The problem is many users are not experienced. And the more they rely on AI to do their work, the less likely they are to ever become experienced.
An inexperienced junior engineer delegating all their work to an LLM is an absolute recipe for disaster, both for the coworkers and product. Code reviews take at least 3x as long. They cannot justify their decisions because the decisions aren't theirs. I've seen it first hand.
The solution to bad abstractions it not to make it very difficult to create abstractions at all. For systems code I think it's fine but for application code you probably want some abstractions or else it's very hard to scale a codebase.
It’s really not though. Plenty of systems are built in Go, Erlang etc that do not have the architectual monstrosities which commonly show up in object-oriented code, especially when a Java or C# expert beginner has been let loose.
They have a lot of employees. I think over 50. Probably more than they need and they re-invest a lot in the business. Also, the cost of $15 per user per year is VERY LOW.
50 employees generating 6.5 mil in yearly sales means the business would barely cover payroll and basic expenses in a first world country. In a lower income country, they can be profitable by taking advantage of cheap labor, but that usually does not scale well to international markets in services.
There’s literally no evidence they did either of these things. I really hope these companies can explain their hiring process as it reflects badly on them that they keep calling him top 0.1% without any explanation of their process.
What was your interview process like? I think that would be helpful information in helping design a better vetting procedure to avoid this in the future.
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