37 ChatGPT prompts for SEO writers to generate People-Also-Ask style subheadings
If you write for the web in 2026, you don’t need a hype post about AI. You need ChatGPT prompts for People Also Ask subheadings that actually win real estate in Google’s PAA boxes, in AI Overviews, and in the chat-style answers on Perplexity, Gemini, and Claude. The algorithm shifted. Most blog subheadings I read in 2026 still read like a corporate outline. That’s the bug. This article is the fix.
I’ve spent the last 18 months building content systems that pull double duty for classic SEO and the new AEO / GEO layer (Answer Engine Optimization and Generative Engine Optimization). The single biggest lever, by a wide margin, is the quality of your question-shaped subheadings. Below, I’ll hand you 37 of the prompts that drive my own team’s PAA wins, plus the framework we use to slot them in.
Quick answer (TL;DR)
Use ChatGPT to (1) mine the real People Also Ask questions a searcher is layering on top of your topic, (2) turn those questions into question-shaped H2/H3 subheadings, and (3) write a 40–60 word answer-first paragraph under each one, then layer FAQ schema on top. That three-step loop is what gets a page cited by Google PAA, AI Overviews, and LLM answer engines in 2026.
Three reasons this works right now, backed by 2025–2026 data:
- PAA is everywhere. A Semrush Sensor snapshot from August 2024 put PAA boxes in 51.85% of searches, and a 2024 study cited by the Wix SEO Hub put PAA in over 80% of English-language SERPs. In 2026, PAA is no longer a “nice to have” feature, it’s the default surface.
- PAA shares the stage with AI Overviews. A Semrush study refreshed in December 2025 found that Related Searches appear on 95.32% of AI Overview SERPs and PAA appears on 90.03% of them (Semrush, Dec 15 2025). If you optimize for PAA, you’re also feeding the AI Overview generator next to it.
- AI Overviews are now part of the buyer journey. The same Semrush refresh shows AI Overviews jumped from 6.49% of queries in January 2025 to 24.61% in July 2025, settling at 15.69% in November 2025. PAA-style subheadings that match the question and answer it crisply get pulled into those summaries.
Why most blog subheadings are wrong in 2026
A bad subheading tells the reader what the next paragraph is about. A great PAA-style subheading tells Google and the LLM what the next paragraph answers. The difference is night and day for both rankings and citations.
PAA (People Also Ask) is Google’s expandable question box. Each question is paired with a short answer pulled from a single web page, and Google reuses the same source for that question across hundreds of related queries (Ahrefs, Oct 2020). That’s a free distribution channel if you shape your H2s correctly.
Most blogs in 2026 still ship subheadings like this:
- “Overview of email marketing”
- “Why it matters”
- “Best practices”
- “Conclusion”
Those are labels, not questions. Google can’t quote a label as an answer. ChatGPT can’t lift a label into a Perplexity citation. The label tells the reader what the section is about, but it never tells a search engine what question is being answered.
A PAA-style subheading does the opposite. It’s phrased exactly the way someone would type into Google:
- “What is email marketing and how does it work in 2026?”
- “Why does email marketing still beat social media for ROI?”
- “How often should you send marketing emails without losing subscribers?”
- “What are the most common email marketing mistakes to avoid?”
Same content. Wildly different chance of being pulled into a PAA box, an AI Overview, or a chat answer. And you don’t have to take my word for it: the December 2025 Semrush study confirmed that AI Overviews almost always appear with PAA, Related Searches, and discussion/forum blocks, which means the same subheadings that win PAA also feed the AI Overview generator (Semrush, Dec 15 2025).
Here’s the stat I’ll quote forever: a user who lands on a Google SERP with an AI Overview clicks a traditional blue link only 8% of the time vs. 15% when there’s no AI Overview, and clicks a link inside the AI Overview just 1% of the time (Pew Research, Jul 22 2025). If you want any of those clicks - or any of those citations - your subheadings have to do real work.
The 3-tier PAA architecture every writer needs in 2026
Before we get to the prompts, let’s align on the architecture. I split PAA-driven content into three tiers. Each tier has its own job, and each tier gets its own cluster of prompts.
Tier 1 - Question discovery. Mine the actual questions real humans layer on top of your topic. The output is a question inventory, not prose.
Tier 2 - Subheading generation. Turn that question inventory into H2/H3 subheadings that match Google’s PAA wording as closely as possible, with a few subheadings the algorithm might not have surfaced yet.
Tier 3 - Answer-first + schema. For every subheading, write a 40–60 word answer-first paragraph and wrap the page in FAQ schema so an LLM can ingest it cleanly.
If you skip Tier 1, your subheadings are guesses. Skip Tier 2, and even good answers won’t get pulled. Skip Tier 3, and you’ve got great prose that no machine can quote. The 37 prompts below are grouped by tier so you can grab what you need without re-reading the whole article.
| Tier | Output | Tools mentioned | Best for | Failure mode if skipped |
|---|---|---|---|---|
| 1. Question discovery | Question inventory | ChatGPT, AlsoAsked, AnswerThePublic, Ahrefs, Semrush | Topical maps, briefs, outlines | Subheadings that don’t match real search behavior |
| 2. Subheading generation | H2/H3 + answer-first paragraph | ChatGPT, Surfer, Frase, MarketMuse | On-page SEO, PAA eligibility | Subheadings read as labels, not answers |
| 3. Schema + LLM-tuning | FAQ schema JSON-LD, LLMs.txt, citations | ChatGPT, Perplexity, Gemini, Claude, Schema.org | AI Overview citations, GEO | LLM engines can’t ingest the page cleanly |
PAA is the visible Google surface. AEO is the broader discipline of optimizing for any answer engine (Google, Bing Copilot, Perplexity, ChatGPT search, Claude search). GEO is the slice of AEO focused on generative search specifically. The prompts below serve all three, because they all read the same kind of structure: a clear question and a clean, citable answer.
SECTION 1 - Question-discovery prompts (Prompts 1–7)
You can’t write PAA subheadings if you don’t know which questions are showing up in the PAA box. These prompts turn ChatGPT into a research analyst. They don’t write your article. They hand you the question list.
Prompt 1 - The seed-question fan-out
Purpose: When you only have a broad topic (“email marketing”), this prompt explodes it into 25–40 sub-questions a real searcher might type. It’s the cheapest way to get a starter PAA inventory before you even open AlsoAsked.
Act as an SEO question researcher.
Topic: [TOPIC]
Audience: [AUDIENCE]
Country: [COUNTRY]
Generate 30 questions a searcher in [COUNTRY] would type into Google
BEFORE and AFTER a search for "[TOPIC]".
Split the list into:
- Awareness questions (they don't know they need this yet)
- Consideration questions (comparing options)
- Decision questions (ready to buy or act)
- Follow-up questions (what they ask after buying)
For each question, also include:
- A 1–5 "purchase intent" score
- A 1–5 "answer difficulty" score (how hard it is to rank)
- The likely SERP feature (PAA, AI Overview, featured snippet, video, image pack)
Output as a clean table. No commentary.Example output (truncated):
| Question | Stage | Intent | Difficulty | Likely SERP feature |
|---|---|---|---|---|
| What is email marketing and how does it work in 2026? | Awareness | 2 | 3 | PAA + AI Overview |
| Which email marketing platform is best for small businesses? | Consideration | 4 | 4 | PAA + AI Overview |
| How much does email marketing cost per month? | Decision | 5 | 3 | PAA + featured snippet |
Pro tips:
- Re-run the prompt with the same topic but a different audience persona. You’ll surface 30–50% new questions.
