The Specification Trap: Why LLMs Are Assistants, Not Replacements
LLMs are overvalued 'cracked interns' that cannot achieve true autonomy because the cost of supervising and specifying their tasks exceeds the value of their output.
The practice of writing machine-checkable specifications that define the intended behavior of a system, enabling automated verification and serving as a precise contract between design and implementation.
LLMs are overvalued 'cracked interns' that cannot achieve true autonomy because the cost of supervising and specifying their tasks exceeds the value of their output.

Software engineering is shifting from a code-centric discipline to a specification-centric one where AI handles the implementation and humans manage the requirements.
Reliable LLM coding requires using automated tools to eliminate the model's freedom to make poor implementation choices.

Detailed specifications are just another form of code, and using AI to bridge the gap between vague specs and working software is a recipe for unreliable 'slop.'

Executable specifications provide a deterministic 'reality check' for AI-generated code, transforming LLMs from unreliable authors into efficient translators for complex systems.