Snapshot · Modern Wisdom
Mark Zuckerberg announced 8,000 layoffs and keystroke tracking of workers in the same week — illustrating how AI input/output data enables automated replication of cognitive labour.
Where this was said
At 9:50 · chapter starts 6:20
Wright builds his most original argument in this chapter: the training process behind modern AI is not merely a form of machine learning in the conventional sense — it is a form of accelerated evolution. Just as biological natural selection, through trial and error over millions of years, built cognitive machinery into human brains, AI training accomplishes the same feat in compressed form using human-generated data. Nobody told the machines what words mean; they figured it out. Nobody architected the semantic structure; the training process reverse-engineered it. Wright uses this to correct a fundamental error he himself made when he first wrote about Hinton's neural network work in 1983 — he had assumed that meaning would need to be manually programmed in, dictionary entry by dictionary entry. He was wrong. The key revelation: all you need is data, and the machines do the rest. Wright then grounds this in the present tense with the Zuckerberg anecdote — Meta announced 8,000 layoffs and keystroke tracking of remaining workers in the same week, illustrating the exact mechanism: capture what goes in and what comes out, and AI will replicate whatever cognitive process happened in between. The implication for employment is stark and near-term.
AI training processes reverse-engineer cognitive functionality that took millions of years of biological evolution to develop, doing so purely through data.
When Meta announced 8,000 layoffs and keystroke tracking in the same week, it revealed the core mechanism of AI job displacement. Capture the inputs an employee receives and the outputs they produce, and the machine will figure out everything in between — and replace them.
AI independently invented edge detector neurons to recognise visual objects — the same solution evolution built into biological brains.
AI systems have independently invented edge detector neurons — the same solution biological evolution arrived at for visual object recognition. This is convergent evolution happening between silicon and carbon, the same phenomenon that gave crabs their form and flight to birds and bats.
Bhanu grew SiteGPT to $13,000 monthly recurring revenue entirely through organic channels, spending nothing on paid marketing.
More than 1 million people have visited SiteGPT's website since launch in March 2023, all through organic channels.
Approximately 90% of SiteGPT's Google search traffic comes from the free tools Bhanu built, not the main product pages.
Bhanu sold his first SaaS product, Feather, for $250,000 so he could focus fully on the faster-growing SiteGPT.
SiteGPT has generated approximately $500,000 in total revenue since its launch in March 2023.
The average customer lifetime value for SiteGPT is approximately $1,700 to $1,800, which Bhanu considers unusually high.
SiteGPT receives around 50,000 visitors per month, of which about 200 convert to leads and 60 start free trials.
SiteGPT hit $10,000 MRR within its very first month of launch, driven largely by early traction in the AI chatbot space.
Despite strong download numbers, PropGPT could not push past $1,000–$2,000 MRR due to poor product retention.
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