Log every mistake for 30 days with date, event…

Maintain an error log for 30 days that records date, what happened, and conditions present for every mistake, without analysis or interpretation, to create raw data for pattern detection.

When This Fires

When you want to understand your personal error patterns but don't yet have data
When the same types of errors seem to recur but you can't articulate the common factor
Before designing error-correction systems (Classify errors as execution, knowledge, or judgment…-500) — you need pattern data first
As the raw data source for After 10+ post-action reviews, analyze in aggregate… (aggregate review analysis)

Common Failure Mode

Analyzing each error as it's logged: "I made this mistake because..." This defeats the purpose. The analysis is premature (you have one data point, not a pattern), biased (the emotional context shapes the explanation), and prevents future pattern detection (you've already "explained" each error individually, making it harder to see the aggregate pattern). Log the facts — date, event, conditions — and analyze only after 30 days of accumulated data.

The Protocol

(1) For 30 consecutive days, log every mistake, error, or failure. Set a daily reminder to ensure completeness. (2) For each entry, record three things only: Date/time: when it occurred. What happened: a factual, non-judgmental description. "Sent the email to the wrong recipient" not "I was careless again." Conditions: what was true at the time? Energy level, sleep quality, time of day, workload, emotional state, environment. (3) Do NOT analyze. Do not write "because" or "the reason was." Just facts and conditions. (4) After 30 days: read the entire log in one sitting. Look for patterns across entries: recurring conditions, clustering by time/day/energy, common situational factors. (5) The patterns that emerge from 30 days of raw data will be more accurate and more actionable than any single-instance analysis could produce.