Claude Code is extremely easy to set up and use. I suspect its saturation among software professionals is at the majority of the addressable market.
What if there are no other killer apps for Enterprise? Only CC will produce the level of token churn that could drive huge profits for model providers.
The Enterprise market is not as substantial as the rapid success of CC makes seem.
I thought AI video was the future? Now the biggest AI company in the world is straight up shutting their service down because it's too expensive? Simply a disaster for OpenAI and the industry as a whole.
A rebuttal: the institutional and experiential barriers to wealth generation can be overcome with AI unlike any other technology before. Consider: someone wanting to start a business previously had to negotiate tremendous legal/compliance/technological hurdles. The prospect of going alone given these is very intimidating so most without wealth or connections didn't. Their good ideas languished. Now, everyone has a knowledgeable and forgiving partner and guide.
Capital flows to where it enjoys the greatest returns. That is not Europe, not now nor in any foreseeable future. There is no reason for a skilled professional interested in making money to go there.
The EU is going to fail in the next decade or two. It is a financially and politically unsustainable patchwork that will rip apart in the great power conflict that is coming. The sick man of Europe is now Europe itself.
Did it not work after the first try and you gave up? Did it not produce any usable code that you could hand tweak or build off of? I want to understand your definition of "failed" here.
But it's so easy to try something like Claude Code. It's not like you need to get up to speed. There is no learning curve*, that's the nature of AI. Just start using it and you'll see why it has attracted so much hype.
*I should qualify that "using" CC in the strict sense has no learning curve, but really getting the most out of it may take some time as you see its limitations. But it's not learning tech in the traditional sense.
Waste and inefficiency is real. As unpalatable as it is, cleaning up the mess of decay often requires brutal methods. That begs the question, is waste and inefficiency socially undesirable? Maybe not. Maybe not on certain scales or in isolation. But waste compounds.
These very valid points apply to all companies trying to make money off of proprietary models, which means margins are going to collapse in a vicious price war that will make Uber vs Lyft seem tame.
As margins collapse capex will collapse. Unfortunately valuations have become so tied to AI hype any reduction in capex will signal maybe the hype has gotten ahead of itself, meaning valuations have gotten ahead of themselves. So capex keeps escalating.
None of this takes into account the hoarding effects at play with regards to GPU acquisition. It's really a dangerous situation the industry is caught in.
I will admit, one thing the crowd attention model does exceptionally well is surface the best comments on content. Whether it's HN, Instagram, YouTube, etc... the top comments are usually the "best", depending on how best is defined in the given context. On the silly Instagram meme videos my algo serves up, the top comments are invariably hilarious, often funnier than the actual content, and as you scroll it's impressive how the ordering by like count matches hilarity quite well.
It is fascinating to observe the concept of protest, like so many other concepts recently, being hijacked and misappropriated to mask something else entirely. We have a particular conception of the term, what it implies, what it evokes, yet it is frequently being used to describe activities that clash with the implicit features carried by the term. This is a form of semantic warfare, in which words become enmeshed in the fog of war.
To be more precise, one aspect of what I'm describing relates to the mass production of protest, the formation of an inorganic protest "complex". Protest is popularly considered a spontaneous, organic outpouring of popular sentiment, something that reflects the mass will of a people suppressed by some hostile power. Yet increasingly protest is being used by hostile forces in a pre-meditated, engineered, inorganic way while maintaining the appearance and narrative of the "traditional" conception of protest, which it resembles less and less.
This is just one example of the general case of a metric ceasing to be useful once it is recognize as a metric. Once we begin explicitly trying to target some metric, some behavior, some form, we effectively become liars as the form we take no longer speaks to some deeper truth as it was originally meant to.
What if there are no other killer apps for Enterprise? Only CC will produce the level of token churn that could drive huge profits for model providers.
The Enterprise market is not as substantial as the rapid success of CC makes seem.