this post was submitted on 30 Sep 2025
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I work adjacent to software developers, and I have been hearing a lot of the same sentiments. What I don't understand, though, is the magnitude of this bubble then.
Typically, bubbles seem to form around some new market phenomenon or technology that threatens to upset the old paradigm and usher in a new boom. Those market phenomena then eventually take their place in the world based on their real value, which is nowhere near the level of the hype, but still substantial.
In this case, I am struggling to find examples of the real benefits of a lot of these AI assistant technologies. I know that there are a lot of successes in the AI realm, but not a single one I know of involves an LLM.
So, I guess my question is, "What specific LLM tools are generating profits or productivity at a substantial level well exceeding their operating costs?" If there really are none, or if the gains are only incremental, then my question becomes an incredulous, "Is this biggest in history tech bubble really composed entirely of unfounded hype?"
From what I've seen and heard, there are a few factors to this.
One is that the tech industry right now is built on venture capital. In order to survive, they need to act like they're at the forefront of the Next Big Thing in order to keep bringing investment money in.
Another is that LLMs are uniquely suited to extending the honeymoon period.
The initial impression you get from an LLM chatbot is significant. This is a chatbot that actually talks like a person. A VC mogul sitting down to have a conversation with ChatGPT, when it was new, was a mind-blowing experience. This is a computer program that, at first blush, appears to be able to do most things humans can do, as long as those things primarily consist of reading things and typing things out - which a VC, and mid/upper management, does a lot of. This gives the impression that AI is capable of automating a lot of things that previously needed a live, thinking person - which means a lot of savings for companies who can shed expensive knowledge workers.
The problem is that the limits of LLMs are STILL poorly understood by most people. Despite constructing huge data centers and gobbling up vast amounts of electricity, LLMs still are bad at actually being reliable. This makes LLMs worse at practically any knowledge work than the lowest, greenest intern - because at least the intern can be taught to say they don't know something instead of feeding you BS.
It was also assumed that bigger, hungrier LLMs would provide better results. Although they do, the gains are getting harder and harder to reach. There needs to be an efficiency breakthrough (and a training breakthrough) before the wonderful world of AI can actually come to pass because as it stands, prompts are still getting more expensive to run for higher-quality results. It took a while to make that discovery, so the hype train was able to continue to build steam for the last couple years.
Now, tech companies are doing their level best to hide these shortcomings from their customers (and possibly even themselves). The longer they keep the wool over everyone's eyes, the more money continues to roll in. So, the bubble keeps building.
When the AI bubble bursts, even janitors and nurses will lose their jobs. Financial institutions will go bust.