MLSystemDesign

Use when running a stage-gate or gate review for an AI product, deciding Go/Kill/Pivot at a gate, judging whether an AI initiative is ready to advance to the next stage, triaging a portfolio of AI ideas, or choosing between a full and a fast-track path. Applies a Stage-Gate process built for AI products — incremental investment, dual value-and-technical validation, alignment/ethics/data checks at every gate — to reach an evidence-based gate decision.

Use when reviewing ML system design docs, ML/AI project repos, design-doc PRs, RAG/LLM/foundation-model architectures, agentic AI workflows, or production ML readiness. Applies the ML System Design framework by Kravchenko and Babushkin to grade designs, compare docs with code, find critical gaps and low-hanging fruit, and give specific non-cringy praise.