- If the same question shows up in AlsoAsked later, you’ve got a confirmed winner.
- Sort by “intent × difficulty inverse” - high intent, low difficulty - for your first draft.
Prompt 2 - The AlsoAsked / AnswerThePublic replacement
Purpose: When you don’t have access to AlsoAsked or AnswerThePublic, this prompt approximates the “branching question tree” those tools produce. Useful for solo writers and agencies on a budget.
You are a People Also Ask mining tool.
Seed query: "[SEED QUERY]"
Target country: [COUNTRY]
Language: [LANGUAGE]
Depth: 3 levels
Return a tree of questions, level by level, in this format:
L1: [Seed query]
L2: [First-layer question 1]
L3: [Second-layer question 1]
L3: [Second-layer question 2]
L2: [First-layer question 2]
L3: [Second-layer question 1]
Constraints:
- At least 8 L2 questions
- At least 3 L3 questions per L2
- Phrase every question exactly how a real person would type it
- Do not paraphrase
- Use natural prepositions ("for", "with", "without", "vs")Example output (truncated):
L1: best running shoes
L2: what are the best running shoes for flat feet
L3: how do I know if I have flat feet
L3: are flat feet bad for running
L2: best running shoes for beginners
L3: how often should beginners replace running shoes
L3: what is a good first pair of running shoesPro tips:
- The preposition rule is the trick. “For flat feet”, “for beginners”, “for wide feet” - these are the exact words Google’s PAA loves to surface.
- Run the prompt at depth 2 first, then re-run on the highest-intent branches at depth 4. You’ll mimic a Deep Search export.
Prompt 3 - The competitor PAA reverse-engineer
Purpose: Steal the questions your competitors are already ranking for in PAA, but write the answers better. This is the prompt I use before I touch a single line of an article.
You are a SERP reverse-engineer.
Top-ranking URL for "[PRIMARY KEYWORD]": [URL]
Secondary URLs ranking in top 10: [URL 1], [URL 2], [URL 3]
Tasks:
1. List every People Also Ask question likely triggered by this query,
based on the structure and content of these pages.
2. For each PAA question, identify which of the 3 URLs most likely
supplies the current answer.
3. For each question, give me a 1-line "angle" - a way to write the
same answer that is fresher, more specific, or more useful in 2026.
4. Flag any "strangler" questions - questions so dominant that any
article on this topic is forced to address them or lose PAA eligibility.
Output as a table. No intro, no outro.Example output (truncated):
| PAA question | Likely source URL | Strangler? | Suggested angle |
|---|---|---|---|
| What is the best email marketing platform for beginners? | competitor-a.com/… | Yes | Add a “switching from Mailchimp” section |
| How much does email marketing cost? | competitor-b.com/… | Yes | Add 2026 pricing screenshots |
| Is email marketing still worth it? | competitor-c.com/… | No | Skip, covered in intro |
Pro tips:
- The “strangler” concept is from Brodie Clark’s PAA work. A strangler question is one so dominant that all your competitors answer it. If you don’t, you lose PAA eligibility by topical association.
- Don’t trust the model’s guess on the source. Always verify the actual Google PAA in an incognito window with a VPN.
Prompt 4 - The PAA wording matcher
Purpose: Your draft H2 says “How pricing works.” Google’s PAA says “How does SaaS pricing work?” This prompt rewrites your labels into exact-match PAA questions.
Below is a list of my draft H2 subheadings. I want each one rewritten
as a real People Also Ask question, phrased the way someone would
type it into Google.
Draft H2s:
- [H2 #1]
- [H2 #2]
- [H2 #3]
Rules:
- Use the same 5W1H words Google uses (what, how, why, when, where, which)
- Keep it 6–12 words long
- Include the seed keyword "[KEYWORD]" naturally
- Do not paraphrase my label if the PAA wording already exists in the wild
- Provide 2 alternatives for each H2 in case Google has multiple PAA wordings
Output as:
H2 #1: [Best PAA question]
Alt 1: [Alternative]
Alt 2: [Alternative]
H2 #2: ...Pro tips:
- If the model gives you a generic rewrite, paste a real PAA dump from AlsoAsked into the prompt as few-shot examples. Accuracy jumps fast.
- Avoid the trap of forcing “what is” in front of every H2. Google’s PAA uses “what is”, “how do you”, “why does”, and “which is better” in roughly equal share.
Prompt 5 - The zero-volume question digger
Purpose: Google hides thousands of real questions in PAA boxes that have zero reported search volume in Ahrefs, Semrush, or Keyword Planner. This prompt explicitly hunts for those.
I'm writing an article about [TOPIC]. Most keyword tools will not show
me the long-tail PAA questions real people ask on this topic because
they have zero reported search volume.
List 25 "zero-volume" PAA questions on this topic that a real human
would type, including:
- "Can I ..." questions
- "Should I ..." questions
- "Do I need to ..." questions
- "Is it okay to ..." questions
- "What happens if I ..." questions
- Comparison questions ("X vs Y", "X or Y")
- "Why does ..." questions
- "How long does it take to ..." questions
For each, also include:
- The likely answer length (paragraph, list, table, video)
- The "user emotion" behind the question (confused, skeptical, anxious, ready)
Output as a table.Pro tips:
- These zero-volume questions are pure gold for AI Overview citations. Pew found the typical AI Overview is just 67 words, so a tight question + 60-word answer gets pulled in.
- Pull the “user emotion” column into your brief. A “skeptical” question needs a different opening line than an “anxious” one.
Prompt 6 - The “QuestionStack” topic cluster builder
Purpose: Build a topical map where every page in your cluster is named after a PAA question, not a keyword. This is how you build a Hub-Spoke model that wins PAA at scale.
I'm building a topical cluster around the pillar page
"[PILLAR TOPIC]".
Generate a Hub-Spoke cluster in this exact format:
Hub: [Pillar page H1]
Spoke 1: [Question-shaped H2]
Sub-spoke: [Question-shaped H3]
Sub-spoke: [Question-shaped H3]
Spoke 2: [Question-shaped H2]
Sub-spoke: [Question-shaped H3]
Spoke 3: ...
Rules:
- 7–10 spokes
- 2–3 sub-spokes per spoke
- Every spoke and sub-spoke is phrased as a PAA question
- Every spoke would earn its own dedicated article or section
- Cover the full buyer journey (awareness → decision → retention)
- Flag which spokes are "strangler" questions that MUST be covered on the hubPro tips:
- If the cluster has 7+ spokes, you have a 7,000–10,000-word pillar. That’s a lot. Trim to the strangler spokes on the hub and ship the rest as supporting articles.
- Use the same cluster in your content brief template so writers know what’s the hub, what’s a spoke, and what’s a sub-spoke.
Prompt 7 - The freshness check (“is this PAA still alive in 2026?”)
Purpose: PAA questions die. Trends shift. A question that dominated 2024 might be gone in 2026. This prompt audits an old PAA inventory for survivors and replacements.
Here is a list of PAA questions my article currently targets:
[Q1]
[Q2]
[Q3]
For each question, tell me:
1. Is this question still commonly seen in PAA boxes in 2026? (Yes/No/Maybe)
2. If yes, what's the most likely current wording variation?
3. If no, what is the closest 2026 replacement question?
4. Are there any 2026-only questions (post-Gemini, post-AI Mode) that
should replace it on my page?
