Repricing of Software Engineering Labor
TLDR
A software engineer reflects on how LLMs have compressed the cost of implementing standard software, causing the market to reprice implementation-heavy generalist roles as lower-value work while rewarding deep domain expertise and systems knowledge. The late-2010s funding boom created demand for generalists who could ship features quickly across any technology stack, but LLMs now handle standardized CRUD apps, API integration, and framework-heavy work that once required teams. Going forward, competitive advantage shifts from breadth and implementation throughput to specialized expertise in domains where correctness, reliability, scale, and operational complexity matter.
Why it matters
The AI-native tooling layer is crowded and being an 'AI engineer' is not a moat, as production requires engineers who understand reliability, scale, security, and operational trade-offs.
