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As you inadvertently pointed out, AI improvements are not linear. They depend on new discoveries more than they do iteration. We could be in either out of jobs or lamenting the stagnation of AI (again).

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After an innovation phase there is an implementation phase. Depending on the usefulness of the innovation, the integration with existing systems takes time. It is calculated in years, tens of years. Think back on the 80-90s, where it took years to integrate PCs into offices and workspaces.

From your comment, is sounds like you think that the implementation phase of LLMs is already over? And if so, how do you come to this conclusion?

It's not as if we have no idea how to make use of AI in programming. We've been working on AI in one form or another since the 70's, and integrated them with our programming workflow almost as long (more recently in the form of autocomplete using natural language processing and machine learning models). It's already completely integrated into our IDEs, often with options to collate the output of multiple LLMs.

What further implementations of integrating AI and programming workflows have LLMs shown to be missing?

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