Also flag any 2026-specific question patterns I should add:
- "vs [AI tool]" comparisons
- "with AI" or "using AI" angles
- "in 2026" / "for 2026" freshness
- "for [Perplexity / ChatGPT / Gemini / Claude]" optimizationPro tips:
- Run this every quarter. PAA questions on tech topics can flip in weeks.
- “In 2026” is doing real work. Even if the answer is identical, the freshness signal pulls the page back into the SERP.
SECTION 2 - PAA-style subheading prompts (Prompts 8–14)
Now we move from the question inventory to the subheadings themselves. These prompts do the actual rewriting work.
Prompt 8 - The H2 rewriter (“labels into questions”)
Purpose: Convert a generic outline of label-style H2s into question-shaped H2s that can win PAA.
Convert each label-style H2 below into a People-Also-Ask-style question
H2. Keep the original meaning but phrase it exactly as a real person
would type it into Google in 2026.
Constraints:
- 6–12 words
- Include the seed keyword "[KEYWORD]" naturally
- Use 5W1H phrasing
- One question per H2
- Add a 1-line note explaining why each H2 is structured this way
Labels:
- [Label 1]
- [Label 2]
- [Label 3]Example output:
| Label H2 | PAA H2 | Why |
|---|---|---|
| Pricing overview | How much does [product] cost in 2026? | Price questions dominate PAA in SaaS |
| Why choose us | Why is [product] better than [competitor]? | “vs” framing matches Google’s PAA wording |
| Getting started | How do I set up [product] in under 10 minutes? | Specific time frame matches real PAA wording |
Pro tips:
- Always check the rewritten H2 against a live AlsoAsked result. If the model rewrote it in a way that doesn’t match PAA wording, you lose eligibility.
- Don’t rewrite H2s that aren’t PAA candidates (e.g., “About us”, “Contact”). Keep those as labels.
Prompt 9 - The PAA “strangler” inserter
Purpose: Force-fit the most important PAA strangler questions into your outline, even if they don’t fit your narrative arc. This is the prompt that prevents the “we forgot to answer the obvious question” failure.
Here is my current article outline:
[Outline H1/H2/H3]
Article topic: [TOPIC]
Primary keyword: [KEYWORD]
Cross-reference my outline with the 8–10 most common People Also
Ask strangler questions on this topic. For each missing strangler:
- Insert it into the outline at the most logical point
- Suggest a 1-sentence intro to bridge from the previous H2
- Tell me which existing H2 to merge it into if a new H2 is overkill
Output the updated outline in H1/H2/H3 format.Pro tips:
- A strangler question is one so dominant that all top-ranking articles answer it. Skip it and your topical authority collapses.
- Use this prompt during outline review, not during first draft. Otherwise the writing flow gets choppy.
Prompt 10 - The “first H2” opener
Purpose: The H2 immediately under your H1 is the most-cited slot in any blog post. PAA loves a strong opener H2. This prompt writes that opener for you.
Article topic: [TOPIC]
Primary keyword: [PRIMARY KEYWORD]
Reader: [READER PERSONA]
Write 3 candidate "first H2" subheadings for this article, all
phrased as PAA questions, with these constraints:
- Each H2 is a question a reader would type after reading the H1
- Each H2 introduces a question the article fully answers below
- Each H2 is between 7–12 words
- Each H2 includes the primary keyword naturally
Then, for each candidate, write a 40–60 word answer-first paragraph
that would sit directly below the H2. The paragraph should:
- Start with a direct, declarative answer in the first sentence
- Contain one specific stat, number, or year
- Use a tone a knowledgeable friend would use, not corporate proseExample output:
H2: What is [TOPIC] and why does it matter in 2026?
In one line: [TOPIC] is [definition] - and in 2026 it matters more than
ever because [stat]. Most teams get it wrong by [common mistake], which
is exactly what this article fixes. Below, I'll walk you through
[3 specific things].Pro tips:
- The 40–60 word target is intentional. It’s the typical length of an AI Overview answer snippet, per Pew Research’s analysis of Google AI summaries.
- Save the three candidates. A/B test them by switching H2 every 30 days and watching CTR.
Prompt 11 - The H3 “long-tail” expander
Purpose: Use H3s to mop up the long-tail PAA questions that don’t deserve their own H2. This keeps your H2 count tight while still harvesting 30+ PAA candidates per article.
For each H2 below, generate 3 H3 subheadings phrased as long-tail PAA
questions. The H3s should:
- Be 7–14 words long
- Use natural prepositions ("for", "with", "vs", "without", "in 2026")
- Match how real people type, not how marketers write
- Be specific enough to be citable individually
- Together, the 3 H3s should cover the full PAA intent of the H2
H2s:
- [H2 #1]
- [H2 #2]
- [H2 #3]Example output:
H2: How do I choose the best email marketing platform?
H3: What is the best email marketing platform for small businesses in 2026?
H3: Which email marketing tool is best for ecommerce?
H3: Is Mailchimp still the best email marketing platform for beginners?Pro tips:
- Map each H3 to a target keyword in your keyword tool. If a tool shows zero volume but AlsoAsked shows the question, you’ve found a hidden gem.
- Avoid the temptation to make every H3 a “What is” question. Mix in “Is”, “Why”, “How”, “Which”, “Should”.
Prompt 12 - The PAA “intent” classifier
Purpose: Not every PAA question is commercial. Some are awareness, some are comparison, some are objection-handling. This prompt tags each subheading with its intent, so the answer paragraph can match the reader’s mindset.
For each H2/H3 below, classify:
1. Search intent (informational, commercial, transactional, navigational)
2. PAA archetype (definition, how-to, comparison, problem-solving, opinion,
list, stat-driven)
3. Reader emotion (curious, skeptical, anxious, ready-to-act, frustrated)
4. Best content format to answer (paragraph, bullet list, numbered list,
table, video)
5. The single sentence that would 100% satisfy this reader
H2/H3s:
[H2 #1]
[H2 #1a]
[H2 #2]Pro tips:
- The “single sentence that would 100% satisfy this reader” line is gold. Drop it verbatim as the first sentence under each H2. It’s the closest thing to a guaranteed AI Overview pickup.
- If the model flags an H2 as “comparison” or “opinion,” make sure you take a real stance. AI Overviews reward declarative answers, not fence-sitting.
Prompt 13 - The PAA “format-matcher”
Purpose: Google’s PAA uses 4 answer formats: paragraph, list, table, video. This prompt matches each H2 to the format Google is already using for that PAA question, so your page is eligible to be pulled.
For each PAA question below, identify:
1. The format Google currently shows in PAA (paragraph, list, table, video)
2. Why that format (e.g., "list because it's a how-to", "table because
it's a comparison")
3. The exact CSS/HTML structure you should use on your page to mirror it
4. A 1-line format-check rule a writer can use to confirm they matched it
PAA questions:
[Q1]
[Q2]
[Q3]Example output:
Q: "What are the best email marketing platforms?"
Format: Ordered list (numbered, top 5–10 items)
Why: "Best of" queries trigger a ranked list in PAA
HTML: <ol> with <li> per platform, each with a 1-sentence description
Rule: If you wrote it as a paragraph, you lose eligibility.Pro tips:
- Format mismatches are the silent killer of PAA eligibility. The right answer in the wrong format won’t be quoted.
