@GestaltU@mxschumacher@Jesse_Livermore Atm I agree. But AI will offer new methods of capture that will probably allow the same contract cycle.
Enterprises can't switch on a dime like consumers.
@GestaltU@Jesse_Livermore Microsoft was a low margin business that leveraged enterprise sales contracts for dominance. IBM used the same tactic at a time when lots of companies had data processing.
Not saying you're wrong. I think you're totally correct. But biz models exist.
@minakimes@Ihartitz 6'5" 288lbs
Six Five, Two Eighty Eight.
Six feet, Five inches tall, Two Hundred and Eighty Eight Pounds.
*silence*
I tried to write that without capital letters, and it just seemed wrong.
@GestaltU@biancoresearch Pretty cool perspective - where to you look for the usage data? Is there a platform for tokens like Chainalysis, or Dune Analytics?
The pace of Micron’s rise to becoming a $1 trillion company is unprecedented. The dot-com boom created millionaires. The aftermath of the 2008 financial crisis minted billionaires. The AI revolution is resulting in trillionaires. https://t.co/0qwUdh7dFG
@GestaltU@TXMCtrades I would apply the same lens to taxation. It's not just the amount or source being taxed, it's the objective of the spend and measurable growth of the investment.
@TFTC21 What I am about to say is openly catty, unfair, and not constructive.
But Tony looks like he's become the wrong doppleganger of himself in The Substance.
I think AI coding hype follows roughly four stages:
1. Amazement
You try it and can’t believe how much code it generates from a few prompts.
2. Expansion
You start more and more projects because shipping suddenly feels cheap and fast.
This is also the phase where people start convincing everyone around them:
- coworkers
- management
- friends in other companies
because nobody wants to “fall behind” in 6–12 months.
That creates a massive snowball/FOMO effect.
3. The grind phase
You realize the generated code has architectural issues, sloppy mistakes, weird abstractions, duplicated logic, broken edge cases, etc.
So you start:
- re-prompting
- switching models
- increasing reasoning effort
- reviewing fixes
- generating fixes for previous fixes
And suddenly you spend your days reviewing AI-generated pull requests instead of building software.
4. Realization
You realize AI coding increases output much faster than it increases certainty.
The code still needs:
- review
- testing
- ownership
- architectural understanding
- long-term maintenance
Usually by expensive senior engineers.
And the interesting thing is:
this whole cycle can take many months or even more than a year because people become socially and professionally invested in the narrative themselves.
Once teams, managers, and entire companies have been convinced that this is the future, it becomes psychologically and politically very hard to later say:
“Actually, the ROI is much lower than we expected.”
Today, among the goods that are universally intended for everyone, we must also include new forms of property, such as patents, algorithms, digital platforms, technological infrastructure and data. In a context where the wealth of nations depends increasingly on knowledge and technology, when these goods remain concentrated in the hands of a few, without adequate forms of sharing and access, a new imbalance is created that contradicts the universal destination of goods. In turn, it widens the gap between the included and the excluded, between those who can participate in the digital revolution and those who remain on the margins. #MagnificaHumanitas
@america This is not accurate.
The Constitution of the United States is wholly predicated on three branches of government who don't trust each other and use their power to check each of the others.