Article argues that language models should be constrained by linters and tools before generating content, since models are non-deterministic and cannot reliably maintain structural consistency across documents. Rather than relying on prompt engineering, developers should encode structural rules into executable parsers and validators that models can be optimized against.
PCBSchemaGen is a benchmark and verification framework for evaluating LLM-generated PCB schematic designs. It provides 227 synthesis tasks and a deterministic 5-layer verifier that checks candidate SKiDL designs against electrical and topological constraints derived from IC datasheets, without requiring simulation or API calls.
A blind test of ChatGPT, Claude, and Gemini across 20 everyday tasks found ChatGPT leading with a 40% clean win rate, Claude second at 25%, and Gemini at 15%, with 20% of prompts resulting in ties. The evaluation revealed genuine failures: Gemini prescribed unsafe exercises to a back-pain patient, Claude violated explicit recipe constraints and exceeded character limits, and Gemini missed documented meeting action items. Scoring was based on task completion, factual accuracy, clarity, usability, and format compliance.