🚨ServiceNow agreed to acquire cybersecurity startup Armis for $7.75 billion in cash—the company's largest acquisition ever—betting that enterprise security and AI trust will be inseparable as businesses scale AI deployments across increasingly complex attack surfaces.

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A small cohort of native ad operators are quietly outperforming their competitors by 3-5x. Their secret? They're studying persuasion techniques that governments spent decades perfecting to move entire populations.

While most marketers are split-testing button colors and subject lines, a growing underground of performance marketers has discovered something far more powerful: historical propaganda archives. Not for shock value or edginess—but because these materials represent the most extensively tested emotional triggers in human history.

The method is surprisingly simple, almost embarrassingly so. Open an AI tool like Gemini or Claude. Search for "[country name] propaganda posters" or "wartime persuasion campaigns." Analyze the psychological frameworks used—fear amplification, in-group loyalty, moral urgency, scarcity of safety. Then adapt those emotional triggers to your native ad copy.

Congratulations. You just tapped into 100+ years of A/B tested persuasion techniques that moved entire populations to sacrifice, save, fight, and buy war bonds.

How it works:

The process follows a straightforward research-to-implementation workflow:

Step 1: Access the archives

Search Google, Library of Congress archives, or AI vision tools for propaganda materials from major campaigns: WWII homefront posters, Cold War messaging, public health campaigns, wartime recruitment materials. The key is choosing campaigns where the stakes were existential—governments don't half-ass persuasion when survival is on the line.

Step 2: AI-powered framework extraction

Upload propaganda images to Gemini, GPT-4 Vision, or Claude. Ask: "What psychological frameworks and emotional triggers is this using?" The AI breaks down:

- Primary emotion targeted (fear, duty, shame, pride)

- Cognitive biases exploited (loss aversion, social proof, authority)

- Rhetorical structure (us vs. them, ticking clock, moral imperative)

- Visual hierarchy and attention patterns

Step 3: Pattern identification

After analyzing 15-20 pieces from the same campaign, patterns emerge. You'll notice governments repeatedly used specific formulas:

- "Your [loved one] needs you to [action]" (personalization + duty)

- "While you [comfortable thing], they [suffer]" (guilt + contrast)

- "Every [small action] brings [big outcome] closer" (empowerment + impact scaling)

- "[Enemy/problem] won't wait" (urgency + external threat)

Step 4: Ethical adaptation

How it works:

Here's where legitimate marketers separate from manipulators. The frameworks are tools—how you use them matters. Apply these triggers to:

- Products that genuinely solve problems

- Offers with real value propositions

- Copy that doesn't deceive

For example, a WWII poster showing "Loose Lips Sink Ships" uses fear + responsibility + clear cause-effect. Adapted ethically to cybersecurity software: "One weak password can sink your entire business. Protect your team in 3 minutes."

The core trigger (fear of being the weak link that causes disaster) remains. But it's applied to a real problem with a real solution.

What makes this different from traditional swipe files:

Most copywriters study... other copywriters. They're looking at David Ogilvy, Gary Halbert, and Eugene Schwartz—masters, absolutely. But they're studying commercially-motivated copy that had to be profitable, not existentially critical.

Propaganda materials had different constraints:

- Unlimited testing budgets (governments don't worry about ad spend when national survival is at stake)

- Mandatory response tracking (recruitment numbers, war bond sales, rationing compliance)

- Decades of iteration (WWI lessons informed WWII, which informed Cold War messaging)

- Cross-cultural validation (similar techniques worked across completely different populations)

When Britain needed housewives to save kitchen scraps for munitions, they didn't guess at emotional triggers. They tested, measured, and optimized until every household complied. Those frameworks are pure distilled persuasion.

The WWII example:

American war bond campaigns generated $185.7 billion (inflation-adjusted: $2.6 trillion) from ordinary citizens. The posters and ads achieving this didn't rely on price promotions or limited-time offers. They used:

- Social proof ("Your neighbors are buying bonds—are you?")

- Identity-based messaging ("Real Americans support our boys")

- Loss framing ("Every dollar NOT invested is a bullet for the enemy")

- Future pacing ("When we win, you'll know YOU helped")

Those same frameworks, adapted:

- "Join 127,483 marketers who refuse to settle for 2% conversion rates"

- "Real founders invest in tools that scale their business, not band-aids"

- "Every day without this system costs you qualified leads"

- "When you hit your revenue goal, you'll know THIS was the turning point"

The market context: Why this matters now

Performance marketing is in a crisis of sameness.

Facebook's ad costs are up 61% year-over-year (2024 data). Native ad platforms like Taboola and Outbrain are saturated with identical hooks: "Doctors hate this," "One weird trick," "Number 7 will shock you." Click-through rates are plummeting because consumers have pattern recognition—they smell generic marketing from a mile away.

