Market snapshot, not real-time
S&P 500 (SPY) $748.62 +0.88% Nasdaq-100 (QQQ) $708.90 +1.85% Dow (DIA) $522.55 +0.89% Russell 2000 (IWM) $295.82 +1.20% 10-Year Treasury (IEF) $93.32 −0.23% Crude Oil (USO) $128.37 +2.28% Gold (GLD) $373.85 +1.70% US Dollar Index (UUP) $28.45 +0.23% Volatility (VXX) $21.29 −3.77% Semiconductors (SMH) $583.24 +4.37% Silver (SLV) $53.36 +4.67% Emerging Markets (EEM) $65.45 +2.97% Bitcoin (BTC) $66,470.13 +1.90% Ethereum (ETH) $1,922.88 +1.00% S&P 500 (SPY) $748.62 +0.88% Nasdaq-100 (QQQ) $708.90 +1.85% Dow (DIA) $522.55 +0.89% Russell 2000 (IWM) $295.82 +1.20% 10-Year Treasury (IEF) $93.32 −0.23% Crude Oil (USO) $128.37 +2.28% Gold (GLD) $373.85 +1.70% US Dollar Index (UUP) $28.45 +0.23% Volatility (VXX) $21.29 −3.77% Semiconductors (SMH) $583.24 +4.37% Silver (SLV) $53.36 +4.67% Emerging Markets (EEM) $65.45 +2.97% Bitcoin (BTC) $66,470.13 +1.90% Ethereum (ETH) $1,922.88 +1.00%

Methodology

Learning in Practice

The habits behind this project — curiosity, accountability, context, and openness to challenge — made visible in the work itself.

This is not a credential checklist. It is a record of how ideas from class become more useful when they are tested against evidence and revised in public.

HabitWhat it requires in practiceWhere it's demonstrated here
Intellectual curiosity that goes looking for the counterargument Not settling for a comfortable conclusion — actively seeking out the case against your own position The mandatory Bear Case column in every position's Risk/Reward table and the Learning in Practice page.
Accountability that survives a bad month as well as a good one Publishing results and mistakes on the same schedule, regardless of how either one looks The Portfolio Review & Retrospective format in every full letter, and the standing Compliance Ledger that keeps a rule breach listed until it's actually resolved
A human-centered read on what a company's numbers actually mean Treating a balance sheet as a description of a real business with customers and employees, not an abstract spreadsheet Every position's Fundamental Case, and the Opinion section's editorial writing on the businesses and people behind the AI capex theme
Pressure-tested research over solitary conviction Being wrong in front of someone who will tell you so, not just in front of yourself Named plainly as a limit of this project: the work is independent, but stronger conclusions come from thoughtful challenge before action as well as after.

The honest version of this page

A crosswalk table is easy to write and easy to overstate. The real claim here is narrower: these habits matter only when they are visible in the work — in the sources, the written rules, and the record of changed views.

A worked example, not just a table

Rather than only assert these habits, The Physical Limits of Compute is one underneath them: a full industry whitepaper on the 2026–2027 AI-infrastructure cycle, including a dedicated section arguing against my own thesis and a closing section on how the research actually changes what I hold. It is the same rigor from the table above, applied once, in full, on the record.

Download the whitepaper (.pdf) →