Note: This section is primarily for my personal reviews and post-mortems. If you find it interesting or useful, you’re welcome to read along.

Why I write this

I decided to treat investing as something worth doing properly—not something I ignore until volatility forces my attention.

I also admit a human motivation: investing adds a bit of intensity and color to life. But I learned the cost early: investing can silently consume time and attention, and my math study and projects slow down.

That is why I document and review: to keep investing explainable, repeatable, and in the background, so I can go further without sacrificing what matters most.

Attention boundary (math comes first)

To prevent investing from hijacking my schedule:

  • I keep investing in small, scheduled windows (and avoid “always-on monitoring”).
  • If I break this boundary, it must be written down and reviewed.
  • The goal is not to “win every week”, but to remain consistent for years.

How to read this section

If you’re new:

  1. Read the Playbook first (the “constitution” — world-view, methodology, decision standard).
  2. Scan a few entries in the Log (execution in the wild).
  3. Browse Lessons (rules backed by concrete cases — historical v1.x record).
  4. Use Monthly Reviews to see how structure and attention drift over time.

Decision standard (before any action)

For any potential position:

  1. Apply risk vectors (rate / geopolitical / AI bubble / regulatory / macro fiscal) sector-specifically — no universal “should I be in stocks?” answer.
  2. Apply the Interconnections framework — first-order financials are insufficient; second-order sector ecosystem analysis separates driver from symptom.
  3. Compare risk-adjusted potential return to near-riskless yield (T-bill / money market / short-duration bonds). If below → skip; if above → proceed to sizing.

Cash level is the cumulative downstream result of these decisions, not a policy target.

Tools (operational layer)

These pages back the Playbook with concrete, frequently consulted state:

  • Watchlist — candidate pool of names not held but in active monitoring, with explicit trigger conditions.
  • Circle of Competence — core / edge / outside map; where I have edge, where I’m learning, where I should fast-skip.
  • Calibration — Tetlock-style prediction tracking; every substantive thesis gets a confidence + deadline + verification source.
  • Calibration Methodology — 5-step process for deriving a defensible confidence number (not intuition).

Cadence

  • Log: not frequent — just honest and close to the decision (3–10 minutes).
  • Monthly review: once per month, mainly to detect drift and attention cost.
  • Lessons: if the same mistake appears twice, it gets turned into an explicit rule.
  • Sector library / calibration review: quarterly (90 days) or trigger-based.