Meanwhile, AI writing tools are flooding the market with more of the same templated copy. ChatGPT trained on the same Copyblogger articles everyone else read. More words, same emotional triggers everyone's already numb to.

The marketers who win in this environment are those who dig deeper into human psychology—not surface-level "curiosity gaps" but fundamental emotional architecture.

And whether we like it or not, propaganda represents the most thoroughly documented case study of mass persuasion in human history. These aren't marketing theories from a $97 course. They're frameworks that convinced millions of people to:

- Send their children to war

- Ration food they desperately needed

- Buy bonds instead of feeding their families

- Completely restructure their daily lives

That's the power of properly executed emotional triggers.

What's next

This approach will either get normalized or stigmatized—no middle ground.

Path 1: Normalization

Marketing education catches up. Copywriting courses add "historical persuasion case studies" sections. It becomes as standard as studying Ogilvy or Bernbach. The ethical frameworks mature. Industry norms develop around appropriate vs. manipulative use.

Path 2: Stigmatization

A high-profile scandal. Someone takes it too far—selling snake oil with war-level persuasion techniques, causes harm, gets exposed. Media runs "Marketers Are Using Government Mind Control Tactics" stories. The practice gets blacklisted, driven further underground.

The smart money is on Path 1, with better ethical guard rails. Because the fundamental insight is sound: if you want to understand what truly moves human behavior, study the campaigns where failure meant national collapse.

Just use that knowledge responsibly.

BTW: The algorithm already knows

Facebook's ad algorithm, Google's quality score systems, TikTok's content recommendations—they're all optimizing for engagement, which is code for "emotional response."

The platforms are already rewarding content that triggers strong feelings. They just don't advertise that their algorithms prefer fear, outrage, and urgency over calm rationality.

Have an ad concept ready but don't want to deal with expensive shoots or stock footage? ScriptKit lets you generate, curate, and edit AI ads in one platform.

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The Recap: Italy's competition authority (AGCM) ordered Meta to suspend its WhatsApp policy that bans rival AI chatbots from using the messaging app's Business API, finding enough evidence that the policy may constitute abuse of dominant position. Meta updated its WhatsApp Business terms in October to prohibit general-purpose AI assistants like ChatGPT, Claude, and Perplexity from the platform starting January 15, 2026, while keeping its own Meta AI accessible—a move regulators say could cause "serious and irreparable harm" to competition in the rapidly evolving AI chatbot market.

Unpacked:

Bottom line: Meta's WhatsApp chatbot ban reveals the next battleground in AI competition: not model capability, but distribution access. Platform owners with billions of users can theoretically decide which AI assistants reach consumers, turning messaging apps into choke points for the entire AI industry. Italy's intervention establishes that dominant platforms can't unilaterally close distribution channels they previously opened to third parties, especially after launching competing products.

ServiceNow acquired Israeli cybersecurity firm Armis for $7.75 billion in its largest-ever deal, jumping 27% above Armis' $6.1 billion valuation from just one month ago—signaling enterprise giants are paying premiums to consolidate security capabilities as AI adoption expands attack surfaces faster than companies can defend them.

Waymo discovered testing Gemini as an in-car AI assistant through a 1,200+ line system prompt found in its app code, revealing autonomous vehicle leaders are outsourcing conversational AI to cloud providers rather than building it internally—exposing that self-driving tech companies now depend on external AI infrastructure for the rider experience layer.

Trump administration banned all new foreign-made drones from receiving FCC authorization starting this week, effectively blocking DJI and other Chinese manufacturers from launching new models in the U.S.—forcing first responders and businesses that rely on drones to choose between aging equipment or paying significantly more for less capable domestic alternatives.

Apple agreed to allow third-party app stores and external payment systems in Brazil within 105 days to settle a three-year antitrust investigation, marking another jurisdiction where regulatory pressure fractured Apple's unified iOS control after similar concessions in the EU, Japan, and South Korea.

John Carreyrou joined other authors in a new lawsuit against six major AI companies over training data usage, adding to the fragmented liability landscape where copyright holders are pursuing parallel class actions across jurisdictions—creating long-tail legal costs that could reshape frontier model development economics.

Gaming community polarization over AI intensified in 2025 as corporate adoption clashed with creator resistance, suggesting mainstream AI integration will follow a polarization trajectory rather than consensus—where adoption happens despite vocal opposition, not through cultural buy-in.

Matrix protocol abandonment by security-focused organizations exposes how open infrastructure struggles to meet enterprise security requirements, revealing that decentralization's appeal may be permanently limited by the need for centralized trust and accountability mechanisms that open protocols can't provide.

Best of AI™ Team

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