The commoditization of writing was here long before AI
We tend to blame the chatbots for everything wrong with online content these days, pointing fingers at ChatGPT, Claude, and Gemini as the villains responsible for flooding our feeds with generic, forgettable prose that all sounds remarkably similar, but that's not entirely fair to the technology itself.
The frameworks were already there long before anyone had heard of large language models. PAS, AIDA, BAB, QUEST, FAB—these copywriting formulas have been taught in marketing courses for decades, deployed by agencies worldwide, and used as the backbone of content marketing strategies across every industry. They're effective for their intended purpose, sure, but they're also deeply formulaic, producing predictable patterns that anyone with even a passing familiarity with marketing can spot from a mile away.
Long before ChatGPT existed, LinkedIn was already overflowing with posts following these exact templates, and the "humblebrag industrial complex" that we now complain about was already thriving. The ghostwriting industry was already massive, with an estimated 15-20% of funded startup founders using ghostwriting services and over 200 agencies operating globally by 2024. The pattern was always the same: a provocative hook designed to spark curiosity, followed by a series of short one-sentence paragraphs that felt profound but said little, a bullet list of supposed takeaways, and a reflection question at the end designed to drive engagement—the content changed from post to post but the template never did.
AI didn't create this emptiness; it just made it faster to fill the template.
The frameworks we already knew
Let's look at what was already happening before AI entered the picture, because understanding this context is essential to understanding what the real problem actually is.
PAS (Problem-Agitate-Solution) is one of the oldest and most widely used copywriting frameworks, and it works by first identifying a problem that the reader relates to, then agitating that problem by making it feel more urgent or painful, and finally offering a solution that the product or service provides. It's effective for sales copy, but it's also entirely predictable once you know the pattern.
AIDA (Attention-Interest-Desire-Action) follows a similar logic, grabbing attention with a bold statement, building interest by explaining the benefits, creating desire by painting a picture of the outcome, and then asking for action with a clear call to action. It's the oldest trick in the book, and it's been used so widely that readers have become nearly immune to it.
BAB (Before-After-Bridge) takes a slightly different approach by showing the reader the before state of their problem, then showing them the after state where the problem has been solved, and finally bridging the gap with the product or service that makes the transition possible. Simple, formulaic, and effective, but also hollow when used without genuine substance.
QUEST (Qualify-Understand-Educate-Stimulate-Transition) is a more elaborate version that qualifies the audience, understands their needs, educates them about the solution, stimulates their desire, and transitions them to a call to action.
These frameworks aren't wrong to use, and they serve a legitimate purpose in marketing and sales contexts. The problem isn't the container itself—it's the lack of anything meaningful to put inside it, the emptiness that becomes obvious when the same template is used over and over again without genuine insight or authentic perspective.
The LinkedIn ghostwriting industry
The ghostwriting industry that flourished before AI provided a clear preview of what was to come, because those ghostwriters were essentially doing the same thing that AI does now—producing formulaic content for people who didn't have the time or inclination to write it themselves. By 2024, the numbers were already striking: an estimated 15-20% of funded startup founders were using some form of ghostwriting service, and over 200 dedicated LinkedIn ghostwriting agencies had emerged to serve this growing market. Solo ghostwriters were charging anywhere from $1,000 to $5,000 per month for their services, and they were following the same patterns that we now associate with AI-generated content. The output was generic because the input was generic, and the ghostwriters were writing for people who often had nothing particularly authentic or interesting to say, just a need to maintain a visible presence on the platform.
The AI acceleration
Then ChatGPT arrived in late 2022, and everything changed in ways that we're still trying to understand and process.
Suddenly, you didn't need a ghostwriter at all, and you certainly didn't need to pay $3,000 per month for someone to write formulaic posts on your behalf—you could simply generate the same kind of content yourself, for free, in seconds. The floodgates opened, and the impact was immediate and measurable in ways that researchers have been documenting ever since.
One detection firm analyzed nearly 9,000 English-language LinkedIn posts with more than 100 words and found that 54% showed clear signs of AI generation, representing a staggering 189% jump from pre-ChatGPT levels. Post length doubled across the platform, and engagement patterns shifted significantly, with the algorithm increasingly rewarding standardized formats that fit certain predictable patterns. The frameworks that had already been empty were now being filled at lightning speed, and the acceleration of emptiness became impossible to ignore.
The real problem: authenticity
But here's the thing that we often miss when we complain about AI content, and it's the point that gets lost in all the hand-wringing about technology. The problem isn't really the copywriting frameworks themselves, and it's not even the AI tools that we're using to fill them; the real problem is the lack of authenticity, the lack of people who genuinely have something to say and the lack of time and space to figure out what that thing is.
The platforms actively encourage this situation, because their business models reward volume over substance and frequency over thoughtfulness. The advice that circulates on social media is almost always the same: you need to post constantly, to maintain a visible presence, to show up every single day no matter what. Buffer's analysis of 2 million LinkedIn posts confirmed that posting more frequently does help with performance, because the algorithm rewards frequency with more impressions, more engagement, and more reach. Richard van der Blom's research found something more nuanced though, showing that creators who increased their posting frequency from 5x to 7x per week during the 2025 reach crash actually saw a 27% drop in average reach per post.
The message is confusing, but the pattern is clear: the algorithm rewards frequency, but it also rewards quality, and the people who post too much start to get ignored because their content becomes predictable and empty. The LinkedIn feed is increasingly dominated by AI-generated template posts, putting the credibility of B2B leaders at serious risk, and this is the direct result of the pressure to post constantly without having anything authentic to say.
The paradox of writing
Here's the paradox that sits at the heart of this entire situation, and it's something that I've been thinking about a lot recently.
To have something worth saying, you actually need to take a step back from the constant production cycle and give yourself the time and space to reflect, to process your experience, and to find the insight that makes your perspective unique and valuable. The platforms don't allow this kind of reflection, because they demand constant output and punish periods of silence with algorithmic irrelevance. The people who are actually doing interesting work in their professional lives often don't have time to post about it constantly, because they're too busy doing the work itself. The people who are posting constantly, meanwhile, often don't have time to do interesting work, because they're too busy producing content about what they supposedly do.
This is the acceleration of emptiness: the faster we post, the less we think, and the less we think, the less we have to say that's actually worth reading.
The alternative
The alternative is simple, but it requires a different relationship with both the platforms and the tools.
Write less, think more, and say something worth saying—this is the approach that actually builds genuine connection and trust with readers. Levee helps with this approach because it doesn't generate full drafts for you, and it doesn't fill empty frameworks with generic prose. Instead, it works alongside you as you write, preserving your voice and helping you express what you actually want to say, not what some template tells you to say.
The choice is yours, and it's becoming increasingly clear that readers can tell the difference. Post constantly and fill empty frameworks with AI-generated generic content, hoping that volume will compensate for lack of substance. Or slow down, think deeply, write authentically, and trust that having something genuine to say is ultimately more valuable than having something to say at all. The platforms want you to choose the first option, because it drives their engagement metrics. The readers who actually matter want you to choose the second, because they're looking for connection, insight, and authenticity.
Levee helps you choose the second option, and that's the entire point.
Try Levee free at levee.theleverage.tech—no card required. Write with AI, not instead of it. Have something to say.