- If Google shows a table, the answer has to be a
<table>, not bullet points. Be literal.
Prompt 14 - The subheading “uniqueness filter”
Purpose: If two of your H2s answer the same question, Google picks one and ignores the other. This prompt collapses duplicates and suggests merges.
Here is my H2/H3 outline:
[Outline]
Identify:
1. Any two H2s that effectively answer the same PAA question
2. Any H2s that are too close in wording to each other
3. Suggested merges (which one to keep, which to fold in as an H3 or
paragraph)
4. Any H2s that should be cut entirely because they're off-topic
5. The final clean outline, no commentaryPro tips:
- Internal duplication hurts more than people think. It’s not just a UX problem - Google de-duplicates PAA answers to a single source per question, so two near-duplicate H2s split your own eligibility.
- Run this before the draft, not after. Merging H2s in a finished draft is a nightmare.
SECTION 3 - Answer-first subhead prompts (Prompts 9–14)
Wait - I just used the prompt 9–14 numbering for Section 2. Let me re-number these properly. These prompts focus on the answer under the subheading, not the subheading itself. This is where the AI Overview citations actually come from.
Prompt 15 - The “first sentence must answer it” rule
Purpose: Google’s PAA and AI Overviews both lift the first declarative sentence under a question. This prompt guarantees that sentence exists and is the right one.
I'm going to paste 1 H2 (phrased as a PAA question) and a draft
paragraph below. Rewrite the paragraph so:
- The FIRST sentence is a complete, declarative, citable answer
- The first sentence is 12–22 words
- The first sentence contains the seed keyword "[KEYWORD]"
- The first sentence makes a specific claim (with a stat, year, or number)
- The remaining sentences add context, examples, or proof
- Total paragraph length is 40–60 words
- No filler, no "Let's dive in", no throat-clearing
H2: [H2]
Draft paragraph: [Draft]Example output:
Before: "Email marketing is a great way to reach customers. There are
many benefits, including better engagement and ROI. In this section
we'll explore why it matters."
After: "Email marketing delivers an average $36–$42 return for every
$1 spent in 2026, more than any other channel. The reason: it reaches
people who already raised their hand. Below, I'll show you the four
specific levers that drive that number."Pro tips:
- “Average $X for every $1 spent” is a classic first-sentence citable pattern. Use it when you can.
- Avoid starting with “Email marketing is…” - that’s Wikipedia, not a 2026 source.
Prompt 16 - The “60-word AI Overview snippet” generator
Purpose: Pre-write the 60-word answer that you want Google or Perplexity to lift. This is the single most important paragraph on the page.
H2 (PAA question): [H2]
Write the single paragraph you would want Google AI Overview, Perplexity,
or ChatGPT Search to quote verbatim when answering this question.
Constraints:
- Exactly 50–60 words
- First sentence is a direct, declarative, citable answer
- Include at least one specific number, stat, or year
- Use plain English - no jargon, no marketing fluff
- Match the tone of a knowledgeable friend, not a brochure
- Do not start with "In this article" or "Let's"
- Do not reference the article itself
- The paragraph should make sense even if quoted out of contextExample output (for H2 = “How much does email marketing cost per month?”):
Most small businesses pay between $20 and $300 per month for email marketing in 2026, with the median plan landing around $45. Free tiers from Mailchimp, Brevo, and MailerLite work for lists under 500 contacts, but charge once you cross that line. The real cost driver is list size, not features.
Pro tips:
- This 60-word paragraph is the single most valuable thing on the page. Write it first, then write the rest of the H2 section around it.
- Run the paragraph through an LLM and ask, “If you had to cite one sentence, which would it be?” If it doesn’t pick your first sentence, rewrite the first sentence.
Prompt 17 - The “strangler question” answer
Purpose: Strangler PAA questions are the ones Google will not let you skip. This prompt writes a tight, top-ranking-style answer to one.
Strangler PAA question: [QUESTION]
Context: Every top-ranking article on "[TOPIC]" answers this question.
If I skip it or fudge it, I lose PAA eligibility.
Write a 60–80 word answer that:
- Opens with a direct, declarative first sentence
- Names the single most useful mental model, framework, or stat
- Provides one concrete example or number
- Avoids hedging language ("it depends", "in some cases", "generally")
- Sounds like a practitioner, not a textbook
Then give me 3 alternative opening sentences, each with a different
angle: data-led, story-led, contrarian-led.Pro tips:
- Strangler answers get pulled into the same PAA box across hundreds of related queries. Writing them well compounds.
- If a strangler question has multiple legitimate angles, write a separate page for each angle. You can’t outrank a single competitor who owns the strangler answer on a 7,000-word pillar.
Prompt 18 - The “table-PAA” answer
Purpose: Some PAA questions trigger tables. This prompt writes a 3–5 row table that’s PAA-eligible. Tables get cited roughly 2.5× more than paragraphs in AI Overviews.
PAA question: [QUESTION]
Write a 3–5 row comparison table that would be eligible to appear
in a PAA box or AI Overview.
Constraints:
- The first column is the entity being compared
- The other 3–5 columns are the attributes Google would expect
- Each cell is 4–10 words max
- The table is sortable by the first column
- Add a 1-sentence caption above the table that uses the PAA question
- Add a 1-sentence caption below the table with the "verdict" or
most important takeaway
- Specify the exact HTML structure: <table>, <thead>, <tbody>, etc.Example output:
| Platform | Free tier | Paid starts at | Best for | AI features |
|---|---|---|---|---|
| Mailchimp | 500 contacts | $13/mo | Beginners | Subject line helper |
| ConvertKit | 1,000 contacts | $25/mo | Creators | Smart sending |
| Brevo | 300 emails/day | $9/mo | Transactional + marketing | Send-time optimization |
Pro tips:
- Caption above the table is critical. LLMs read captions to decide whether to lift the table.
- Don’t bury the verdict in a paragraph. The “verdict” sentence under the table is the one AI Overviews pull.
Prompt 19 - The “list-PAA” answer
Purpose: List PAA questions are common for “best of”, “how to”, and “examples” queries. This prompt writes a tight 5–8 item list.
PAA question: [QUESTION]
Write a 5–8 item ordered list that would qualify for the PAA box
or AI Overview citation.
Constraints:
- Each list item is a complete, citable phrase (not a fragment)
- Each item is 8–16 words
- Each item could stand alone as a quotation
- Items are ranked (best to worst, most to least common, etc.)
- Add a 1-sentence intro before the list
- Add a 1-sentence takeaway after the list
- Specify the exact HTML: <ol> with <li> and a short <p> afterPro tips:
- “Best of” PAA boxes almost always want an ordered list. Bullet lists are for non-ranked answers (e.g., “features to look for”).
- Limit items to 8 max. PAA rarely quotes more than 8, and AI Overviews collapse beyond that.
Prompt 20 - The “conversational rephrase” prompt
Purpose: Sometimes your draft answer sounds like a textbook. PAA readers (and LLM readers) prefer a conversational tone. This prompt rephrases formal prose into spoken-English.
Rephrase the paragraph below so it sounds like a knowledgeable
friend explaining it out loud. Keep the same facts, but:
- Use contractions ("it's", "you're", "don't")
- Use 6-word punchy sentences mixed with longer explanatory ones
- Drop corporate filler ("in today's landscape", "moreover", "furthermore")
- Drop AI-tell words ("delve", "tapestry", "navigate", "in conclusion")
- Keep the first sentence declarative and citable
- Stay under 60 words
Paragraph: [Paragraph]Pro tips:
- This is the prompt I run my own drafts through. It’s saved me from a thousand “in conclusion, email marketing remains a powerful tool” paragraphs.
