Building custom eval tools with coding agents w/ Isaac Flath

AI-assisted development requires a structured, human-in-the-loop approach to achieve consistent, high-quality results. Isaac Flath emphasizes moving beyond "vibe coding" by implementing spec-driven development, where clear plans are defined in markdown files before execution. Central to this workflow is the use of "ruler" files, which allow developers to maintain consistent context across various AI agents like Cursor and Windsurf. Furthermore, building custom Model Context Protocol (MCP) servers enables automated debugging, such as capturing client-side browser console logs that standard server logs miss. By treating AI tool reviews as rigorous, task-based assessments rather than superficial demos, developers can better identify which models excel at specific infrastructure or multimodal tasks. This methodology transforms AI from a hit-or-miss assistant into a reliable, integrated component of the software engineering lifecycle.