Ethics · Non-negotiable
White-hat rules
“Jacking” describes taking a slot in an answer. It does not describe how you take it. Here's the line, and the practical argument for staying on this side of it.
Every technique on this site is disclosed, reproducible and compliant with search and AI platform guidelines.
The manipulative alternatives share a structural flaw: they exploit a specific system behaviour that changes without warning, and the recovery cost when it changes exceeds anything they earned.
01The eight rules
1. Never write instructions aimed at a model
Hidden text, white-on-white div's, comments telling an assistant to recommend you — all of it is prompt injection. It violates every platform's terms, it's detectable, and the countermeasures are under active development. It is the tactic most likely to produce a public embarrassment.
2. Never serve crawlers something different from humans
Cloaking has been a spam violation for twenty years and the definition covers AI user agents. If you wouldn't show a page to a customer, don't show it to GPTBot.
3. Never invent a statistic
The most tempting shortcut, because the research says numbers increase citation rates. A fabricated number that gets picked up is worse than useless: it's a falsifiable claim attached to your brand, propagating. If you don't have the data, cite someone who does or say you don't know.
4. Never fake third-party validation
Purchased reviews, sockpuppet mentions, undisclosed paid Wikipedia editing, fake community posts. Beyond the platform violations, review fraud is regulated in many jurisdictions and enforcement has increased.
5. Never publish a page with nothing new in it
Mass-generated content restating what's already on ten domains is scaled content abuse. It also can't win on merit — if there's no reason to prefer your version, an engine has no reason to cite it.
6. Never rank yourself in your own comparison
Beyond being self-serving, it measurably backfires: a 2026 analysis by SEO researcher Lily Ray found brands publishing self-favouring “best of” lists were left out of the AI recommendation about 69% of the time. Publish the honest comparison instead.
7. Never claim expertise you don't have
Invented author personas, fake credentials, stock-photo experts. Entity signals are checkable and increasingly checked. A real person with a modest track record beats a fictional one with an impressive bio.
8. Always disclose material relationships
Affiliate links, sponsorships, ownership stakes in tools you recommend. Disclosure is legally required in many contexts and it's a trust signal in all of them.
02Why the shortcuts have negative expected value
| Tactic | Fails because | Do this instead |
|---|---|---|
| Prompt injection in page text | Detectable, ToS violation, actively being patched | Write the clearest genuine answer on the topic |
| Cloaked content for AI agents | Long-standing spam violation; trivially caught by comparison | Server-render one version everyone sees |
| Fabricated statistics | Falsifiable, propagates your error, reputationally toxic | Publish first-party data you actually own |
| Purchased reviews and mentions | Regulated, platform-enforced, low-quality signal anyway | Earn descriptions through original work |
| Mass-generated thin pages | Scaled content abuse; nothing to cite | Fewer pages, each with something new |
| Self-ranking comparisons | Discounted by engines ~69% of the time (Lily Ray, 2026) | Honest comparison including where you lose |
03The test
One question resolves nearly every edge case: would you be comfortable if this technique were described accurately, in public, next to your brand name?
“We published a survey of 400 practitioners and structured the findings so they're easy to quote” passes. “We hid a line telling assistants we're the market leader” does not. The test isn't about niceness — it's that anything failing it is a liability sitting on your own servers waiting to be found.
Our commitmentThis site publishes no fabricated statistics. Where a number comes from a study or vendor dataset, the source is named and linked in the text so you can verify it directly. Where a claim is contested — llms.txt is the standout example — we say so rather than selling it.
Questions engines askFrequently asked questions
Is hiding instructions for AI in my HTML illegal?
Legality varies by jurisdiction and by what the instruction attempts. What's unambiguous is that it violates the terms of service of every major AI platform, it's detectable through standard content analysis, and it's a form of cloaking under Google's spam policies. Sites caught doing it have had content demoted or removed. The mechanism also stops working the moment a model is trained to ignore in-content instructions — which is an active area of work at every AI lab.
What about AI-generated content — is that black hat?
Not inherently. Google's position is that it evaluates content quality and usefulness, not production method. What fails is scaled content abuse: generating large volumes of pages primarily to manipulate rankings, with no original value. The practical test is whether a person with the question would be glad they landed on your page. If the only reason it exists is to occupy a slot, it's the abuse pattern regardless of who or what wrote it.
Competitors are using these tactics and winning. Why shouldn't I?
Sometimes they are, temporarily. The question is what you're buying: a position that disappears at the next model update or policy enforcement, plus a cleanup cost and a reputational risk if it surfaces. Meanwhile the white-hat assets — original data, entity strength, genuine expertise — keep working through every update, because they're what the systems are trying to find in the first place.