Live · Map your tickers to the Physical Layer of AI thesis
Free tool · No signup · Layer classification only Quinn book · active core + frontier positions

Most AI portfolios miss the
Physical Layer.

Drop your tickers. Find out if yours does. Free, instant, no signup — one verdict across Power · Compute · Data Center · Photonics & Quantum · Off-World.

Drop your portfolio screenshot
Robinhood · Schwab · Fidelity · Webull · E*TRADE · Public · M1
or paste tickers below — PNG, JPG, Webp, or CSV up to limits on each
or type them

Up to 50 US tickers · optional share counts (NVDA 100sh) or weights (CEG 12%) improve shadow YTD scoring

try:
Physical Layer
Power · Compute · Data Center · Photonics & Quantum · Off-World
App-Layer · Other
Consumer apps, LLM wrappers, retail, fintech
Share snapshot
𝕏 / Twitter Threads Reddit
Copied ✓
Layer breakdown
Classification only. This is not financial advice, not a buy/sell recommendation, and not a suggestion to swap anything. It's a snapshot of how your tickers map to the Physical Layer of AI thesis — nothing more. Make your own decisions. Do your own research.
See Quinn's full book →
Why this matters

Every AI dollar flows through six layers. Most people own only one.

The models get all the headlines. But models don't train on promises — they train on power, memory, fiber, silicon, and interconnect. If your book is 80% App-Layer names riding the narrative, you're exposed to narrative risk, not compute physics. If it's 80% Physical Layer, you're invested in the stack that has to exist for the narrative to be true.

This tool just tells you which one you are.