Here’s the lifecycle of the AI experiment in a software development company:

Honeymoon phase: “AI greatly increases productivity, we can reduce the number of programmers, get the product finished more quickly and gain a competitive edge; let’s use as much of it as possible and evaluate coders by token use, because it’s a productivity multiplier so coders who use more AI are more useful to the company”.

Greed phase: “AI greatly reduces or completely negates the differences between programmer skill levels; it just requires precise instructions. This means we can eliminate expensive programmers and replace them with writers of precise instructions for the AI. This is a generic job that requires far less training and qualifications and makes the employees easily replaceable and cheap. Oh goody.”

Mature phase: “We no longer hold any competitive advantage since everybody uses the AI. Also, our code base became a black box since no human in the company can actually inspect it and evaluate AI’s work. We are experiencing unfixable bugs, random outages, and AI intelligence level drops that make it impossible to understand its previous work, let alone fix it. The customers are complaining, but we can’t do anything about it now since our entire code base is AI-produced and AI-maintained and our human employees are all merely human interface for the AI. All our human coders either quit after we offered them pay cuts and/or limited promotion potential, or we fired them. We might have to start looking for programmers to supervise the AI, but since the code complexity is enormous, the cost would be order of magnitude greater than what we started with. Also, since we started experiencing outages and service degradation, the customers started leaving, and we lost 30% of revenue because they refuse to pay for our “AI slop”. We don’t actually have the finances that can handle the cost of employing high-end coders.”

Nightmare phase: “The AI providers understood that they have us hooked and are steadily increasing the token prices for the last year. They are also introducing tiered pricing scheme, where only the top tier is useful for our needs, but it’s astronomically priced and we can no longer afford it. Our token consumption went hyperbolic since the AI constantly generates problems that require enormous numbers of tokens to resolve. Also, there are all kinds of sanctions so American and Chinese providers are limiting access to their most useful models. We lost more than half of our customer base because they say our product became AI slop; the web interface is crashing, the data contains all kinds of nonsense, every now and then things get deleted or show nonsensical results, and they are done with us. We need to start downscaling just to keep the lights on, but if we do so, the product will instantly stop working because nobody will be able to control the AI’s blunders and we might as well close the doors. Why did we even think AI was a good idea in the first place?”