify Gaps → Improve → Verify → Human Edit → Publish → Measure

If you're building a broader AI-powered content system, see our guide on How to Build an AI Workflow.

Use AI to help analyze search intent, uncover missing information, improve structure, detect repetition, suggest internal links, and identify areas that deserve further investigation.

Then use your own judgment to decide what belongs in the final article.

The most useful question is not:

"How can I make this article more SEO-friendly?"

It is:

"How can I make this article more useful for the person who searched for it?"

When search intent, accurate information, useful examples, clear structure, original value, and human editorial judgment work together, AI becomes much more than a writing tool.

It becomes a practical content optimization assistant.

 

Frequently Asked Questions

Can AI optimize an existing article for SEO?

Yes. AI can assist with search-intent analysis, content-gap identification, structural review, repetition detection, heading suggestions, internal-link recommendations, and editorial planning. Human review remains essential.

Should I completely rewrite an old article with AI?

Usually, there is no need to rewrite everything. Preserve useful original insights, examples, experience, and accurate information. Improve only the sections that genuinely need improvement.

How does AI help with search intent?

AI can analyze a target query and existing content to help identify the likely purpose behind the search and determine whether the article adequately addresses that purpose.

Can AI identify content gaps?

Yes. AI can compare your article against relevant topics, questions, and information from sources you provide. Its recommendations should then be evaluated and verified by a human.

Does longer content rank better?

Not automatically. An article should contain enough useful information to satisfy the reader without adding unnecessary material.

How often should existing content be updated?

There is no universal schedule. Review important content when information becomes outdated, performance changes, search intent shifts, or substantially better information becomes available.

Should I use AI to rewrite my title and headings?

AI can provide options, but the final decision should be based on accuracy, clarity, search intent, and whether the title and headings accurately represent the content.

What is the best AI workflow for content optimization?

A practical workflow is:

Human strategy → AI analysis → Human editing → Verification → Publication → Performance measurement

This keeps AI useful while maintaining human control over the final result.

 

Conclusion

Existing content is an often-overlooked SEO asset.

Before creating another article targeting a similar topic, examine what you already have.

AI can help you understand why a page may be underperforming, what readers are likely expecting, where important information may be missing, and which improvements deserve further investigation.

But optimization should not mean changing everything.

The better approach is selective:

Keep what works. Improve what is weak. Remove what is unnecessary. Verify what is outdated. Add what readers genuinely need.

Use AI for analysis and acceleration, but keep humans responsible for strategy, accuracy, originality, and final editorial decisions.

That is how AI can help transform existing content into a stronger, clearer, and more useful resource for both readers and search.