6 tasks. May 5, 2026 closed at 27.3x weighted leverage across 130.5 human-equivalent hours in 287 minutes of wall-clock time. Supervisory leverage came in at 652.5x.
That is 3.3 weeks of human-equivalent throughput in 4.8 hours. The ceiling was 144.0x; the floor was 8.0x. 6 of the 6 entries came from a single project.
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor |
|---|---|---|---|---|---|
| 1 | Bulk-migrated 568 legacy lab step-issues: wrote scripts/migrate_free_labs.py extracting code blocks + filenames into editor-create-file uiSteps; flagged 341 templated-stub labs as shipping:false. Audit now… | 60.0h | 25m | 1m | 144.0x |
| 2 | Five follow-ups: fixed 522 mismatched/wrong-type checkpoints across 245 labs (auto-detector); split 66 && commands across 44 labs; flagged gql-lab-01 as shipping:false; investigated vitest hang (it is just… | 32.0h | 75m | 1m | 25.6x |
| 3 | Lab audit cleanup (32 issues→0) + per-cert lab-examples-by-simulator doc + simulator-inventory doc covering 8 shipped + 8 planned simulators | 14.0h | 35m | 4m | 24.0x |
| 4 | Reschedule AccelaStudy launch May 5 -> May 11 + cascade dates across plan, canonical-values.yaml, press kit, launch-content drafts, and CLAUDE.md | 2.5h | 12m | 4m | 12.5x |
| 5 | Deleted legacy action-dispatch.ts (20K LOC) + bridge from generic-executor; made expectedActions optional in lab-types; fixed pre-existing lab-loader test failures; ran Watch sweep on 65+ migrated labs (~92%… | 14.0h | 80m | 1m | 10.5x |
| 6 | Watch sweep complete (2.6h, 1700 labs, 36 partial). Triaged: removed 103 unwired propertiesPresent in 69 cloud-cert labs (recovered 8 partial->full); fixed az-204 slots->deploymentSlots property name; flagged… | 8.0h | 60m | 1m | 8.0x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 6 |
| Total human-equivalent hours | 130.5 |
| Total Claude minutes | 287 |
| Total supervisory minutes | 12 |
| Total tokens | 1,134,000 |
| Weighted average leverage factor | 27.3x |
| Weighted average supervisory leverage factor | 652.5x |
| Human-equivalent weeks | 3.3 |
Analysis
The highest factor of the day came in at 144.0x and the lowest at 8.0x, a spread of 18.0 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 60.0 of the 130.5 human-equivalent hours, or 46 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 12 minutes against 287 minutes of execution, a ratio of about 1 to 24. Supervisory leverage of 652.5x 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.