Build a product -> make it free or very affordable -> create dependency -> collect user data to improve product resulting in more dependency -> create a near market monopoly if possible -> make it paid only or make the free version a lot worse so users have to pay -> cross fingers that no alternative emerges or just buy it and shut it down if you can.
Always the same pattern.
That’d be 691077 regular sized hamburgers laid next to each other in a rigid grid pattern, 797502 if laid in a hexagonal pattern, 891720 if squished.
Create a captive audience through monopoly or near monopoly on a given market, then charge them more for a worse version of the product, reducing costs and maximizing profits, it’s always been the goal with corporate capitalism, look at the whole Copilot and GitHub situation right now.
Me smelling the different camemberts in the aisle to find the stinkiest most ripe one to buy.
The strategy is always to gain a monopoly or near monopoly on a market before pushing for the enshittification of the product to reduce costs and maximize profits, once customers have become dependent on said product, then pray that most choose the path of least resistance which is staying and dealing with the worse and more expensive version of what they’re used to rather than retraining or restarting from zero elsewhere.
Capitalism 101.
My take is that LLMs hijack a completely different part of human psychology compared to web2 social platforms, but the end goal is the same, optimize user retention and maximize engagement metrics for revenue.
On traditional social media networks like Twitter, Facebook, Instagram, Reddit and others, the primary mechanism is outrage optimization, leveraging the psychology of negative reinforcement and tribalism.
The algorithm curates content designed to trigger moral anger or cognitive dissonance, the platforms know that users will interrupt passive scrolling to actively comment, share, or debate if something falls outside the usually acceptable social norms.
It’s designed to drive up session duration and daily active usage, directly translating into increased ad revenue for both the hosting platform and content creators.
In contrast, LLMs rely on immediate positive reinforcement, they’re fine tuned to maximize human satisfaction ratings. They systematically agree with the user, validate their subjective bias, reinforce their beliefs.
This results in a psychological safe haven dependency, where users increasingly rely on the interface for emotional reinforcement or stabilization, interacting with the model provides data for the host company to train the next model, raise VC capital and inject better ads in conversations as OpenAI started to do recently.
In both cases, it’s definitely a form of addiction.
I call it the great illusion of “globalism for thee but not for me”.
The managerial class in the Western world championed globalized trade, outsourcing, and open markets under the assumption that only low skilled, blue collar workers would face market disruption. When that happened, the working class was told to “retrain for the digital age”, in other words “deal with it, not our problem nor responsibility”.
This credentialed elite mistakenly believed that their specialized degrees, cognitive skills, and institutional placement rendered them permanently immune to the same forces of automation, offshoring, and global competition they so eagerly unleashed on others.
That illusion is shattering today for several macroeconomic and structural reasons, the original architecture of globalism, as engineered in the 80s, completely failed to anticipate the modern shifts redefining our world, the total digitization of the economy through the internet, foreign competitors like China bypassing Western credentialized gatekeeping entirely to scale up the value chain, and the rise of automation also eroding the premium on cognitive labor.
In the end, they’re just reaping what they sow.
“Generate an image of David Tennant as the Doctor on the BBC.”