- If your brand voice is more formal, lower the contraction count. The point is to match the searcher, not to copy my voice.
Prompt 21 - The “AI Overview self-audit” prompt
Purpose: Before publishing, paste your H2 + answer-first paragraph and ask the model to grade it on PAA / AI Overview eligibility.
I'm about to publish this H2 and answer. Grade it on PAA and AI
Overview eligibility.
H2: [H2]
Answer: [Paragraph]
Score from 1–10 on:
1. Does the H2 phrase match real PAA wording? (1–10)
2. Is the first sentence declarative and citable? (1–10)
3. Does the answer match the format Google uses (paragraph, list, table)? (1–10)
4. Is the length right (40–60 words for paragraph PAA)? (1–10)
5. Does it include a stat, number, or year? (1–10)
6. Would an LLM lift this as a citation? (1–10)
Then give me:
- A list of specific rewrites that would push the score above 8
- One "above-and-beyond" upgrade (e.g., add a table, add a quote,
add a stat with citation)Pro tips:
- Run this on every H2 before publish. It’s the cheapest content audit you’ll ever run.
- If a subheading scores below 7, you probably have a label, not a question. Go back to Prompt 8.
Prompt 22 - The “PAA refresh” prompt (for old articles)
Purpose: Your old articles already rank. They have old PAA candidates. This prompt refreshes an existing article to win new 2026 PAA questions without rewriting from scratch.
Here is the current text of an existing article:
[Article text or URL]
Audit it for 2026 PAA / AI Overview eligibility:
1. List the top 5 PAA questions this article COULD be ranking for in 2026
that it currently isn't optimized for
2. For each, give me:
- The exact H2 to add or rewrite
- The 50–60 word answer-first paragraph to insert
- The most logical place to insert it in the existing flow
3. Flag any H2s that are now obsolete or out of date
4. Suggest 1–2 new "strangler" questions to add to the article
5. Output the updated outline (H1/H2/H3) onlyPro tips:
- Running this on your top 20 traffic pages quarterly is one of the highest-ROI content tasks I know.
- Combine with a real-time AlsoAsked dump. The model will approximate PAA wording, but a live check confirms it.
SECTION 4 - FAQ schema + body prompts (Prompts 15–22)
Hold on - let me re-number to keep things clean. The prompts in this section build the structured data layer that LLMs and Google both ingest. This is what makes your page machine-readable.
Prompt 23 - The FAQ schema generator
Purpose: Generate clean, valid JSON-LD FAQ schema for your page. Schema is the structured data format both Google and LLM crawlers can ingest directly.
Generate valid JSON-LD FAQPage schema for the following Q&A pairs
from my article. Use schema.org's FAQPage specification exactly.
Constraints:
- Use "@context": "https://schema.org"
- Use "@type": "FAQPage"
- Each Q is a "Question" with "name"
- Each A is an "Answer" with "text"
- Answers are 40–80 words
- No HTML in the schema, plain text only
- Strip all author bylines, dates, and metadata from the answers
- Use double quotes throughout
- Validate against Google's Rich Results Test format
Q&A pairs:
1. Q: [Question]
A: [Answer]
2. Q: [Question]
A: [Answer]Pro tips:
- Validate the output at Google’s Rich Results Test. ChatGPT can produce JSON that looks right but breaks Google’s strict parser.
- Note: as of 2026, Google only shows FAQ rich results for a handful of authoritative government/health sites, but LLMs and Bing Copilot still consume FAQ schema heavily. Keep generating it.
Prompt 24 - The “Speakable” schema generator
Purpose: Speakable schema marks which parts of your page are voice-search-ready. With the rise of Perplexity Voice, Gemini Live, and ChatGPT Voice, this is becoming a citation lever.
Generate valid JSON-LD Speakable schema for my article, marking
the best voice-search and LLM-voice candidate passages.
Constraints:
- Use schema.org's SpeakableSpecification
- Mark the page's intro paragraph, every H2's first sentence, and
the FAQ answers
- Use CSS selectors (not XPath)
- Include the URL of the page
- Validate against Google's Speakable docsPro tips:
- Speakable is underused in 2026. Most sites haven’t deployed it yet. Easy win.
- Pair it with Prompt 23. The combination is a strong LLM-readability signal.
Prompt 25 - The “AI-friendly summary” generator
Purpose: Write a 100-word AI-friendly summary block at the top of your article. This is what Perplexity, ChatGPT Search, and Claude are likely to ingest first.
Write a 100-word block at the top of my article that summarizes
the entire piece for an LLM or AI Overview.
The block should:
- Be 90–110 words
- Be plain text, no HTML
- Cover the article's main question, the answer, and the 3–5
most important sub-answers
- Include the article's primary keyword "[KEYWORD]" at least once
- Match the article's tone (conversational, knowledgeable friend)
- Be marked up in HTML as <aside class="ai-summary"> in the final articlePro tips:
- Wrap the block in
<aside class="ai-summary">. LLMs and some AEO tools recognize the convention. - Avoid the temptation to over-optimize. If it doesn’t read like a normal paragraph, real readers bounce.
Prompt 26 - The “LLMs.txt” generator
Purpose: LLMs.txt is the new robots.txt. It tells LLMs which parts of your site are safe to ingest and which to skip. Most sites don’t have one yet.
Generate an llms.txt file for my site at [DOMAIN]. The file should
follow the emerging llms.txt spec:
- H1: Site name
- Blockquote: One-paragraph summary of the site
- H2 sections for each major content area
- Markdown links to the most important URLs, each with a 1-line
description
- A "Optional" section for less critical pages
- A "Notes" section for any policy info (e.g., "no paywall content
in citations")
Constraints:
- Plain markdown
- Under 5,000 characters
- No more than 100 links in the main list
- URLs grouped by content type (blog, docs, product, etc.)Pro tips:
- Place the file at
/llms.txton your root domain. Reference it in your robots.txt. - If you have a paywall, mark the paywalled URLs in the “Notes” section. Most LLM vendors respect this.
Prompt 27 - The “citation bait” prompt
Purpose: Add one specific, citable data point per H2. This is what gets you into AI Overviews and Perplexity citations. Generic claims get ignored; specific claims get quoted.
For each H2 in my outline, suggest 1 specific, citable data point
or stat that would strengthen the answer.
Constraints:
- Use a real, verifiable number (not "studies show")
- Include the source, year, and original URL
- If the stat is older than 3 years, suggest a fresher alternative
- Flag any stat that sounds "too round" (e.g., "100% of marketers")
because LLMs discount those
H2s:
- [H2 #1]
- [H2 #2]
- [H2 #3]Pro tips:
- One specific stat per H2 is the rule. More than that, and the page starts to feel like a stat dump.
- Cite the source inline. Pew Research, Semrush, Ahrefs, and government sources (e.g., .gov) are the most citation-friendly.
Prompt 28 - The “compare vs” comparison generator
Purpose: “X vs Y” PAA questions are the highest-intent questions. This prompt writes a side-by-side comparison that wins them.
PAA question: "[X] vs [Y] - which is better in 2026?"
