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Valentine’s Day may now be synonymous with chocolates, flowers, and heart-shaped everything, but its origins are far more complex, blending ancient Roman traditions, Christian martyrdom, and medieval storytelling.
What began as a mid-winter festival tied to fertility and renewal eventually evolved into a celebration of romantic love - one shaped as much by poets and pop culture as by saints and religious history.
Ancient Roots: Before Romance, There Was Ritual Long before Valentine’s cards, ancient Romans celebrated Lupercalia, a mid-February festival focused on fertility, purification, and the coming of spring. The event included symbolic rituals meant to ward off evil spirits and promote health and fertility, far removed from today’s candlelit dinners.
As Christianity spread through the Roman Empire, many pagan festivals were re-interpreted or replaced with Christian observances, laying the groundwork for what would become Valentine’s Day.
Who Was Valentine, Anyway? There isn’t just one Valentine. Historical records point to multiple early Christian martyrs named Valentine, the most famous being Saint Valentine, executed in the 3rd century CE.
One popular legend claims he secretly performed marriages for young couples despite a Roman ban, acts that ultimately led to his execution. While historians debate the accuracy of these stories, they helped cement Valentine’s association with love, sacrifice, and devotion.
Love Enters the Story: Medieval Poets Change Everything Valentine’s Day as a romantic holiday didn’t truly take shape until the Middle Ages. English poet Geoffrey Chaucer is often credited with linking February 14 to romantic love in his poetry, helping popularize the idea that it was the day birds chose their mates.
From there, the connection between Valentine’s Day and courtly love spread across Europe, especially among the nobility, eventually giving rise to handwritten love notes and tokens of affection.
From Handwritten Notes to Hallmark By the 18th and 19th centuries, Valentine’s Day had become a popular occasion for exchanging cards, flowers, and gifts. The Industrial Revolution made printed cards widely available, transforming a once-elite tradition into a mass-market celebration.
Today, Valentine’s Day is a global cultural phenomenon, equal parts romance, commerce, and tradition, evolving to include friendships, self-love, and inclusive expressions of connection.
It isn’t just about romance, it reflects how traditions evolve over time, absorbing layers of culture, religion, and storytelling. Understanding its history helps explain how societies redefine love, relationships, and celebration across generations.
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But there's a catch: You can’t just buy your way in ChatGPT will soon include “clearly labeled sponsored listings” at the bottom of AI-generated responses. And while the mock-ups don't appear all that sophisticated, it's important to focus on the bigger picture.
We're about to see a new wave of 'high-intent advertising' that combines the targeting sophistication of social media with the purchase-intent clarity of search advertising. More on that in a moment.
How Do ChatGPT Ads Work? Starting later this month, free users of the ChatGPT platform and those under 18 will begin receiving Ads at the bottom of their screens.
First, they will see ChatGPT's answer to their question, which provides a comprehensive, relevant response that builds trust.
Then they will see an ad for a sponsored product/service below. An ad that suddenly doesn't feel like a blunt interruption. It feels like a natural next step.
This is premium placement. The user has already received value. They've been educated. And now there's a clear call to action (CTA) that's in context. Open AI has stated that their new Ads “support a broader effort to make powerful AI accessible to more people.” Translation: As they approach 1 billion weekly users across 171 countries using ChatGPT for free, OpenAI needs to offset its astronomical burn rate with ads. Makes sense.
This New Era of Conversational Ads Will be Complicated But there's a structural difference with these new ads. OpenAI has stated that ads will only appear when they're relevant to that exact conversation.
This means you can't just buy your way into ChatGPT Ads. In fact, with ChatGPT you are being selected because you're the right answer the user needs at that time. Put another way: When ChatGPT evaluates which sponsored products to show, it will favor brands with demonstrated authority on the topic.
So unlike traditional paid search, where a higher bid gets you ranked in sponsored results, ChatGPT Ads will reward the brands whose content has already been recognized as authoritative by the AI model.
