The new battle isn’t just “ranking.” It’s being chosen as a source when an AI-powered search system answers, summarizes, and cites.
In AI search (ChatGPT Search, Gemini, Perplexity, and also Google with AI Overviews/AI Mode), your content competes on two layers at once:
- Eligibility: Can they crawl and access your page without friction?
- Citability: When the model needs to back up a claim, is your content the easiest to find, understand, and “lift” as a citation?
These AI search editorial guidelines are an editorial operating system to win that game: format + evidence + clarity + governance.
What changes with AI search (and why editorial guidelines matter)
In traditional search, the prize was the click. In AI search, many queries end at the answer (no navigation), and the prize becomes mention + link + citation.
One signal: Bain reported that a significant share of users frequently rely on AI summaries and that this reduces clicks to the open web. (Bain press release, Feb 19, 2025, on “AI summaries” and “no-click” behavior.)
Editorial implication: your pages must work like “answer modules,” not just long articles.
The CITA framework (Tacmind) for “citable” AI search content
Think of CITA as four questions an editor must be able to answer before publishing.
C—Crawlable: Can they crawl and access it?
- Technical requirements and baseline best practices (if they fail, you have no visibility).
- If you rely on heavy JS, poorly configured paywalls, or aggressive WAF blocks, many AI systems simply don’t “read” well.
- You can control what’s shown in Google’s AI features using the same search mechanisms (e.g., nosnippet / max-snippet / noindex).
Editorial rule: if a page is strategic for your brand, it can’t live in an inaccessible, slow, or fragile corner of your stack.
“Perfect content that can’t be crawled doesn’t exist.”
— Pablo López
I—Intent-aligned: Do you match intent without detours?
- Start with a direct answer (1–3 sentences), then expand.
- Use H2/H3 as real questions (“What is…?”, “How do you…?”, “When does it make sense…?”).
- If the topic is comparative, force a comparison structure (criteria → options → recommendation).
Lean on formats Google already understands well for extracting answers (snippets/featured snippets).
T—Trustable: Is it verifiable?
- If you use AI to produce content, Google recommends prioritizing quality, accuracy, and relevance and warns against scaled, low-value content.
- “People-first” isn’t branding; it’s an operating criterion.
- Avoid tactics that fall under spam policies (including “scaled content abuse,” deception, etc.).
Editorial rule: every “debatable” statement must be traceable to a primary source, your data, or a clear method.
A—Answer-packaged: Is it packaged to be cited?
This is the biggest AI-search shift: form matters as much as substance.
- Evidence blocks (template below)
- Definitions with a “quote-ready sentence”
- Short lists (3–7 items) and numbered steps
- Concrete examples (before/after)
- Tables (when you compare or provide checklists)
Template: the “evidence block” (the most citable format)
Use it near the top, right after the short answer, or to open a key section.
Data point / claim (1 sentence).
Minimum context (1 sentence).
Source: link to official doc / paper / dataset / regulation.
Editorial example:
Google allows AI-created content if it provides value and follows Search Essentials; the risk is scaled content with no added value.
Source: <https://developers.google.com/search/docs/fundamentals/using-gen-ai-content>
Editorial rules (the “non-negotiables”)
1) One idea per paragraph. Zero ambiguity
Models struggle with pronouns (“this,” “that,” “the above”). Repeat the key noun when needed: “AI Overviews,” “OAI-SearchBot,” and “spam policies.”
2) Define terms as “ready-to-quote”
Include one self-contained defining sentence:
- “AI search is a search experience where the system generates an answer and supports it with links/citations to sources.”
3) Headings that look like prompts
Examples:
- “What structure increases citability?”
- “How do you demonstrate experience (E-E-A-T) in a guide?”
- “Which AI crawlers should you block or allow?”
4) Use layers: TL;DR → depth → exceptions
AI often “lifts” the TL;DR; humans appreciate the exceptions.
5) Add authorship and accountability proof
- Real author + role
- Updated date
- Methodology (if data is included)
- Note AI assistance when relevant, aligned with Google’s recommendation to provide context about how content was created.
6) Don’t hide key content in PDFs or images
If you must use a PDF, ship an HTML/Markdown version that’s “citable” on-page.
At Tacmind we frequently complement this with llms.txt to curate access to key pages.
7) Structure comparisons with fixed criteria
When comparing tools/models, use the same grid for every option; here's an example of us.
8) Structured data only if it reflects visible content
Don’t mark up what isn’t actually on the page.
9) If there are warnings, say them (for readers and AI)
AI answers can be wrong. If your topic is nuanced, include a “Limitations / it depends” section.
10) Publish with a checklist and a score (not faith)
The CITA-100 score (an editorial prioritization method)
Use this to audit existing content and to validate drafts before publishing.