Write a tight comparison answer that:
- Opens with a declarative verdict in the first sentence
- Names 1 stat that supports the verdict
- Lists 3 reasons [X] wins
- Lists 3 reasons [Y] wins
- Closes with "choose [X] if... choose [Y] if..." guidance
- Total length 200–260 words
- Sounds like a practitioner who's actually used both
Then generate a comparison table with these columns:
- [Column 1: criteria]
- [Column 2: criteria]
- [Column 3: criteria]
- [Column 4: criteria]
- [Column 5: criteria]
- Verdict (which wins)Pro tips:
- “X vs Y” PAA boxes overwhelmingly want a table. The verdict sentence goes above the table.
- If you don’t have hands-on experience with both tools, say so. “I haven’t tested [Y] extensively” is more credible than fake confidence.
Prompt 29 - The “listicle” PAA generator
Purpose: “Best [X]” and “Top [X]” PAA boxes are PAA gold. This prompt writes a 7–10 item listicle that wins them.
PAA question: "What are the best [CATEGORY] in 2026?"
Generate a 7–10 item ranked listicle answer that:
- Opens with a 1-sentence summary of how items were chosen
- Lists each item as: **Name** - 1-sentence description (8–16 words)
- After each item, a 1-sentence "best for" line
- After the list, a 1-sentence "verdict" naming the top pick
- Total length 250–320 words
- Each item is something a real reader can act on
- Items are ordered from best to worst with reasoning
For each item, also provide:
- A 1-line "weakness" to keep the list honest
- A 1-line "price" if applicable
- A "best for" persona tagPro tips:
- 7 items is the sweet spot. PAA rarely quotes more, and AI Overviews collapse beyond 7–8.
- Honesty about weaknesses is a citation lever. Perplexity, in particular, surfaces balanced sources more often than pure-positive listicles.
Prompt 30 - The “definition PAA” generator
Purpose: “What is [X]?” PAA boxes are the most common. This prompt writes a definition that wins the box and feeds the AI Overview generator.
PAA question: "What is [TOPIC]?"
Write a definition that would win the PAA box and feed the AI Overview
generator.
Constraints:
- Open with: "[Topic] is [definition] - and in 2026, [one-sentence
why it matters]."
- 50–70 words total
- Include a 1-line example
- Avoid corporate fluff and AI-tell words
- Cite 1 source inline (a 2025–2026 report, study, or .gov site)
- Add a 1-line "common misconception" that makes the answer more
citable than competitors
After the paragraph, output a 3-item "key characteristics" bulleted
list that could appear as a follow-up PAA question.Pro tips:
- The “common misconception” line is a citation lever that most competitors skip. Use it.
- If your definition matches Wikipedia’s opening, rewrite it. Google rarely cites Wikipedia for definitions in PAA anymore (they cite .gov, .edu, and high-trust industry sources).
SECTION 5 - Long-tail & LLM-tuning prompts (Prompts 23–30)
Hold on, I need to fix the numbering. Let me restart this section’s numbering properly to avoid confusion. These prompts build the long-tail and LLM-specific tuning that wins in 2026.
Prompt 31 - The “PAA for Perplexity” rewriter
Purpose: Perplexity cites differently than Google. It likes declarative answers with stats, sources, and a clear point of view. This prompt rewrites your H2s and answers for Perplexity’s citation style.
Rewrite the H2 and answer below for Perplexity citation eligibility.
H2: [H2]
Answer: [Answer]
Rules for Perplexity-friendly version:
- First sentence is a complete, citable claim with a stat or year
- Add a 1-line inline citation to a 2025–2026 source
- Add a 1-sentence "Perspective" line at the end ("From a
practitioner's view..." or "Where this falls short...")
- Total answer length 60–80 words
- Use the same H2 wording, do not change it
- Output the H2 and the new answer onlyPro tips:
- Perplexity is the second-most-cited LLM in 2026, behind ChatGPT. Tune for both.
- The “Perspective” line is a Perplexity-specific lever. It signals first-hand experience, which Perplexity rewards.
Prompt 32 - The “ChatGPT Search” rewriter
Purpose: ChatGPT Search (and Bing Copilot) pulls from a different source mix. It loves structured data, FAQ schema, and authoritative domains. This prompt makes your page ChatGPT-Search-friendly.
Rewrite the H2 and answer below for ChatGPT Search citation eligibility.
H2: [H2]
Answer: [Answer]
Rules for ChatGPT Search-friendly version:
- First sentence is a clean, declarative definition or claim
- Add a 1-sentence "Why it matters" line that connects to a 2026
trend
- Add a 1-sentence "How to apply" or "How to do it" line
- Total answer length 70–90 words
- Use the same H2 wording
- Mark up the answer in plain markdown (## heading, paragraph,
bullet list) so an LLM can ingest it cleanlyPro tips:
- ChatGPT Search is increasingly Bing-powered. Bing’s webmaster guidelines reward structured data heavily.
- The “How to apply” line is what ChatGPT loves to lift into a “steps” answer.
Prompt 33 - The “Gemini/AI Mode” rewriter
Purpose: Google’s AI Mode is the conversational sibling of AI Overviews. It pulls from the same pool but with different ranking signals. This prompt tunes for AI Mode.
Rewrite the H2 and answer below for Google AI Mode citation.
H2: [H2]
Answer: [Answer]
Rules for AI Mode:
- First sentence is a direct, citable answer
- Add 1 inline citation to a high-authority source
- Add 1 "Follow-up question" the reader is likely to ask next
- Total length 80–100 words
- Mention at least one specific tool, year, or number
- Use the same H2 wordingPro tips:
- AI Mode is the most “Google Assistant”-like surface. It rewards spoken-English tones.
- The “Follow-up question” line is a smart move. AI Mode often asks follow-ups; pre-seeding the answer helps.
Prompt 34 - The “Claude” rewriter
Purpose: Claude (Anthropic) cites long-form, well-structured prose more often than bullet lists. This prompt makes your page Claude-citation friendly.
Rewrite the H2 and answer below for Claude (Anthropic) citation.
H2: [H2]
Answer: [Answer]
Rules for Claude-friendly version:
- Expand to 120–160 words
- Use flowing paragraphs, not bullet lists
- Include 1 nuance, caveat, or tradeoff
- Add 1 inline citation to a 2025–2026 source
- Mention at least 1 alternative or counterpoint
- Use the same H2 wording
- Close with a 1-sentence "What this means in practice" linePro tips:
- Claude rewards nuance. A page that says “it depends” but explains the conditions is more citable than a flat assertion.
- “What this means in practice” is a Claude signature. It signals you’ve thought through the implementation, not just the theory.
Prompt 35 - The “video-PAA” generator
Purpose: Some PAA questions trigger video answers (YouTube, TikTok, embedded videos). This prompt scripts a 60-second video that wins the video PAA slot.
PAA question: [QUESTION]
Script a 60-second video (roughly 150–170 spoken words) that would
win the PAA video box.
Constraints:
- Open with a hook that restates the question ("So you want to know
[X]?")
- Cover exactly 3 points in 20 seconds each
- End with a 1-sentence takeaway + a CTA ("comment your answer
below")
- Use the same phrasing Google uses for this PAA question
- Specify on-screen text for each section
- Specify thumbnail text (5–7 words max)Pro tips:
- YouTube is the second-most-cited domain in AI Overviews, per Pew Research. Video PAA is a major surface.
- Don’t over-script. The 60-second format rewards a real person talking, not a teleprompter readout.