Brands with strong organic visibility, topical expertise, and content that aligns with user intent will have a distinct competitive advantage from day one. Brands without that foundation will be paying premium rates to compete with established authorities. How ChatGPT's Ad Strategy is Set to Change Digital Marketing For years, CMOs have treated organic search and paid search as separate budget lines, often managed by different teams. I saw this firsthand, as I helped my client DoubleClick launch it’s first Ad Exchange network in the US market. Programmatic exchanges brought a new efficiency to digital ad buying. It was a very groovy time.
This feels very different. Why? Because, the conventional wisdom has always been that paid search and ads drive immediate results while organic search plays the long game. In 2026, that strategy isn’t completely obsolete.
But that type of thinking is about to get a lot more expensive for clients if they don't start to appreciate quality "organic" content and its ability to improve their paid advertising ROI. Now organic and paid need to get along, to get ahead. ChatGPT Ads Are Looking for Topical Authority that Experts Can Demonstrate When ChatGPT evaluates which sponsored products to show, it will favor brands with demonstrated authority on the topic. Brands won't simply be able to "buy" visibility.
OpenAI in its announcements, has been explicit: ads must be relevant to the conversation. Relevance is determined by topical alignment, not budget. A brand spending millions on generic bidding will lose to a smaller competitor whose product is more precisely aligned with what the user actually asked.
The ads aren't live yet. But the infrastructure supporting them is. Open AI, Google and many of the other generative search platforms are building very sophisticated systems that track topical authority and content quality signals. They're already reshaping how organic search, AI recommendations, and paid advertising work together.
Topical Relevance + Expert Authority is the Path to Visibility in Search Investing in well-developed thought leadership programs generates compound returns. You get the organic search results plus an improvement in your paid search metrics in Generative AI search platforms. When done right, you build authority for AI citations, which then positions you better for ChatGPT ads.
Remember, your organic traffic gains are built on authoritative content. They're built on being the answer that search engines and AI systems select. And once you've built that authority, it works everywhere—traditional search, AI Overviews, ChatGPT, and soon… ChatGPT ads.
What To Do Before AI Ad Networks Start to Scale The early advantage will go to brands that invest in quality content right now. Organizations that invest in expert-authored, intent-aligned content over the next six months will have more AI citation visibility from Google Overviews and similar LLM's like ChatGPT. That means more trust signals, making paid ads more effective when they run.
Content that is aligned with user intent: Answers a specific question. Not tangentially, not after 2,000 words of context. The answer appears in the opening paragraph, structured for AI extraction.
Includes expert perspective. Generic information that could come from anywhere doesn't differentiate you. Expert insight, original research, or proprietary frameworks do.
Demonstrates topical authority. A single authoritative article matters less than a cluster of related content that shows comprehensive expertise on a topic.
Is structured for scanning. Clear headings (H2, H3), bullet points, tables, Q&A blocks. This structure helps both human readers and AI systems parse meaning.
Remember, the brands that get the most value out of ChatGPT Ads will be the ones that built intent-aligned content years before the ads launched. They'll have topical clusters, expert perspectives, and the authority signals that make them the natural choice for sponsorship. Questions CMO’s Should Be Asking their Teams Now to Prepare for ChatGPT Ads Q. Can I pre-purchase Chat GPT Ads? As of today, there are currently no ads in ChatGPT. Open AI has announced that they will begin internal testing ads in ChatGPT later this month for Free users in the US market.
Q. Do Ads influence the answers ChatGPT gives you? What about privacy? Open AI in their release states that answers are optimized based on what's most helpful to you. Ads are always separated and clearly labeled from Answers. They also state that they keep your conversations private from advertisers and will never sell your data to advertisers.
Q. How do we audit our site content to ensure we're aligned with user intent? For your top 20-30 decision-stage queries (the ones that drive revenue), here's a quick test. Does the content directly answer the question in the opening paragraph? Are you including question-and-answer formats in your content? If you're burying the answer in a 3,000-word article full of tangents, you're losing visibility in organic search, and you're already failing in ChatGPT's environment. Restructure.
Q. How do we prepare for ChatGPT Advertising Opportunities? Build topical authority through content clusters. Don't publish isolated blog posts. Organize your content around core topics your audience cares about. Create a long-form hub article that comprehensively covers the topic, then develop additional linked articles that dive into sub-topics and questions. Link them together. This structure helps AI systems over time, recognize your brand as authoritative on that topic, which improves both organic rankings and AI citation rates.
