ML-SystemDesign/MLSystemDesign

# AI Stage-Gate Review

Use this skill to run a gate review for an AI product and reach a defensible decision: advance, fix-and-recycle, or stop. Stage-Gate is a portfolio-management process that structures an AI product from idea to scale: each **stage** of work ends at a **gate** where results are defended and a Go/Conditional/Kill decision is made. The useful output is not a checklist stamp. It is a decision that says what is proven, what is still a risk, what must be true to advance, and how much to invest next.

**Provenance.** This skill was inspired by and builds on work from [Hushpar](https://github.com/Hushpar). It encodes a generic Stage-Gate process adapted for AI products — six stages on Discovery and Delivery tracks, traffic-light gates, and dual value-and-technical validation. It is a distilled, vendor-neutral adaptation, not a transcription of any one organization's internal playbook; tune the stages, criteria, and thresholds to your own portfolio. It is a sibling of `ml-system-design-review` in the same [ML System Design](https://arseny.info/ml_design_book) skill collection: that skill judges *how good a design is*; this one judges *whether it has earned the next investment*.

The process runs on two tracks — **Discovery** (find and validate ideas) and **Delivery** (build and scale) — across six stages, with an optional **Fast Track** for low-uncertainty products. The AI difference is that value alone is never enough: technical feasibility, data, and alignment must clear each gate too.

## Activation

Use when the user asks to run, prepare for, or judge:

- A gate review or gate defense for an AI product or feature.
- A Go / Kill / Pivot / Conditional-Go decision at any stage.

# Lossless Doc Compress

Use this skill to make a design document shorter without making it say less. The useful
output is not a summary. It is the same document with the filler, hedging, slop, and
repetition removed, plus an honest account of exactly what was cut and what the author
should decide for themselves.

This skill is a sibling of `ml-system-design-review` and `ai-stage-gate` in the same
[ML System Design](https://arseny.info/ml_design_book) skill collection by Kravchenko and
Babushkin: **`ml-system-design-review` grades substance; `ai-stage-gate` decides
Go/Kill; `lossless-doc-compress` trims length without touching substance.**

It encodes a simple, well-worn piece of advice: an LLM-written draft is fine *if* the
author read it, corrected it, and gave it context — that is delegating the editing, not

# ML System Design Review

Use this skill to help book readers apply the ML System Design framework by Kravchenko and Babushkin to a real project. The useful output is not a generic checklist. It is a pragmatic review that tells the team what is blocking, what is cheap to improve, what is already strong, and what lesson is worth sharing.

## Activation

Use when the user asks to review, grade, audit, or improve:

- An ML system design document.
- An ML/AI repository or implementation plan.
- A design-doc PR or architecture proposal.
- A production ML readiness plan.
- A RAG, LLM, foundation-model, fine-tuning, or agentic AI system.