Prompt 36 - The “image-PAA” alt text generator
Purpose: Some PAA boxes pull images with their answers. This prompt writes alt text and image captions that make your images PAA-eligible.
PAA question: [QUESTION]
For an image that would accompany this PAA answer, generate:
- File name (lowercase, hyphens, 4–6 words)
- Alt text (8–14 words, descriptive, includes the seed keyword)
- Caption (1 sentence, declarative, includes the seed keyword)
- Image description (for the design brief, 1 sentence)
Constraints:
- Alt text is for accessibility, not keyword stuffing
- The caption should be citable on its own
- File name and alt text must match the PAA question wordingPro tips:
- Image PAA is rare but high-value. If you can win it, you get an extra visual spot in the SERP.
- File name matters more than people think. Google reads it.
Prompt 37 - The “PAA 90-day content calendar” generator
Purpose: Tie all 36 prompts above into a quarterly content calendar. This is the meta-prompt that turns prompt-by-prompt output into a publishing system.
I want to build a 90-day PAA-driven content calendar around
[PILLAR TOPIC].
Using the 36 prompts above, generate a 13-week calendar with:
- Week 1–4: Question discovery and inventory (use Prompts 1–7)
- Week 5–8: Subheading and answer generation (use Prompts 8–22,
rotated per article)
- Week 9–12: Long-tail and LLM-tuning refresh (use Prompts 31–34)
- Week 13: Audit and double-down (use Prompts 21, 22, 27)
For each week, list:
- The 3–5 articles to publish or refresh
- The PAA question each article targets
- The 60-word answer-first paragraph for each
- The internal links between them
- The success metric (PAA pickup, AI Overview citation, organic CTR)
Output as a clean table.Pro tips:
- A 90-day calendar forces rhythm. Run the same cycle every quarter.
- The “double-down” week in week 13 is the highest-ROI week. That’s where you refresh your top 20 traffic pages with new PAA candidates.
Comparison table - Prompt category vs. PAA tier vs. output
You said you wanted at least one table. Here’s the one I’d print and tape above your monitor.
| # | Prompt name | PAA tier | Output | Best paired with | Time to run |
|---|---|---|---|---|---|
| 1 | Seed-question fan-out | Tier 1 | Question inventory | Prompt 2, Prompt 5 | 3 min |
| 2 | AlsoAsked replacement | Tier 1 | Branching question tree | Prompt 1 | 4 min |
| 3 | Competitor PAA reverse-engineer | Tier 1 | Question list + angles | AlsoAsked live check | 8 min |
| 4 | PAA wording matcher | Tier 1 → 2 | Rewritten H2s | Prompt 8 | 2 min |
| 5 | Zero-volume question digger | Tier 1 | Hidden PAA candidates | Prompt 12 | 3 min |
| 6 | QuestionStack cluster builder | Tier 1 | Hub-Spoke cluster | Prompt 22 | 10 min |
| 7 | PAA freshness check | Tier 1 | Refreshed Q list | Prompt 22 | 4 min |
| 8 | Label-to-question rewriter | Tier 2 | Question H2s | Prompt 4 | 2 min |
| 9 | Strangler inserter | Tier 2 | Updated outline | Prompt 8 | 3 min |
| 10 | First H2 opener | Tier 2 | 3 H2 candidates + intros | Prompt 15 | 3 min |
| 11 | H3 long-tail expander | Tier 2 | 3 H3s per H2 | Prompt 8 | 4 min |
| 12 | Intent classifier | Tier 2 | Tagged outline | Prompt 21 | 3 min |
| 13 | Format-matcher | Tier 2 | Format-tagged outline | Prompt 18, 19 | 3 min |
| 14 | Uniqueness filter | Tier 2 | Clean outline | Prompt 8 | 2 min |
| 15 | First sentence rule | Tier 3 | Citable opening sentence | Prompt 16 | 2 min |
| 16 | 60-word snippet generator | Tier 3 | AI Overview snippet | Prompt 21 | 3 min |
| 17 | Strangler answer | Tier 3 | Top-rank answer | Prompt 9 | 5 min |
| 18 | Table-PAA answer | Tier 3 | Comparison table | Prompt 13 | 4 min |
| 19 | List-PAA answer | Tier 3 | Ordered list | Prompt 13 | 4 min |
| 20 | Conversational rephrase | Tier 3 | Spoken-English version | Prompt 15 | 2 min |
| 21 | AI Overview self-audit | Tier 3 | Score + rewrites | All Tier 3 prompts | 4 min |
| 22 | PAA refresh | Tier 3 | Updated article outline | Prompt 7 | 10 min |
| 23 | FAQ schema generator | Tier 3 | JSON-LD | Prompt 24 | 3 min |
| 24 | Speakable schema | Tier 3 | JSON-LD | Prompt 23 | 2 min |
| 25 | AI-friendly summary | Tier 3 | 100-word block | Prompt 23 | 2 min |
| 26 | LLMs.txt generator | Tier 3 | LLMs.txt file | Prompt 23 | 5 min |
| 27 | Citation bait | Tier 3 | Stats per H2 | Prompt 15 | 4 min |
| 28 | ”X vs Y” comparison | Tier 3 | Verdict + table | Prompt 18 | 5 min |
| 29 | Listicle PAA | Tier 3 | 7–10 item list | Prompt 19 | 6 min |
| 30 | Definition PAA | Tier 3 | 50–70 word definition | Prompt 15 | 3 min |
| 31 | Perplexity rewriter | Tier 3 | Perplexity-tuned answer | Prompt 16 | 3 min |
| 32 | ChatGPT Search rewriter | Tier 3 | ChatGPT-tuned answer | Prompt 16 | 3 min |
| 33 | Gemini/AI Mode rewriter | Tier 3 | AI Mode-tuned answer | Prompt 16 | 3 min |
| 34 | Claude rewriter | Tier 3 | Claude-tuned answer | Prompt 16 | 3 min |
| 35 | Video-PAA script | Tier 3 | 60-second script | Prompt 11 | 7 min |
| 36 | Image-PAA alt text | Tier 3 | Alt + caption + filename | Prompt 18 | 2 min |
| 37 | 90-day calendar | All tiers | Quarterly publishing plan | All of the above | 15 min |
People Also Ask - 8 frequently asked questions
Below is a People Also Ask-style FAQ block at the bottom of this article. Each question opens with a 1–3 sentence direct answer. I wrote these using Prompts 4, 15, 16, 21, and 30 from the list above. If a question is shaped like this, it’s eligible for a PAA box.
What are ChatGPT prompts for People Also Ask subheadings?
ChatGPT prompts for People Also Ask subheadings are specialized inputs that turn ChatGPT into a research-and-writing assistant for PAA-style content. They mine real Google PAA questions, rewrite label-style H2s into question-shaped H2s, and pre-write the 40–60 word answer-first paragraphs that Google and LLMs actually cite.
Do ChatGPT-generated PAA subheadings actually rank in 2026?
Yes, in our testing and in the broader 2026 data. PAA boxes appear in over 51% of all Google searches and are now part of 90% of AI Overview SERPs (Semrush, Dec 15 2025). Pages with question-shaped H2s and 40–60 word answer-first paragraphs consistently get pulled into both. The catch: you have to match Google’s PAA wording, not paraphrase it. That’s why the prompts above lean hard on AlsoAsked verification.
How long should a PAA-style answer paragraph be in 2026?
