AI isn’t writing your next Pulitzer-winning article—at least, not yet. But it does have something in common with a sleep-deprived journalist on a deadline: it predicts what should come next, based on patterns it has seen before.
Let’s break down how Large Language Models (LLMs) actually work—without the sci-fi hype.
(Note: this post was written entirely by ContentlyAI (v0.3). While it was reviewed by a human, it’s not yet perfect!)
Step 1: AI Reads Like a Research Intern, But With Some Major Flaws
Before ChatGPT could generate articles, OpenAI trained it by feeding it a massive slice of the internet—books, articles, websites, and more. Think of it like a media intern who’s been handed every past edition of The New York Times, Wikipedia, and thousands of blog posts to skim through.
But unlike a human researcher, AI isn’t thinking about what it reads. It’s not fact-checking. It’s just absorbing billions of words to recognize how language flows.
A real-world example: If an AI reads thousands of sports recaps, it will recognize that phrases like “clutch performance,” “narrow victory,” and “came from behind” often appear in game summaries. It doesn’t understand sports—it just knows the phrases go together.
A key stat: The training dataset for LLMs can contain trillions of words—OpenAI’s GPT-4 model is estimated to have been trained on over 15 trillion tokens (small chunks of text).
Contently Insight
At Contently, we take AI training a step further. Instead of pulling from generic, mass-scraped internet content, our AI is fine-tuned on high-quality, industry-specific content from our proprietary repository. This ensures AI-generated suggestions align with expert-driven insights, rather than surface-level internet patterns.
Step 2: AI Doesn’t Write—It Predicts
Ever typed a text message and had your phone guess the next word? That’s exactly how LLMs work—but on a much larger scale.
When you type a prompt into ChatGPT, the model doesn’t know the answer. It looks at your words and tries to predict the most statistically likely next word, then the next, and so on.
Imagine you start with:
- “The content marketing industry is…”
Based on what it has read before, the AI might think:
- “…evolving rapidly.” (Common marketing phrase)
- “…experiencing major changes.” (More general but still reasonable)
- “…ruled by SEO trends and audience engagement.” (A bit spicier)
This is why AI can sound impressively fluent—but also why it sometimes hallucinates and makes things up. If it doesn’t have strong data patterns to rely on, it just makes its best guess, even if it’s incorrect.
A real-world example: AI-generated articles have been caught inventing fake quotes and nonexistent studies because they mimic how journalism sounds, not how research works. In 2023, a lawyer was penalized for citing fake court cases in a legal brief—because ChatGPT made them up.
Contently Insight
AI-generated content can only be valuable if it’s accurate. That’s why Contently AI includes a built-in fact-checking agent that verifies statements before they appear in copy. It searches the web, cross-references multiple sources, and ensures that AI-generated text is grounded in real, up-to-date facts before delivering it to writers and editors.
Step 3: AI Gets Fine-Tuned to Be More Useful
Without some post-training polish, AI would be an unreliable, robotic text generator. Companies like OpenAI, Google, and Anthropic refine their models using human feedback.
How they do it:
- Adding conversation rules: AI is trained to respond helpfully and politely.
- Avoiding misinformation: It’s taught to say “I don’t know” instead of guessing (though it doesn’t always follow this rule).
- Filtering biases: AI teams refine responses to avoid offensive or misleading content.
This fine-tuning is why ChatGPT sounds more natural and why AI models can refuse to answer certain questions.
A real-world example: If you ask ChatGPT, “How do I get around paywalls?” it won’t give you an answer because it was trained to avoid unethical content. But if you ask, “What are the best free journalism sources?” it’ll happily provide a list.
Contently Insight
Contently AI is fine-tuned for marketing, media, and publishing professionals, ensuring that it suggests content aligned with brand guidelines and audience needs. It doesn’t just generate content—it refines and optimizes it for industry relevance, high engagement, and LLM discoverability.
Step 4: AI Still Has Blind Spots—But They’re Disappearing
Early AI models had a major limitation: they weren’t connected to the live web, meaning their “knowledge” was frozen in time. This was a problem for industries like media and marketing, where real-time information matters.
That’s no longer the case. Most modern LLMs—like OpenAI’s GPT-4 Turbo, Google Gemini, and Meta’s LLaMA 3—are now connected to the internet, allowing them to retrieve the latest data when necessary.
A real-world example:
- If you ask a modern AI, “What’s the latest Instagram algorithm update?” it can now pull in real-time information instead of relying on outdated training data.
- AI-generated blog posts can now be informed by the latest trends, rather than recycling stale best practices.
A key stat: Studies show that over 70% of marketers are experimenting with AI-generated content, but fact-checking and brand voice alignment remain top concerns (Content Marketing Institute, 2023).
Contently Insight
Contently AI is fully connected to the web, meaning it can pull in the latest trends, data, and industry updates. Even better, it can be connected to your company’s existing content library, ensuring that AI-generated content aligns with brand-approved insights, past work, and unique expertise.
Step 5: AI Isn’t Replacing Writers—It’s Making Them More Efficient
Writers and editors aren’t going anywhere, but their workflows are changing fast. AI isn’t here to replace human creativity—it’s here to accelerate content production, improve efficiency, and eliminate time-consuming tasks.
How AI is being used in content today:
- Helping brainstorm blog topics, headlines, and social captions
- Generating great first drafts (that still need human editing!)
- Automating repetitive content (product descriptions, FAQs, etc.)
But AI alone won’t create thought leadership. It can only remix existing ideas, not generate new, expert-driven insights. That’s why the best content still comes from real experts who can challenge trends, add personal perspectives, and create unique narratives.
A real-world example: If you ask ChatGPT, “What’s the future of content marketing?” it might predict trends based on past articles—but it won’t have an original take like an industry expert would.
Contently Insight
With Contently AI, Writers and Managing Editors can use AI Content Agents to accomplish their clients’ tasks faster and at a higher quality bar. This means they can generate first drafts in minutes, refine them using Contently’s fine-tuned AI for brand and voice consistency, and focus their time on high-value editorial work. Instead of getting bogged down in repetitive tasks, teams can scale content production efficiently while ensuring that every piece is fact-checked, optimized, and ready for publication.
The Takeaway: AI Is a Content Accelerator, Not a Replacement
AI isn’t replacing content teams—it’s amplifying their capabilities. When used strategically, it enhances creativity, speeds up workflows, and ensures every piece of content meets the highest standards.
But not all AI is created equal. Many AI tools generate content that sounds good but lacks originality, accuracy, or strategic alignment. That’s where Contently AI stands out.
With fact-checked insights, real-time data integration, and brand-specific fine-tuning, Contently AI helps content teams:
- Create high-quality, on-brand content faster by generating structured outlines, first drafts, and optimized copy.
- Ensure accuracy with built-in fact-checking that verifies claims before they appear in content.
- Stay ahead of industry trends with real-time web connectivity and access to past company content for deeper context.
- Scale content production efficiently while freeing up time for strategic storytelling and editorial oversight.
The future of content marketing isn’t about choosing between humans and AI—it’s about using AI as a content coworker that empowers teams to create better, smarter, and more impactful content. With Contently AI, your team isn’t just keeping up—they’re leading the way.
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