Both forces are playing out simultaneously - which is what makes this hard to forecast.

The generalist capability boost is real. I'm shipping things that would have required frontend, backend, and devops specialists two years ago. But a new specialization is quietly emerging alongside that: people who understand how LLM pipelines behave in production.

This is genuinely hard knowledge that doesn't transfer from traditional engineering. Multi-step agent pipelines fail in ways that look nothing like normal software bugs - context contamination between model calls, confidence-correlated hallucinations that vary by model family, retry logic that creates feedback loops in agentic chains. Debugging this requires understanding the statistical behavior of models as much as the code.

My guess: the profession splits more than it unifies. Most developers will use LLMs to be faster generalists on standard work. A smaller group will specialize in building the infrastructure those LLMs run on - model routing, context management, failure isolation, eval pipelines. That second group isn't really a generalist or a traditional specialist. It's something new.

The Fowler article's 'supervisory middle loop' concept hints at this - someone has to monitor what the agents are doing, and that role requires both breadth and a very specific kind of depth.