Know when to buy, hold or sell a focused watchlist of ~150 AI stocks and US equities, with exact prices and a nightly alert. Catch the upside, skip the crashes. Two minutes a night.
Public ledger, regenerated nightly: 566 closed signals since 2022 · 63.1% ended in profit · every one on the public record, losers included.
No card required for the free tier. Educational tool, not financial advice.
The engine's job is simple: stay with strong names while they trend, step aside before the deep crashes. Scored on held-out data it never trained on, across all 152 evaluated names, that discipline looks like this.
For scale: cash, the S&P 500 and the Nasdaq 100 over the same 4.5 years, dividends included.
About half the worst-case pain, scored on data the engine never trained on, and shallower on 150 of the 152 names.
Held-out means each engine is tuned on the early part of a name's history and scored on the last 40% it never saw, after costs, next-day execution. All 152 evaluated names · July 2026. The universe is picked for engine fit, so treat per-name return edges as a curated list; the drawdown discipline holds across essentially every name. Benchmarks cover the same stretch most held-out windows span, January 2022 to July 2026: S&P 500 and Nasdaq 100 as total return with dividends (SPY, QQQ), cash as the average 3-month T-bill yield. Process on the methodology page, every published signal on the public ledger.
Pick a name. Triangles are the engine's buys and sells. Below, what $10,000 became versus just holding.
Held-out test: the last 40% the engine never trained on · after costs, next-day execution · backtested, not live · July 2026.
| Name | Engine | Just holding | Worst drop |
|---|---|---|---|
| Bitcoin | +34.5%/yr | +7.6%/yr | −23% vs −67% |
| Ethereum | +23.2%/yr | −1.1%/yr | −18% vs −68% |
| ServiceNow | +12.6%/yr | +3.4%/yr | −20% vs −65% |
| PayPal | +0.9%/yr | −14.0%/yr | −2% vs −62% |
| Meta | +35.2%/yr | +17.7%/yr | −20% vs −77% |
| Oklo | +116%/yr | +62%/yr | −47% vs −74% |
| Iris Energy | +324%/yr | +129%/yr | −28% vs −60% |
| Rigetti Computing | +1072%/yr | +315%/yr | −70% vs −77% |
Each name is scored on its held-out 40% (never trained on), after costs, next-day execution. Windows differ per name, which is how young rockets like Rigetti print extreme annualized rates over short stretches. These are names where the engine wins; not every name does, and each stock page says so honestly. Updated July 2026.
The headline GPU names get the attention. The real money sits two to five layers upstream, in the chokepoints nobody watches. We map the whole stack, from raw materials to the power grid, and call every buy and sell.
Plus the adjacent waves AI propels: genomics & AI-health, robotics, quantum, space, fintech. Around 150 names. None get in on a story. Every one had to earn its place against buy-and-hold, risk-adjusted, on data the engine never saw.
The build-out's demand engine is AI capability itself. The most-cited map is Aschenbrenner's "Situational Awareness": steady gains in compute, algorithms, and the unhobbling that turns a chatbot into an agent.
His sharpest point matches the data: the binding constraint becomes power, not chips. That is the whole idea in one line: the money is upstream. An influential but contested view, not a forecast. Read it ↗
The price to buy at, add at, trim at, and the line where you get out.
Signal flips land on Telegram and in your inbox after each close.
One 0-100 read of the whole cycle, from opportunity to overheated.
A running list of strong names trading at a discount, with the reason why.
Free gets you the dashboard, the heat gauge and three stock pages a day, full trade plan included. Pro opens the whole thing: unlimited pages across the 150+ name universe, daily alerts, the at-risk monitor and the model portfolio.






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