Let's say that as long my as the complexity is low, it is really worth using AI, and you can be twice as effective, maybe more, because it can take care of most

Let's say that as long my as the complexity is low, it is really worth using AI, and you can be twice as effective, maybe more, because it can take care of most of the coding/testing/integration which are 80% of project, and can help you with the architecture part as long as it is easy/standard. As the complexity grow, the usefulness of AI agents decrease: a lot, and quite fast. In particular, integration of microservices are a really hard case to crack for any AI agent as it often mix training data with context data. It is more useful in centralised apps, and especially for front dev, as long as you don't use finite state machines. I don't understand why, even Claude/Cursor trip on otherwise really easy code (and btw if you don't use state machines for your complex front end code, you're doing it wrong). As long as you know what your agent is shitty at however, using AI is a net benefit as you don't loose time trying to communicate your needs and just do it, so it is only gains and no loses.