Why I'm still bearish on LLMs after Navier-Stokes

The author remains bearish on LLMs, despite impressive demonstrations like Navier-Stokes, due to the high labor costs associated with rigorous specification and validation. They argue that formal specifications often evolve with implementation insights, and verifying against high-level specifications is currently insurmountable. Furthermore, while frontier labs are priced on the narrative of fully automated knowledge worker replacement, current models require extensive oversight even for simple tasks, contrasting with the continued employment of lower-quartile software engineers who would score below these models on benchmarks.

Unlike many optimistic views, this analysis argues against LLM scalability by comparing specification costs in software to hardware engineering's higher validation overhead.