The biggest technology shift in a generation runs on a few hundred stocks: chips, power, cloud, and the next waves. Hesper Atlas maps about 150 of them and tells you exactly what to do with each, buy, add, trim or sell, at exact prices, with nightly alerts and a public record of how every call played out.
No card required for the free tier. Educational tool, not financial advice.
The headline GPU names get the attention, but the real money in the AI build-out is often two to five layers upstream, in the chokepoints almost nobody watches. So we map the whole stack, from the raw materials a chip is born from to the power grid that feeds the data center, and call the buys and sells on every layer.
Plus the adjacent waves the same AI is propelling: genomics & AI-health, robotics, quantum, space and fintech. Around 150 names in all. And none of them get in on a story. Every name had to beat buy-and-hold on data the engine never saw to earn its place in the universe.
The build-out has a demand engine: AI capability itself. The most-cited map of it is Leopold Aschenbrenner's "Situational Awareness", which counts the steady gains in compute, algorithms, and what he calls unhobbling, turning a chatbot into an agent.
His sharpest point lines up with what the data shows: the binding constraint becomes power and electricity, not chips. That is the whole idea in one line: the money is upstream. The timeline is an influential but contested view, not a forecast. Read it ↗
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% of each name's history, which the engine never trained on · after trading costs, next-day execution · backtested, not live results · updated June 2026.
| Name | Engine | Just holding | Worst drop |
|---|---|---|---|
| Bitcoin | +34.7%/yr | +7.0%/yr | −23% vs −69% |
| Ethereum | +24.5%/yr | −1.5%/yr | −18% vs −68% |
| ServiceNow | +12.7%/yr | +1.1%/yr | −20% vs −64% |
| PayPal | +0.9%/yr | −14.8%/yr | −2% vs −62% |
| Meta | +32.2%/yr | +15.3%/yr | −19% vs −77% |
| Oklo | +121%/yr | +82%/yr | −47% vs −74% |
| Iris Energy | +347%/yr | +209%/yr | −28% vs −60% |
| Rigetti Computing | +1069%/yr | +590%/yr | −70% vs −77% |
Each name is scored on the held-out 40% of its own history (data the engine never trained on) after trading costs, next-day execution. Windows differ per name, which is how young rockets like Rigetti print extreme annualized rates over short stretches. And these are names where the engine wins; not every name does. Inside the app, each stock page shows honestly whether its engine beats holding. Backtested, not live results · updated June 2026.
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.
Every signal is written to a public ledger the day it's published (entry, exit and result) and stays there. If the engine has a bad quarter, you'll see it here first.
See the live track record7-day refund on Pro, cancel anytime. The track record stays public either way. That's the point.
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The free tier takes a minute to set up and shows you the market dashboard, the heat gauge and three stock pages a day.
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