Q. Can we still get traction with content that is not authored by experts? Generic AI-written content won't differentiate you. Get expert voices into your content. Feature your subject-matter experts, partner with practitioners, and customers to contribute original insights, case studies, or frameworks. AI systems can detect authenticity, and original expert perspectives is now a ranking signal. This is especially critical as you prepare for ChatGPT ads. OpenAI has prioritized conversations that cite authoritative sources.
Q. How does content need to be structured for citations? Implement proper schema markup and structured data. AI systems extract information by parsing content structure. If your pages include proper schema markup (FAQPage, HowTo, Review, Product schema), you're making it easier for AI to pull your content into answers. This increases citation rates, which builds authority before ChatGPT ads scale.
Q. How do we allocate our organic and paid programs? Own the organic + paid intersection. For your highest-intent topics, if you have a budget, invest in both organic visibility and paid campaigns. Run ads targeting the same keywords where you rank organically. This takes up more real estate on the results page and signals authority. It also gives you direct feedback on keyword performance, messaging, and landing page effectiveness—data that informs your organic content strategy and drives more citations - a virtuous cycle.
Q. What types of creative will work best in these new Ad products? Until they roll out, it's unwise to make too many predictions. The safe bet here is to prepare your team for conversational advertising. ChatGPT ads won't reward traditional ad copy. They'll reward clarity, specificity, and direct value messaging. If you're used to brand-heavy, aspirational creative, this will feel foreign. Start testing conversationally-appropriate messaging now. Short, clear, problem-focused. Test on existing paid channels and refine before ChatGPT ads launch.
Our Prediction When ChatGPT ads fully launch and scale, many brands that have invested in organic visibility and content quality will start to pull away from the pack.
Remember…The brands that win won't be the ones with the biggest ad budgets. They'll be the ones whose content has already proven they're the right answer. They'll be the ones users already trust, already cite, and already know.
The ads are coming. Are you ready?
AI is changing how people discover expertise.
Today, journalists, event organizers, researchers, and the public increasingly turn to tools like ChatGPT, Claude, Perplexity, and Google Search’s AI summaries powered by Gemini. Instead of clicking through pages of links, they expect clear, credible answers—often delivered instantly, with citations.
That shift has major implications for organizations.
It’s no longer enough for your experts to “rank well.”
They need to be understood, trusted, and accurately represented by AI systems. So the real question becomes:
When AI talks about your experts, does it get it right? This is where LLMs.txt plays an important role—especially when paired with an ExpertFile-powered Expert Center.
What is LLMs.txt (In Plain English)? ...and why is it essential for expert content LLMs.txt is a small, machine-readable file placed on your organization’s website—in the case of your expert content alongside your main Expert Center. Its purpose is simple:
to explain your expertise to AI systems clearly and unambiguously. “AI systems don’t just scan for keywords; they look for clear meaning, consistent context, and clean formatting — precise, structured language makes it easier for AI to classify your content as relevant.” Microsoft: Optimizing Your Content for Inclusion in AI Search Answers Rather than forcing AI to infer meaning from scattered pages, LLMs.txt explicitly tells systems:
Who your experts are Which pages represent official, curated content How expert profiles differ from articles, Q&A, or research content How your organization’s expertise should be interpreted as a whole Think of it as a table of contents and usage guide for AI —helping large language models understand your site the way a communications professional would.
Why This Matters for Visibility and Trust It Establishes Your Organization as the Source of Truth AI systems routinely synthesize information from multiple places. Without guidance, they may rely on outdated bios, scraped content, or secondary references.
LLMs.txt provides a clear signal:
This is our official expert content. This is what represents us. For ExpertFile clients, this matters because the platform already centralizes and curates expert content—from profiles and directories to Spotlights and Expert Q&A—ensuring that what AI sees is current, governed, and institutionally endorsed.
