The setup is framed as extreme fear into AI-driven earnings growth: NASDAQ is down more than 5% in 30 days, the S&P 500 down 1.6%, NVDA down 6.3%, while the forward P/E is 19 and earnings growth is still running around 30%. The core claim is that AI now splits into infrastructure and implementation, and the bigger opportunity has shifted to the second wave, where software and platform winners can compound on top of the buildout. Two names get singled out from that second wave, ARM and APP, with scorecard-style cases built around high growth, strong margins, and depressed stock prices. A prior free 15-stock list from December 18, 2025 is used as proof of process, while a May seven-stock list is cited as a more recent validation that the thesis has kept working.
Over the past 30 days, NASDAQ is down more than 5%, the S&P 500 is down 1.6%, and NVDA is down 6.3%, with the selloff tied to AI-bubble fear, massive anxiety, and uncertainty.
A free report on December 18, 2025 listed 15 "generational opportunities"; by near end-October, 11 of the 15 were up and four were down, with an average return of 28 12% and a 73% success rate.
The December 18, 2025 15-stock list is said to have delivered an "28 1/2 benchmark against the S&P with 12 1/2," but remains too soon to celebrate after about 10 months; named stocks from that list include AMD, Crowd, ARM, ASML, AAPL, VRT, and NVDA.
A new free list of "my top 11 stocks" is promised in the video, with no paywall.
Two of the 11 were presented on a 3-hour master class held yesterday that drew 13.5K people and was marked by YouTube as top 1% of all global live streams; the two revealed names were ARM and APP.
The market’s AI selloff is pinned on capex fears, debt taken on to fund it, and the risk that AI companies may not earn enough to cover expenses.
Long term, only earnings drive stock prices: if AI companies keep making money, growing earnings, and expanding margins, stock prices should rise regardless of capex and debt.
The S&P 500 forward P/E is cited at 19, called the 10-year average, while earnings growth is cited at 29.5%, described as above average; valuations staying at average while earnings grow at 30% is called a good setup.
High interest rates are framed as a guardrail against bubbles because money gets expensive and investors become selective; some AI stocks can still go to zero even in a strong bull cycle.
The fear-and-greed index is cited at 21, at historical lows and in "extreme fear" territory, with the claim that crashes happen when people are complacent, not when they are bracing.
Credit conditions are said to be tight: there is no IPO mania despite big IPOs from Anthropic and SpaceX, no meme-stock or crypto-meme frenzy like COVID, and no uptick in trading volume; high volatility is presented as healthy because complacency would show up as a flat VIX.
AI is split into two phases: infrastructure and implementation; infrastructure is still ongoing but much of the money there is already made, while implementation is described as virtually wide open and misunderstood.
The second wave is said to be bigger than the first because it targets businesses built on AI rather than the buildout itself; Amazon is used as the analogy, down 95% in two years from 1999 to 2001 yet still one of the best stocks now.
The first-wave add-ahead-of-time list included NVDA in 2020, AMD, TSM in 2021, AET in 2023, and VRT last year; claimed returns were NVDA +1400%, AMD +560%, TSM +231%, AET +300%, and VRT +80%, and these holdings are said to remain very attractive.
In May of the current year, a seven-stock second-wave list was published; since then six of seven are said to be up 86% on average, with an 86% hit rate and a 32.5% average gain, versus about 0.5% for the S&P 500 and a 32% outperformance since May 29.
The May seven-stock list is said to include ZS up 82%, ZETA up 48%, SNOW, PLTR, CRM up 30%, NOW up 28%, and TSLA down 14.6%, with the claim that all but TSLA were up.
ARM is described as being down 50% while revenue is growing 22%, with $4 billion of cash and zero debt; it is framed as owning the semiconductor infrastructure tollbooth, taking license fees and royalties on every chip sale.
ARM’s metrics are given as 22% revenue growth, 27% free cash flow margin, and a rule of 40 of 49, with a scorecard result of 115 out of 125, losing only because short interest is 1% above threshold.
APP is described as down 65% while growth is almost 50%, free cash flow growth almost 60%, and guidance calls for 50% further growth; its ad tech model inserts ads into app inventory, learns via machine learning/AI, and improves budgets and model performance over time.
APP’s metrics are given as almost $7 billion of revenue, operating margin almost 80%, free cash flow of $4.5 billion, and a rule of 40 of 113.8; on the 125-point scorecard it loses points for debt versus cash at 3.7 versus 3.05 and for not being recession-proof because advertising weakens in recessions.
The other nine stocks are promised for free with the full thesis and report via the description link; the December report and May report are both described as free.
The academy is said to be closed to new members for now, with no promo today and likely no new members until the end of the year.