12 tasks. July 19, 2026 closed at 51.8x weighted leverage across 1,310.5 human-equivalent hours in 1,517 minutes of wall-clock time. Supervisory leverage came in at 1355.7x.
That is 32.8 weeks of human-equivalent throughput in 25.3 hours. The ceiling was 86.2x; the floor was 11.7x. 12 of the 12 entries came from a single project.
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor |
|---|---|---|---|---|---|
| 1 | Build all 138 computer_science-cluster interactive simulations on the generalized harness (CS contract with real-algorithm correctness bar; build->verify workflow; recovered from 2 session-limit cutoffs via… | 460.0h | 320m | 3m | 86.2x |
| 2 | Build all 131 core_math-cluster interactive simulations on the generalized harness (math contract with exact-arithmetic correctness bar, jsxgraph->SVG/canvas, build->verify workflow, hand-recovered 2 partials… | 430.0h | 300m | 3m | 86.0x |
| 3 | Remediate all 3 Criticals + 22 Highs from staging readiness audit across 8 repos (engine, avian-api, auth, notification, onboarding, deletion-Lambda, web app, deploy infra): health-check auth exemption,… | 80.0h | 60m | 4m | 80.0x |
| 4 | Full readiness audit: orchestrated 5 parallel deep security+a11y sub-audits (engine/api/web-app/notification/onboarding), reconciled ~75 findings with the canonical pipeline report, produced a consolidated… | 40.0h | 50m | 5m | 48.0x |
| 5 | Full-monorepo canonical-values reconciliation via 36-agent workflow (recompute every value from source: content aggregates across 407 packages, specs, labs, 112-repo build metrics, [ip] from application… | 30.0h | 55m | 8m | 32.7x |
| 6 | Fix all 20 Medium staging-audit findings across 5 repos (engine/avian-api/auth/notification/web) + repair avian-api uncallable onboarding module + port S3 PII-delete endpoint + decommission onboarding-service… | 42.0h | 80m | 5m | 31.5x |
| 7 | Deploy avian-engine to AVIAN staging from staging branch: fixed the image build (uv --no-sources for vendored path-deps, numba>=0.61 for arm64 llvmlite wheel), added a CPU 'staging' profile (cloud d=512 +… | 40.0h | 95m | 4m | 25.3x |
| 8 | Deployment | 140.0h | 360m | 15m | 23.3x |
| 9 | Fix engine SQLAlchemy boot error + migrate engine to GPU in AVIAN staging: resolved branched-alembic-heads (ran 'upgrade heads' -> created governance_audit_log + all engine tables), confirmed GPU quota… | 24.0h | 85m | 4m | 16.9x |
| 10 | Populate AVIAN staging with full prod content + fix engine cold-boot OOM: server-side synced 6370 objects/16.5GB domain packages prod->staging, diagnosed boot-cache-miss forcing a full in-RAM parse (prod… | 16.0h | 70m | 3m | 13.7x |
| 11 | Prep omniscient sweep for all live/candidate/beta packages (403 domains, 3-at-a-time): root-caused engine symlink-overlay data-dir trap in gen_omni_sweep.py readiness gate; added start-temporal-worker.sh… | 5.0h | 24m | 2m | 12.5x |
| 12 | Debugging | 3.5h | 18m | 2m | 11.7x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 12 |
| Total human-equivalent hours | 1,310.5 |
| Total Claude minutes | 1,517 |
| Total supervisory minutes | 58 |
| Total tokens | 67,850,000 |
| Weighted average leverage factor | 51.8x |
| Weighted average supervisory leverage factor | 1355.7x |
| Human-equivalent weeks | 32.8 |
Analysis
The highest factor of the day came in at 86.2x and the lowest at 11.7x, a spread of 7.4 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 460.0 of the 1,310.5 human-equivalent hours, or 35 percent of the day. No single task dominated the total, so the weighted average is representative.
Supervisory time was 58 minutes against 1,517 minutes of execution, a ratio of about 1 to 26. Supervisory leverage of 1355.7x 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.