13 tasks. May 2, 2026 closed at 17.0x weighted leverage across 395.0 human-equivalent hours in 1,393 minutes of wall-clock time. Supervisory leverage came in at 353.7x.
That is 9.9 weeks of human-equivalent throughput in 23.2 hours. The ceiling was 60.0x; the floor was 3.4x. 12 of the 13 entries came from a single project.
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor |
|---|---|---|---|---|---|
| 1 | Embedded subscribe flow: PaymentIntent backend + recompute + coupon validate endpoints, new shared @avian/subscribe-react lib (FlipCard primitive, SubscribeFront/Back, EmbeddedSubscribeFlow,… | 24.0h | 24m | 6m | 60.0x |
| 2 | Cloud-cert lab Batch 5 wave 1: AZ-204 cluster shared root cause diagnosis (stale sidebarTarget bug) lifted all 19 AZ-204 labs in one shot, plus partial progress on AZ-305/AZ-500/DEA-C01. 26 newly strict-pass;… | 52.0h | 120m | 3m | 26.0x |
| 3 | Operator-managed banners across avian-admin/avian-api/avian-app-web with markdown CRUD, semantic color variants, audience targeting from purchase state, push-to-all-clients SSE broadcast, dismissal tracking,… | 28.0h | 65m | 6m | 25.8x |
| 4 | Diagnose hard hang from disk-full + memory exhaustion (Docker VM + TM + Spotlight + Maestral); archive 123 GB training chunks to new S3 bucket with byte-exact verification | 3.0h | 7m | 4m | 25.7x |
| 5 | Cloud-cert lab Batch 3: lifted 100 closest-to-passing labs (gap 5-30) to strict-pass via sub-agent across 11 waves. Service-cluster fixes on dp-420, dp-700, dp-900, az-400, ai-900, plus per-lab fixes.… | 100.0h | 293m | 5m | 20.5x |
| 6 | Add purge + bulk-purge for revoked comps across purchase-service, admin-service WS, and avian-admin UI with tests | 4.0h | 12m | 3m | 20.0x |
| 7 | Cloud-cert lab Batch 4: harder set of 100 partials (gap 20-40, AWS 28 / Azure 24 / GCP 48) lifted to strict-pass via sub-agent across 7 waves. Heavy dashboard work to add testIds for missing modal flows. 810… | 150.0h | 577m | 5m | 15.6x |
| 8 | Testing | 5.0h | 30m | 4m | 10.0x |
| 9 | Documentation | 12.0h | 90m | 12m | 8.0x |
| 10 | Infrastructure | 4.0h | 35m | 4m | 6.9x |
| 11 | Add Rime TTS as alternate provider; add voice/speed picker in Settings with Play audition; wire labs to user-selected voice; deploy backend + frontend + infra to production | 8.0h | 75m | 6m | 6.4x |
| 12 | Engine dual-auth: accept JWTs from auth-service JWKS alongside static AVIAN_API_KEY (jwt_auth module port of gateway core/jwt.py + middleware refactor in rest_gateway.py + tests) | 3.0h | 30m | 4m | 6.0x |
| 13 | Diagnose remaining engine 401s as a frontend bug (engine.ts had its own raw fetch() bypassing Authorization header), audit all api/*.ts callsites, fix engine.ts request()+lesson-audio+evidence-audio paths to… | 2.0h | 35m | 5m | 3.4x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 13 |
| Total human-equivalent hours | 395.0 |
| Total Claude minutes | 1,393 |
| Total supervisory minutes | 67 |
| Total tokens | 2,684,000 |
| Weighted average leverage factor | 17.0x |
| Weighted average supervisory leverage factor | 353.7x |
| Human-equivalent weeks | 9.9 |
Analysis
The highest factor of the day came in at 60.0x and the lowest at 3.4x, a spread of 17.5 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 24.0 of the 395.0 human-equivalent hours, or 6 percent of the day. No single task dominated the total, so the weighted average is representative.
Supervisory time was 67 minutes against 1,393 minutes of execution, a ratio of about 1 to 21. Supervisory leverage of 353.7x 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.