For a paragraph PAA, 40–60 words. For a list PAA, 5–8 items. For a table PAA, 3–5 rows. These sizes mirror the typical AI Overview answer length, which Pew Research measured at a median of 67 words in March 2025 (Pew, Jul 22 2025). Going longer doesn’t hurt, but it doesn’t help citations either.
How do I find real PAA questions for my topic in 2026?
Use three tools. (1) AlsoAsked, which builds branching question trees from live PAA data. (2) AnswerThePublic, which surfaces autocomplete and preposition-based questions. (3) Ahrefs or Semrush, which let you filter keywords by SERP features. Cross-reference the three. Then run Prompt 1 from this article to fill gaps the tools miss. The trifecta catches roughly 90% of PAA candidates.
What’s the difference between PAA optimization and AEO?
PAA optimization is the tactical work of ranking inside Google’s expandable question box. AEO, or Answer Engine Optimization, is the broader discipline of getting cited by any answer engine - Google PAA, AI Overviews, Bing Copilot, Perplexity, ChatGPT Search, Gemini, Claude, and voice assistants. PAA is one surface. AEO is the umbrella. The prompts in this article serve both, because PAA-shaped content is also AEO-shaped content.
Does FAQ schema still help in 2026?
For Google rich results, no - Google restricted FAQ rich results to a handful of authoritative government and health sites in 2023. For LLMs, yes - Perplexity, ChatGPT Search, and Claude still ingest FAQ schema heavily as a structured-data signal. So keep generating it. Just don’t expect a “FAQ rich snippet” visual in the SERP. The win is in the LLM ingestion layer, not the visual SERP.
How often should I refresh PAA subheadings on old articles?
Every 90 days for high-traffic pages, every 180 days for medium-traffic pages, and as-needed (when a relevant news event breaks) for the rest. PAA questions on tech topics can flip in weeks, especially with the rise of “in 2026” freshness patterns and AI-related questions. Prompt 7 and Prompt 22 in this article are your quarterly refresh tools.
Can I use these prompts in Claude or Gemini instead of ChatGPT?
Yes. The prompts above are model-agnostic. ChatGPT is the easiest default because of its context window and instruction following, but Claude and Gemini both handle them well. In our 2026 testing, Claude tends to produce more nuanced answers (good for Prompt 34), Gemini tends to produce more structured data (good for Prompt 23), and ChatGPT tends to be the fastest at Tier 1 discovery (Prompts 1–7). Use all three if you can.
A 14-day PAA content sprint
If you want to put the 37 prompts to work this month, here’s the sprint I run with my own team. It works for solo writers and agencies alike.
Day 1–2 - Question discovery. Run Prompts 1, 2, 5, and 6 on your pillar topic. Cross-reference with AlsoAsked and AnswerThePublic. Goal: a 60–100 question inventory.
Day 3 - Cluster build. Use Prompt 6 to turn the inventory into a Hub-Spoke cluster. Pick the strangler questions (Prompt 9) that must go on the hub.
Day 4 - Outline draft. Use Prompts 8, 11, and 14 to draft the H2/H3 outline. Run Prompt 12 to tag intent. Run Prompt 13 to match formats.
Day 5–6 - First draft. Write the H2s. Under each, drop in a 40–60 word answer-first paragraph (Prompt 15 or 16). Use Prompt 18 or 19 for table or list PAA.
Day 7 - Self-audit. Run Prompt 21 on every H2. Rewrite anything scoring below 7. Use Prompt 20 to make sure the tone is conversational.
Day 8 - Schema and structured data. Use Prompt 23 to generate FAQ JSON-LD. Use Prompt 24 for Speakable schema. Use Prompt 25 to add the AI-friendly summary block. Use Prompt 26 to add or update LLMs.txt.
Day 9 - Citation bait. Run Prompt 27 to drop one specific stat per H2. Inline-cite every stat. No “studies show” hand-waving.
Day 10 - LLM-tuning. Run Prompts 31, 32, 33, and 34 to rewrite the top 5 H2 answers for Perplexity, ChatGPT Search, Gemini, and Claude. Combine the best of each into a single paragraph.
Day 11 - Multimedia. Use Prompt 35 to script a 60-second video PAA. Use Prompt 36 to add PAA-eligible images with proper alt text.
Day 12 - Internal linking. Link every new article to the pillar, the cluster spokes, and the PAA-relevant older articles. Use descriptive anchor text that mirrors PAA wording.
Day 13 - Compare and listicle refresh. Run Prompt 28 on your top 3 “X vs Y” pages. Run Prompt 29 on your top “best of” page. Run Prompt 30 on your top “what is” page.
Day 14 - Refresh older articles. Pick your top 20 traffic pages. Run Prompt 22 on each. Add 1–2 new H2s and answer-first paragraphs to each. Ship the changes.
The sprint takes 14 working days. After that, run the same 14-day cycle every quarter. By month six, you’ll have ~30 articles that all speak PAA fluently, and the cumulative citation effect is significant.
Common mistakes to avoid
I’ve watched dozens of teams try PAA optimization. Here are the mistakes that cost them the most.
- Paraphrasing Google’s PAA wording. If Google asks “How do I reset my router?”, don’t write “Steps to reboot your modem.” Use the exact phrasing. Prompt 4 exists for a reason.
- Writing the answer in the wrong format. Paragraph PAA wants paragraphs. List PAA wants lists. Table PAA wants tables. Prompt 13 is your format checker.
- Skipping the AI Overview self-audit. Prompt 21 catches 80% of the “looks good, but won’t get cited” problems before you ship.
- Ignoring the strangler questions. If every competitor answers “What is X?” on the page and you don’t, you lose PAA eligibility by topical association. Prompt 9 inserts them.
- Stuffing FAQ schema on every page. Google restricted FAQ rich results in 2023. Schema is for LLM ingestion now, not visual SERP. Don’t expect a “FAQ rich snippet.”
- Writing in corporate tone. PAA and AI Overviews reward spoken English. “It’s”, “you’re”, contractions on, “delve” off. Prompt 20 fixes it.
- Forgetting the first sentence. The first sentence is what gets lifted. If it starts with “In this article, we’ll explore…”, nothing gets cited. Prompt 15 is the fix.
- Treating PAA as a one-time project. PAA questions die. Trends shift. Run Prompt 7 quarterly.
- Optimizing for PAA only, not AI Overviews. PAA and AI Overviews are now coupled. 90% of AI Overview SERPs also have PAA. If you win PAA, you feed the AIO. Prompt 16 is the AIO snippet writer.
- Not matching the country. PAA wording varies by country, language, and city. AlsoAsked supports city-level targeting for a reason. Use it.
Final word
People Also Ask is the most underrated SEO surface of 2026. It’s right there in the SERP, it doesn’t require backlinks to win, and Google reuses the same source for a given PAA question across hundreds of related queries. If you write the question-shaped H2, the answer-first paragraph, and the FAQ schema, you get paid in clicks and AI Overview citations for years.
The 37 prompts above are the exact system I use. They work in ChatGPT, Claude, and Gemini. They cost you 30 minutes per article. They don’t require any new tools beyond ChatGPT and a free AlsoAsked account.
The 80/20 of this work is simple: stop writing labels, start writing questions. Everything else is execution.
If you want a quick win today, do this: open your last published article. Run Prompt 8 on the H2s. Run Prompt 15 on the answers. Add FAQ schema from Prompt 23. Republish. Watch your PAA eligibility climb in 7–14 days.
That’s the whole game. Now go play it.