Monopoly Round-Up: The $2 Trillion Collapse of Bitcoin and Terrible Software Companies
AI is going to displace business software because so much of it is terrible quality crap peddled by monopolists. Policy can help. Plus, bitcoin falls, & enforcers may drop the Ticketmaster suit.
Crypto has gone down by $1.7 trillion in market value since its October peak, with the decline accelerating last week
The blockchain is a foundational groundbreaking technology, only known to a niche segment, and hamstrung by a hostile political environment.
When Trump got elected, the story seemed to play out. Bitcoin jumped in value, and the first “crypto President” appointed friendly regulators. Congress passed the GENIUS Act to legalize "stablecoins" a type of financial instrument based on crypto,
Only, it turns out there are no real use cases for crypto except for money laundering and fraud,
Nvidia CEO Jensen Huang thinks that replacing all software with AI is dumb, akin to re-inventing the screwdriver rather than just buying one that already exists.
But there are sector-specific ones as well, in every nook and cranny of American business.
Tyler Technologies provides software that manages municipal functions, everything from “permitting, police dispatching, jail booking, property appraising, campground reservations, restaurant inspecting, cannabis licensing and school bus tracking.”
As Keeler notes, all of the software incumbents close their ecosystems to prevent rivals from selling to their customers.
If a new company can come in and interoperate with a dominant platform, it can offer a new feature and help make the software ecosystem better. It doesn’t need to displace the platform;
And that’s where generative AI comes in. Over the past couple of weeks, like a lot of journalist-adjacent political types, I’ve spent time using Anthropic’s new tool for creating computer programs. Generative AI tools, from Google’s Gemini to Anthropic’s Claude Code, are now quite useful. They aren’t super-intelligent, they are fundamentally pattern recognition and copying machines, and they still hallucinate and lie. But unlike crypto, there are important use cases where people can deploy these tools to do things they couldn’t do before.
I know of companies that use generative AI to radically accelerate creating tools for projects, but those projects only need to be 90% correct. That’s not the case with, say, health records, or bank transfers. Those have to be correct every time. And if AI systems are given access to important file systems they can accidentally do great damage. But used carefully, generative AI can foster significant gains.