<div class="tg-wrap"><table class="tg">
<thead>
<tr>
<th class="tg-0pky">Dimension</th>
<th class="tg-0pky">What you review (in 2 minutes)</th>
<th class="tg-0pky">Points</th>
</tr>
</thead>
<tbody>
<tr>
<td class="tg-0pky"><strong>Crawlable</strong></td>
<td class="tg-0pky">No access blocks, visible content, canonical URLs, no WAF/paywall friction</td>
<td class="tg-0pky">0–20</td>
</tr>
<tr>
<td class="tg-0pky"><strong>Intent</strong></td>
<td class="tg-0pky">Direct answer up top, question-style H2s, one applied example</td>
<td class="tg-0pky">0–20</td>
</tr>
<tr>
<td class="tg-0pky"><strong>Trust</strong></td>
<td class="tg-0pky">Primary sources, author/role, date, caveats, people-first</td>
<td class="tg-0pky">0–20</td>
</tr>
<tr>
<td class="tg-0pky"><strong>Answer Packaging</strong></td>
<td class="tg-0pky">Evidence blocks, short lists, numbered steps, table if relevant</td>
<td class="tg-0pky">0–20</td>
</tr>
<tr>
<td class="tg-0pky"><strong>Freshness</strong></td>
<td class="tg-0pky">Recently updated, changes logged, examples still current</td>
<td class="tg-0pky">0–20</td>
</tr>
</tbody>
</table></div>
Quick interpretation
- 80–100: ready to compete for citations
- 60–79: good, but missing “answer packaging” or evidence
- <60: fix eligibility (crawlable/trust) before publishing more
“Going from 65 to 85 is usually more about format and evidence than ‘writing more’.”
— Pablo López
Mini real-world stories (repeatable patterns)
What we tried: putting the key definition in paragraph 6 (“to avoid being basic”).
What failed: in AI search, others got cited because they said it within the first screen.
Fix: definition + evidence block up top + a 5-line example.
Result: more mentions as the “definitional” source, fewer as a secondary link.
— Pablo López
What we tried: protecting content with an aggressive WAF without allowlists.
What failed: legitimate bots couldn’t access; citability dropped.
Fix: clear bot policies + log review + allowlists where appropriate.
Useful reference: OpenAI documents separate bots for search vs training (OAI-SearchBot vs GPTBot).
— Pablo López
What we tried: publishing 30 “fast” AI-assisted pieces to cover long-tail.
What failed: repetitive, low-originality content; risk of scaled content abuse.
Fix: consolidation, proprietary POV, data and sources; fewer pieces, better pieces.
— Pablo López
A 30-day implementation plan (without rebuilding your whole blog)
Days 1–3: Define your brand “canon”
- 10–20 questions you want to “own” in AI search
- 5 pages that must be citable regardless of what (pricing, product, flagship guide, glossary, comparison)
If you want to speed things up, Tacmind often starts with an AI-visibility and competitor audit:
Days 4–10: rewrite for “answer-first”
- Add a short answer + evidence block to each priority page
- Turn H2s into real questions
- Add 1 table or checklist per page (where relevant)
Days 11–17: evidence + trust
- Add primary sources (official docs, regulations, papers)
- Author + role + date + “last reviewed”
- “Limitations / it depends” section
Days 18–24: bot governance and access (the thing few teams document)
- Review robots, meta robots, and snippet controls if you need to limit extracts
- If you’re concerned about specific AI crawlers:
- OpenAI: (OAI-SearchBot vs. GPTBot)
- Perplexity: crawler docs + recommended IP lists for WAF
Days 25–30: scoring + editorial routine
- Score with CITA-100
- Turn the score into your team’s “Definition of Done”
- Schedule monthly refreshes for strategic pages
Common mistakes (and fast fixes)
- Starting with long storytelling for informational queries.
- Fix: TL;DR up top + story later.
- Soft definitions (“it’s a tool that helps…”).
- Fix: technical definition + example + boundary.
- No sources or low-trust sources.
- Fix: link primary sources (official documentation). Start with Search Essentials and spam policies for SEO/AI topics.
- Structured data that doesn’t match visible content.
- Fix: align markup and on-page text.
- Ignoring snippet controls (when you care how much gets shown).
- Fix: Use nosnippet/max-snippet where relevant.
FAQ
Are “AI search editorial guidelines” the same as SEO?
Not exactly. SEO is necessary; citability is the extra layer. You still need technical foundations + quality, but you must also package answers for extraction and citation.
Does Google penalize AI-generated content?
Not for using AI per se; the risk is publishing scaled content with no added value.
What formats do AI systems cite best?
Clear definitions + short lists + numbered steps + evidence blocks tied to primary sources.
Do I require structured data to get cited?
Not always, but it can help consistency and understanding if implemented correctly and aligned with visible content.
How do I manage AI bots (allow/block) without breaking Search?
Treat access and training as separate where providers support it. For example, OpenAI documents separate bots for search vs. training.
What if my team has no time?
Start with five “canon” pages and raise their CITA-100 score. That’s where you’ll see results fastest.
Final checklist (paste into your editorial workflow)
- Direct answer within the first scroll
- Quote-ready definition (1 sentence)
- 1 evidence block with a primary source
- H2s written as real questions
- 1 list or numbered steps (if relevant)
- Author + role + date + last reviewed
- Primary sources linked (not only blogs)
- CITA-100 review before publishing
If you want to turn this into a measurable system (prompts → mentions → sources → actions), you can start with a quick platform trial.
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