The result: Greater accuracy, stronger attribution, and reduced risk of misrepresentation when your experts appear in the ever growing AI-generated overviews and answer.
ahrefs: AI Overviews Have Doubled How It Improves Discovery Across AI Platforms It Makes Structured Expertise Easier for AI to Use ExpertFile is purpose-built to publish structured expert content at scale—content that goes well beyond static bios. LLMs.txt simply helps AI recognize and use that structure correctly.
It clarifies the role of key ExpertFile content types, including:
Expert Profiles → Canonical identity, credentials, and areas of expertise Spotlight Posts → Timely commentary, thought leadership, and research insights Expert Q&A → Authoritative answers to real-world questions Directories, Research Bureaus, and Speakers Bureaus → Curated collections of expertise by topic or audience This makes it easier for AI systems to:
Match your experts to breaking news and trending topics Pull accurate summaries for AI-generated responses Identify the right expert for journalists, event organizers, and researchers Combined with ExpertFile’s extended distribution through expertfile.com and the ExpertFile Mobile App, your expertise is not only published—but actively discoverable across channels used by key audiences .
How It Builds Organizational Authority It Connects Individual Experts to Institutional Credibility Without context, AI may treat expert pages as isolated profiles. LLMs.txt helps connect the dots.
It tells AI that:
Your experts are curated and endorsed by the organization Their insights are part of a broader expertise ecosystem Your institution has depth across priority subject areas This aligns closely with how ExpertFile structures content to support E-E-A-T (Experience, Expertise, Authority, Trust)—not just at the individual level, but across the organization .
The outcome: Your organization is recognized not just as a collection of experts, but as an authoritative source of knowledge.
How It Works with Google, Gemini, and AI Search Supports AI Summaries, Citations, and Knowledge Panels LLMs.txt helps ensure that when Google’s AI:
Summarizes your organization Cites expert commentary Builds “about this topic” panels …it draws from your official, structured ExpertFile content, rather than fragmented third-party sources.
This complements ExpertFile’s existing SEO and AI-discoverability foundation, which includes clean code, proper meta data, schema markup, and frequent crawling by both search engines and AI bots.
How LLMS.txt Fits with SEO, Meta Tags, and Schema LLMS.txt doesn’t replace SEO—it builds on it. Traditional SEO elements such as page titles, meta descriptions, schema.org markup, and internal linking remain essential for helping search engines index and rank your content.
ExpertFile already delivers these fundamentals out of the box, continually testing and evolving SEO and GEO (Generative Engine Optimization) standards as search changes .
“Semantic SEO helps search engines understand context... it now helps bridge a critical gap between traditional SEO and newer generative engine optimization (GEO) and AI optimization (AIO) efforts.” Search Engine Land: Semantic SEO: How to optimize for meaning over keywords LLMS.txt adds a layer designed specifically for AI systems: Schema explains individual pages LLMs.txt explains your entire expertise ecosystem In simple terms: SEO helps your content get found LLMs.txt helps AI understand, summarize, and cite it correctly Together, they ensure your experts are not only visible—but accurately represented wherever AI is shaping discovery.
Why This Is Especially Powerful on ExpertFile ExpertFile was designed to future-proof expert visibility—offering structured publishing, governance, distribution, inquiry management, analytics, and professional services as part of a continuously evolving SaaS platform .
LLMS.txt acts as a multiplier on that foundation:
Turning your Expert Center into a machine-readable expertise hub Strengthening AI discovery without adding operational burden Supporting emerging use cases like automated expert matching and AI-assisted research It’s not about chasing new technology.
It’s about ensuring your expertise is clearly defined, properly attributed, and trusted—now and in the future.
The Takeaway An LLMs.txt file on your ExpertFile organization page helps ensure that:
Your experts are found by AI tools, not overlooked Your content is interpreted correctly, not flattened or misrepresented Your organization earns authority and trust in AI summaries, citations, and search results “AI search isn’t eliminating organic traffic. But it is reducing visits to source websites… Measure presence (citations, mentions) alongside traffic to see real impact.” Semrush: AI Search Trends for 2026 & How You Can Adapt As AI becomes the front door to information, LLMs.txt helps make sure that when people ask for expertise, your organization is the answer they get.
