6 tasks. March 19, 2026 closed at 48.6x weighted leverage across 85.0 human-equivalent hours in 105 minutes of wall-clock time. Supervisory leverage came in at 196.2x.
That is 2.1 weeks of human-equivalent throughput in 1.8 hours. The ceiling was 80.0x; the floor was 20.0x. 4 of the 6 entries came from a single project.
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor |
|---|---|---|---|---|---|
| 1 | Electron endpoint sync + study plan polish + iOS dashboard + daily rings + 6 coding domain specs | 40.0h | 30m | 5m | 80.0x |
| 2 | Create 6 coding domain specs (Python/JS-TS/DSA/SQL/Git/Linux) for avian-domains + update domain catalog | 16.0h | 15m | 5m | 64.0x |
| 3 | Sync items 7-8: engine endpoints + study plan polish from web to electron | 16.0h | 25m | 5m | 38.4x |
| 4 | iOS dashboard 3-section redesign + daily rings persistence | 6.0h | 15m | 3m | 24.0x |
| 5 | Create image generation prompts for 16 characters + 2 locations + 3 book covers | 3.0h | 8m | 3m | 22.5x |
| 6 | Create landing site spec + company cross-references + spoiler stripping | 4.0h | 12m | 5m | 20.0x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 6 |
| Total human-equivalent hours | 85.0 |
| Total Claude minutes | 105 |
| Total supervisory minutes | 26 |
| Total tokens | 867,500 |
| Weighted average leverage factor | 48.6x |
| Weighted average supervisory leverage factor | 196.2x |
| Human-equivalent weeks | 2.1 |
Analysis
The highest factor of the day came in at 80.0x and the lowest at 20.0x, a spread of 4.0 times between the two. That is a wide range for a single day, and it usually means the day mixed mechanical work with work that needed real judgement.
The largest single entry accounted for 40.0 of the 85.0 human-equivalent hours, or 47 percent of the day. One task carrying that much of the total is worth noting; the average is doing less work than it appears to.
Supervisory time was 26 minutes against 105 minutes of execution, a ratio of about 1 to 4. Supervisory leverage of 196.2x is the figure I find most honest, because it measures the hours I actually spent rather than the hours a machine spent on my behalf.
Every figure here is recorded at the time the work is done rather than reconstructed afterwards. The human estimate is my own judgement and carries the uncertainty that implies; the minutes and tokens are measured. The full dataset, including this day, is available for download.