@aflat0n aflat0n

Grade = how their written analysis reads (A best). Trader score = how their last-20 timestamped calls performed vs SPY. · Analyst brief as of 2026-06-22.

aflat0n is mainly calling AI infrastructure capex, memory constraints, Intel foundry momentum, and SpaceX-adjacent scarcity as investable themes. The distinctive read is that bottlenecks in memory, power, packaging, networking and space-based infrastructure are becoming the better way to express AI demand, not just owning the front-line model or GPU names. Late-window attention moved heavily toward memory/foundry and space commercialization, while positioning disclosures were mostly third-party 13F or Berkshire-style ownership notes rather than the author's own book.

The author is concentrated in AI infrastructure, especially bottlenecks around memory, foundry capacity, networking, power and space-enabled compute. Conviction appears to intensify late in the window around MU, INTC, AMD/MEXT and SNDK as memory constraints become a repeated thesis, while SPCX remains a high-frequency bullish focus with pump-risk from valuation and product-launch posts. There are no CALL_DIRECTIONAL trade signals in the payload, and position disclosures are third-party ownership notes rather than clear author adds or trims.

Grade is our human read-worthiness rating; trader score is a rolling 20-bet hit-rate/alpha composite — different things, often disagreeing. “Since then” is direction-unaware in the table; the summary line above adjusts for which way they leaned.